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title: Scientific Discovery : Logic and Tinkering SUNY Series iPhilosophy and Biology

author: Kantorovich, Aharon.publisher: State University of New York Press

isbn10 | asin: 0791414787print isbn13: 9780791414781

ebook isbn13: 9780585078342language: English

subject Science--Methodology, Science--Philosophy, Creativeability in science, Serendipity in science.

publication date: 1993lcc: Q175.K19 1993ebddc: 501

subject: Science--Methodology, Science--Philosophy, Creativeability in science, Serendipity in science.

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Scientific Discovery

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SUNY Series in Philosophy and BiologyDavid Edward Shaner, editor

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Scientific Discovery

Logic and Tinkering

Aharon Kantorovich

STATE UNIVERSITY OF NEW YORK PRESS

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Published byState University of New York Press, Albany

© 1993 State University of New York

All rights reserved

Printed in the United States of America

No part of this book may be used or reproducedin any manner whatsoever without written permissionexcept in the case of brief quotations embodied incritical articles and reviews.

For information, address State University of New York Press, State University Plaza, Albany, NY 12246

Production by Marilyn P. SemeradMarketing by Dana E. Yanulavich

Library of Congress Cataloging-in-Publication Data

Kantorovich, Aharon. (Date)Scientific discovery: logic and tinkering / Aharon Kantorovich.p. cm. (SUNY series in philosophy and biology)Includes bibliographical references and index.ISBN 0791414779. ISBN 0791414787 (pbk.)1. ScienceMethodology. 2. SciencePhilosophy. 3. Creativeability in science. 4. Serendipity in science. I. Series.Q175.K19 1993501dc20 921766

CIP

10 9 8 7 6 5 4 3 2 1

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in memory of my father

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CONTENTS

Acknowledgments xi

Introduction 1

Part I In Search for Logic of Discovery

Chapter 1: Exposing and Generating 11

1.1 What is a Discovery?

11

1.2 The Products of Scientific Discovery

16

1.2.1 What Do Scientists Discover When They Look at the World?

16

1.2.2 Objects and Events Contaminated by the Scientist's Intervention

17

1.2.3 The Plasticity of Theories

20

1.2.4 Explanations, Problems and Solutions27

1.3 The Kinds of Discovery Processes

29

1.3.1 Exposure

29

1.3.2 Generation

32

1.3.3 Poincaré: The Poverty of Creation

34

1.3.4 Eureka Events and Unintentionality

35

1.4 The Creative Element in Discovery and the Issue of Realism

36



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1.4.1 Discovery, Invention and Creativity

36

1.4.2 The Case of Particle Physics: An Active Look at Matter

39

1.4.3 Epistemological Realism: Construction, Transaction and Representation

44

Chapter 2: The Scope of Method 49

2.1 The Nature and Function of Method

49

2.1.1 Who Needs a Method?

49

2.1.2 What is a Method of Discovery Supposed to Do?

52

2.1.3 The Origin of Method

58

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2.2 Inferring and Reconstructing

60

2.2.1 Reasoning vs. Creativity

61

2.2.2 Discovery as Inference or Reasoning

62

2.2.3 The Quest for Certainty or: How Ampliative Inference Can BeConverted into Deductive Inference

68

2.2.4 The Hierarchy of Material Logics

74

2.2.5 The Discovery Machine

77

2.2.6 Theory-Construction and Research Programs

80

2.2.7 The Calculus of Plausibility: Logic of Pursuit

85

2.2.8 Discovery as a Skill: The Invisible Logic

92

Chapter 3: Why did Taditional Philosophy of Science Ignore Discovery 97

3.1 The Distinction between the Context of Discovery and the Context of Justification

97

3.1.1 John Herschel's Distinction: Consequentialism

97

3.1.2 Reichenbach's D-J Thesis: Generationism

99

3.2 Objections to the Distinction

101

3.2.1 Justification and Discovery are Inseparable

101



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3.2.2 Justification is Not Aprioristic

102

3.2.3 Information about Generation is Necessary for Evaluation: Predictabilityand Novelty

104

3.2.4 The Context of Generation Has an Epistemic Dimension

106

Part II Discovery Naturalized

The Prepared Mind: Cultivating the Unintentional 113

Chapter 4: Philosophy of Science: From Justification to Explanation 117

4.1 Normative Philosophy of Science: Justification Relativized

118

4.1.1 Instrumental Rationality: Science as a Goal-Directed Activity

118

4.1.2 The Dilemma of the Normative Methodologist and Goodman's Solution:Rationality without Goals

119

4.1.3 From Justification to Explication

122

4.1.4 From Explication to Explanation: Paradigms of Rationality

123

4.2 From Description to Explanation

127

4.3 Explanatory Philosophy of Science

130

4.4 Normative Naturalism: Shallow vs. Deep Theories of Scientific Rationality

134

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4.4.1 Phenomenological Theories of Rationality

134

4.4.2 Explanatory Theories of Rationality: How the Is-Ought Fallacy isAvoided

138

4.4.3 Ideal Theories of Rationality and the Competence-PerformanceDistinction

139

4.4.4 The Therapist Model of Rationality and its Implications for InvoluntaryProcesses of Discovery

141

Chapter 5: An Evolutionary Theory of Discovery: In Search for the Unexpected 145

5.1 Evolutionary Epistemology: Taking Natural Selection Seriously

145

5.2 Blind Variation: The Principle of Serendipity

148

5.2.1 Are Scientific Discoveries Analogous to Blind Mutations?

148

5.2.2 The Evolutionary-Epistemic Significance of Serendipitous Discovery

153

5.3 Some Implications of the Principle of Serendipity

157

5.3.1 Predictability and Epistemic Profit

157

5.3.2 The Mathematical and the Social Media

160

5.4 Two Landmarks of Serendipity in Physics

160

5.4.1 Kepler: The Conscious Sleepwalker

160

163



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5.4.2 Planck: The Reluctant Revolutionist

5.5 Serendipitous Discovery of Natural Phenomena

165

5.6 Cultivating Serendipity

168

Chapter 6: Intrapsychic Processes of Creation 173

6.1 A Psychological Theory of the Creative Process

174

6.1.1 The Chance-Configuration Model

174

6.1.2 Phenomena Explained by the Theory and Evidence for Its Support

176

6.1.3 An Associative Mechanism of Generating Chance Permutations

178

6.2 Implications of the Theory

180

6.2.1 Explaining Serendipity

180

6.2.2 Individual vs. Collective Creativity

182

6.2.3 Cultivating the Creative Potential

184

6.2.4 Multiple Discovery

185

Chapter 7: A Socio-Evolutionary Theory of Science 189

7.1 Epistemic Cooperation and the Social Dimension of Discovery

189

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7.2 The Social Dimension of Blind Variation, Selection and Dissemination

197

7.3 Has Science Liberated Humankind from the Tyranny of the Genes?

199

7.3.1 Genetically Controlled Human Understanding

199

7.3.2 Transcending Our Natural Habitat

203

7.3.3 Two Patterns of Human Evolution:

(a) The Principle of Growth by Expansion

206

(b) The Coevolution of Human Action and Human Understanding

209

7.3.4 The Epistemological Significance of Cooperation in Science: TheEvolutionary Perspective

212

7.4 The Tension between Change and Stability

215

7.5 Implications for Discovery

218

7.5.1 The D-J Distinction Revisited

218

7.5.2 Cultivation: Preparing the Collective Mind

219

7.5.3 Strategies of Discovery

220

Chapter 8: Tinkering and Opportunism: The Logic of Creation 223

8.1 Evolutionary Tinkering in Science

223

8.2 Tool-Oriented Scientists: Intellectual Migration

227



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8.3 Tinkering in Particle Physics

229

8.3.1 Symmetries without Dynamics

230

8.3.2 The Resources of Quantum Field Theory

233

8.3.3 Playing with Quarks

235

8.3.4 Tool-Oriented Particle Physicists

235

Chapter 9: Completing the Picture: Is There a Role for The Genotype-PhenotypeProcess? 243

9.1 Non-Creative Discovery: The Genotype-Phenotype Logic of Growth

244

9.2 The Selection Cycle in Science

249

Conclusion 253

Epilogue: Implications for Science Education 255

Notes 259

Bibliography 261Index 271

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ACKNOWLEDGMENTS

The seeds of this book were sown when I taught philosophy of science in the Institute for History and Philosophyof Science at Tel Aviv University, which was my first philosophical home. I would like to thank Joseph Horovitzthe first coordinator of the Institute, for his moral support over the years.

Later I returned to Tel Aviv University as the guest of Yuval Ne'eman, and we had a very fruitful collaboration. would like to thank him for his agreement to include in the book material from our paper on serendipity and for providing partial support through the Wolfson Chair Extraordinary of Theoretical Physics.

At the preliminary stages of writing the book, during autumn 1989, I had a very stimulating break when I stayed the Center for Philosophy of Science at the University of Pittsburgh as a Visiting Fellow. I would like to thank Jerry Massey, the director of the Center, for inviting me to the Center and for his generous hospitality. Theintellectual and social environment in the Center provided an atmosphere conducive to the development of mywork. In particular, I enjoyed the discussions I had with Sam Richmond.

I am grateful to Paul Levinson, Kai Hahlweg and Cliff Hooker for inviting me to the conferences on evolutionaryepistemology they organized, which provided stimuli for my work.

I also thank Samuel Goldsmith and David Naor for their interest and Nomy Arpali for her assistance.

Finally, I am indebted to Donald Campbell for his encouragement and to the three anonymous readers of SUNYPress for providing some helpful suggestions.

Material from the following papers is included in this book:

1.Philosophy of science: from justification to explanation, published in the British Journal for the Philosophy of Science (1988).

2.Serendipity as a source of evolutionary progress in science, which I wrote with Yuval Ne'eman andwhich was published in Studies in History and Philosophy of Science (1989), reprinted with permission of Pergamon Press Ltd.

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3. Naturalistic philosophy of science: a socio-evolutionary view, published in Journal of Social and Biological Structures (1990).

4.A Theory of the creative process in science, published in Journal of Social and Evolutionary Systems(1992).

5.A genotype-phenotype model for the growth of theories and the selection cycle in science, publishedin Hahlweg and Hooker (eds.), Issues in evolutionary epistemology. SUNY Press (1989).

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Introduction

Unless you expect the unexpected you will never find truth, for it is hard to discover and hard to attain.Heraclitu s, Fragment 19 (Wheelwright 1966, 70 )

Discovery and the Philosophy of Science

Scientific discovery seems to be the most impressive and mysterious feature exhibited by modern natural scienceFrom the material or practical point of view, it enables humankind to control, reproduce and predict naturalphenomena, to create novel phenomena and technologies and to expand its living space. From the epistemologicapoint of view, it immensely increases humankind's capacity for knowing and understanding itself and the naturalworld. Yet, the philosophers of science, who attempt to understand science, have rediscovered this phenomenononly recently after many years of neglect. Logical empiricism, the dominant school of twentieth-centuryphilosophy of science, regarded the study of the process of discovery as an empirical inquiry to be dealt with byscientific disciplines such as psychology or sociology. The only respectable engagement of the philosopher of science was considered to be the logical analysis of the products of scientific discovery. However, formal logicproved not to be a very effective tool for understanding the phenomenon of science, and the discipline of philosophy of science became almost irrelevant for the understanding of the peculiarities and the significance of science.

Only in the last two decades, with the decline of logical empiricism and the emergence of new approaches to thestudy of science, has the study of scientific discovery regained its respectability. It is widely believed now thatthere is no universal logic of discovery. However, philosophers of science who deal with discovery moved fromone extreme to another: from the search for universal method to ''particularism." Some of them are now engagedwith particularities; they tell us about methods of discovery which they extract from specific domains andparticular contexts. This historicist-particularist movement mainly concentrates on case studies of discovery,without trying to rise above this level of study and develop a deeper, or more general, theory of science.







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According to this approach, science seems to be an ad hoc federation of loosely connected research areas. Thequestion arises as to what is the value of this occupation for understanding the phenomenon of scientific discover

Another trend in the study of discovery has developed in recent years. With the explosion in the field of computescience and artificial intelligence, a new movement has emerged"mechanized discovery." However, thistechnology-driven approach does not yield universal methods of discovery either. For the time being, some of theproponents of this enterprise, the cognitive scientists, have succeeded in mechanizing only marginal stages of discovering limited kinds of regularities. Moreover, they claim to have some success in concept formation. Otherwho are engaged in more practical directions, have made some contributions to areas such as medical diagnosticsand drug research. For example, we can find in a recent publication a description of such a product: "a drugdiscovery software system that enables medicinal chemists to design realistic new molecules interactively;construct, test, and refine hypotheses that explain and predict their bioactivity ..." (Science, 28 Feb. 1992, Producand Materials, 1153). This kind of tool may serve as a useful technological aid for conducting research in aspecific area, which may have implications for a heuristic-guided discovery in general.

In this book I have attempted to proceed in a different direction. Instead of looking for a universal logic of discovery, I treat discovery as a universal phenomenon. Instead of mechanizing discovery, I attempt to naturalizeit. I do this within the naturalistic approach which views the philosophy of science as a "science of science." This

approach will allow us to treat those facets of discovery which have escaped the dissecting tools of the logician.Yet, since the naturalistic tools have not yet been crystallized, I have tried to develop some of them in this book.This situation is symptomatic of the present state of the field. Indeed, the philosopher of science is very frequentlengaged in the meta-level problems, as well as in the object level problems; he is evaluating and reconstructing htools of investigation, while using them.

The main message of this book is that the creative process of discovery is not a purely rational enterprise in thetraditional sense which equates rationality with logical reasoning. Yet, although it is not governed by logical rulesit is a manifestation of universal phenomenon which may be treated as a natural phenomenon in its own right. Instudying discovery, I shall transcend the traditional boundaries of the philosophy of science and incorporate intothe theory of discovery ideas from evolutionary biology, psychology and sociology.

Mechanisms of Natural Selection in Scientific Creation

The theory of creative discovery which I propose belongs to the family of evolutionary models, appearing under the title "evolutionary epistemology" (EE)







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Discovery as Inference

One of the main themes which is explored in Part I is the distinction between two main notions of discovery:discovery by exposure and discovery by generation. Examples of exposure are discovery by observation or bydeductive inference; in the former we expose objects, such as a new star or particle, in the latter we expose the

information hidden in a set of statements, such as a prediction derived from a new theory. Examples of generational discovery are discoveries made by active experimentation and theory-construction. I argue that thedistinction between these two kinds of discovery processes is sharper and more useful than the traditionaldistinction between discovery and invention. The discovery-invention distinction makes sense only if we refer todiscovery by exposure. However, in science, the meaning of the word discovery has long transcended its originaletymological origin which refers to exposure. Newton's law of universal gravitation, quantum mechanics and thetheory of natural selection, for example, were not literally dis-covered or un-covered; they were generated. Idiscuss the implications of the exposure-generation distinction for the issue of realism.

The central questions discussed in Part I are: to what extent is scientific discovery regulated by reason or methodand what is the role of creativity in the various discovery processes? The various methods and rules are presentein the order of decreasing strength. The more creative is the process or the act of discovery, the weaker is themethod for generating it.

I describe different kinds of methods which stem from the inference-view of discovery and, in particular, theattempts to convert ampliative, or content-increasing, processes into deductive inference. This leads to the issue omaterial , or content-dependent, logic of discovery and to community-specific logics and domain-specific methodThis subject is directly related to the issue of expert systems in mechanized discovery. When generationaldiscovery, such as theory construction, is viewed as deductive inference, it becomes a discovery by exposure. Thuthe inference-view is intimately related to the view which treats all kinds of discovery processes as processes of exposure. Since inference is in principle method-governed, the search for a method of discovery stems from theexposure-view of discovery. Yet, no discovery process in empirical science is entirely guided by mechanicalalgorithm so that creative steps always play some role in the process.

Some attempts to represent generational processes of discovery as method-governed can be categorized as

"postmortem" procedures. Typical examples are Peirce's and Hanson's logic of retroduction, Musgrave's "inventivarguments" and Simon's discovery machine, which reconstruct the discovery process from the vantage point of owho benefits from the knowledge of the final result. They help us, therefore, only in justifying or reproducingsomething which has already been generated.







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Another postmortem procedure is the logic of pursuit which deals with the plausibility of a hypothesis and with thquestion of whether or not a hypothesis is worth pursuing. This logic of discovery is a method of initial evaluatioof the product of discovery, rather than a method of generating the product. However, evaluation is an integral paof the process of discovery, so that the logic of pursuit should not be dismissed as a partial method of discovery.

Finally, I treat discovery as a skill. Skill is a predominantly tacit faculty. Some basic field-specific presuppositionare internalized by the discoverer and serve as suppressed premises in the process of discovery. These premises cbe treated as "transparent" or "invisible" so that the process of discovery looks like an inference or an exposure.Thus, the following distinction can be made between generational discovery and discovery by exposure.Generational discovery creates new conceptual or experimental tools, which can be viewed as new communicatiochannels with nature. When these channels become transparent, new phenomena and new aspects of reality may bexposed through these channels. This kind of discovery by exposure can be viewed as inference, where thesuppressed premises used by the skilled discoverer are his communication channels with reality.

One of the contributions of traditional philosophy of science to the subject of discovery is the distinction betweenthe context of discovery and the context of justification. This is one of the controversial theses of logicalempiricism, which was one of the major reasons for ignoring discovery. It stems from the inference view of discovery. I discuss some main objections to the distinction thesis. In a naturalistic philosophy of science, the

distinction vanishes and the process of discovery regains its legitimacy as a proper subject.

When we view discovery as a skill, we encounter for the first time a process of discovery which is partiallyinvoluntary. This is predominantly a discovery by exposure. Yet major kinds of generational or creative processediscovery are involuntary processes: the incubation process, the eureka event and the cooperative-historical proceof discovery. What is common to these processes is that the discoverer is not in full command of the process.Traditionally, method-governed discovery has been contrasted with so-called chance discovery. The notion of "chance" or "accidental" discovery is employed whenever the process of discovery is unintentional. But this doesnot mean that there is no explanation for this kind of discovery. For instance, discovery may be a subconsciousprocess, or a cooperative process, which can be described and at least partially explained by psychological andsociological theories. In these cases, the discoverer does not generate the product of discovery. The discoverer canonly cultivate and expose it. Cultivation can be guided by recommen-







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dations for the discoverer, which are similar to the recommendations given to the farmer who grows plants or animals, or to the educator who "cultivates" children. From the viewpoint of the discoverer's contribution to thediscovery, the act of cultivation is weaker than the act of intentional generation. In the latter case the discoverer generates the product of discovery, whereas in the former the discoverer contributes to the process by generatingappropriate conditions for it and by nourishing it. Following the phrase "chance favors the prepared mind," coined

by Louis Pasteur, we may interpret cultivation as preparing the mind for unexpected discovery. Qua-cultivator, thdiscoverer acts here as a spectator at the act of creation.

The highest degree of creativity is exhibited in unintentional or involuntary processes, which are not governed bymethod. Although we may expect the highest degree of novelty to be created by processes of this kind, thephilosophy of science has been totally ignorant of them. In Part II, I will suggest how this deficiency may becorrected.

Discovery as an Evolutionary Phenomenon

The explanatory or naturalistic approach to the philosophy of science is most appropriate for treating theinvoluntary or unintentional processes of discovery. Part II is devoted to these phenomena. Instead of beingregulated by methodological rules, these processes of discovery may be governed by natural laws, or explained b

a theory of discovery. Thus, naturalism would provide us with an alternative to traditional logicism, on the onehand, and particularism or historicism, on the other.

I start with meta-philosophy-of-science. In order to comprehend the significance of the evolutionary approach toscience in a wider perspective, I develop my version of the naturalistic or explanatory approach to the philosophyof science. I present a general view on the nature of the philosophy of science. In this framework I classifydifferent approaches to the philosophy of science, such as logicism, historicism, sociologism, cognitivism or evolutionism. I call these various approaches paradigms of rationality. The main difference between this schemeand most contemporary historicist and naturalistic treatments of science is that the latter characterize a theory of science as (merely) descriptive, whereas I emphasize its explanatory role. I introduce here a scheme whichprovides what I would call a "deep" naturalistic theory of scientific rationality. This contrasts what I would term"shallow" theories, which draw their rules of rationality from the practice of science without trying to find a deep

explanation for them. The latter category includes historicist theories. (The word "shallow" is not used here in itsnegative connotation; in the same sense, phenomenological laws or models in physics are shallower than thetheories which explain them). For example, I not merely pursue the







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claim that scientific creativity is dominated by tinkering, I furthermore attempt to provide a deep explanatorytheory of science which will explain this phenomenon. In fact, it was the theory which came first and thephenomenon of tinkering was then predicted by the theory.

The heart of Part II is the evolutionary theory of science which I propose. In general, it might be categorized as aversion of EE, which models the development of science on natural selection. The theory views science as acontinuation of biological and cultural evolution. In applying this theory to scientific discovery, I present the viewexpounded in my paper with Ne'eman which has far-reaching implications for the nature of scientific discovery. presents our interpretation for the notion of "blind" variation in science, modeled on the notion of quasi-randommutation in evolutionary biology. According to our view, one of the most important kinds of creative discoverymade in science are serendipitous discoveries, which are made when scientists unintentionally solve a problem (oexplain a phenomenon), while intending to solve a different problem (or to explain a different phenomenon). Weclaim that the phenomenon of serendipity is essential to scientific progress, especially to revolutionary progress.Serendipitous discovery is a typical unintentional process. The discoverer can only cultivate the process, beprepared for its unexpected outcome and expose it. Serendipitous discovery, like a biological mutation, can beexplained as an "error" which infiltrated a routine procedurea research program.

Serendipitous discovery is generated by psychological and social processes. I introduce Simonton's psychological

theory of creative discovery which accounts for some major kinds of serendipitous discovery. The theory is basedon the natural-selection model and describes processes which take place in the individual's mind. This theoryattributes an element of chance even to the seemingly most intentional processes of discovery, such as Einstein'sdiscovery of special relativity, which would otherwise undermine the blind-variation view of discovery. It explainan important kind of serendipity-generating mechanism which is related to the creative process of incubation.Thus, according to this theory, the most "intentional" processes are partially involuntary.

Then, I complement the evolutionary theory of science by the social dimension. I claim that the social dimension essential to both the phenomenon of serendipity, i.e. to "blind" variation, and to the process of selection.Furthermore, the social dimension enables science to transcend our evolutionary heritage and to expand our knowledge into new domains, such as the domains of cosmic and microcosmic phenomena. This approachcombines elements of social epistemology and evolutionary epistemology. In the framework of this approach, I

propose two evolutionary patterns, or models, for the growth of scientific knowledge. One pattern may be labeledthe principle of growth by expansion, which is exhibited in biological evolution when a species







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solves problems arising in its original niche by expanding into a new living space. This model accounts for themanner in which science solves problems by active experimentation and theory-construction, thus expanding intonew domains of reality. The second pattern is the coevolution of sensorimotor organs and the brain which isreflected in science by the coevolution of observational-experimental techniques and the theoretical apparatus.

As has been noted above, the notion of tinkering encapsulates the evolutionary facets of scientific creativity. Inapplying this theme to science as an evolutionary phenomenon, new light is shed on some chapters from thehistory of science. I offer examples which illustrate this aspect of discovery. To make the case stronger, I bringsome evidence from what is considered to be one of the most advanced natural sciences: theoretical physics. Themain piece of evidence will be drawn from the history of particle physics which demonstrates the role of tinkeringin generating novelty. In other words, I try to interpret episodes from the history of particle physics as the work oa tinkerer.

Yet, creative discoveries do not fall from the sky. Radical innovation comes from within science; the source of scientific novelty lies in routine research. Moreover, the process of consolidating the ideas generated in the creatiprocess is by itself predominantly non-creative. The evolutionary model, therefore, cannot be complete withoutleaving room for routine research programs which are characterized by inference and reason. In the last chapter, conjecture that the genotype-phenotype structure underlying ontogeny will do the job.

The highly abstract approaches to discovery which are expounded in this book yield down-to-earth consequencesThe notion of the scientist as a tinkerer is one of them. They also have practical implications for society in twoareas. The principles of serendipity and tinkering have important implications for science policy and scienceeducation; the former are indicated in Chapters 5 and 8 whereas the latter are outlined in the epilogue.







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PART IIN SEARCH FOR LOGIC OF DISCOVERY







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Chapter 1Exposing And Generating

Nature loves to hide. The hidden harmony is better than the obvious.Heraclitus , Fragments 17 and 116 (ibid., 70, 79 )

1.1 What is a Discovery?

I would like to start by trying to clarify or explicate the intuitive notion of discovery as it is used in everyday lifeand in science. This may provide us with clues for understanding the epistemological and pragmatic significance discovery in general and of scientific discovery in particular. We may find differences among the usages of theterm in everyday discourse and in science, as it happens also with scientific terms which are borrowed fromordinary language. This time, however, we are dealing with a concept which belongs to the metalanguage of science rather than to science proper. 2

The focus of this book is on the process or the act of discovery. However, we cannot deal with the process of

discovery without also considering the object or product of discovery. For example, we will be engaged with theissue of the ontological status of certain scientific discoveries; e.g., whether a certain (product of) discovery is areal entity which exists independently of the inquiring mind or whether it is our own creation.

Discovery is a "success" word. When we say we have discovered something, it means, for example, that theproduct of discovery is useful, that it solves a problem, explains some phenomena or that it is the lost object wehave been looking for. When one tells us he saw a flying saucer, we would not say that he had discovered a flyinsaucer unless it was proved that what he







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saw was indeed an extraterrestrial vehicle. We would not say that the magnetic monopole was discovered, since iexistence has not been confirmed by experiment. Phlogiston was regarded as a discovery by Stahl and hiscontemporaries. But since Lavoasier's revolution in chemistry, the history of science treated it as a false theory.The same can be said about the status of the aether after Einstein's revolution in physics.

A contemporary scientist who does not believe in the existence of the aether or phlogiston, would not say that theaether was discovered. But a historian of science who is aware of the fact that theories may be overthrown, that aoverthrown theory may be revived in the future and that contemporary theories are not the final truths, wouldrelativize the notion of discovery to a historical period and to some community.

We would be interested in the process of discovering a theory. This encompasses the stage of evaluation andconfirmation in which the scientist finds out that the theory is successful in providing predictions, explanation,understanding or unification of phenomena. I do not use the term confirmation in a logical sense of proof. Notheory can be proved in this sense. A confirmed theory may be overthrown or refuted (and refutation in this sensis not a logical notion either). Moreover, most scientific theories have been refuted. Both the theory of the aetherand Kepler's laws were refuted. So why the latter are considered to be a great discovery and theory of thephlogiston is not? I will turn to this question below.

Epistemological Aspects of Discovery

From the epistemological point of view, discovery is a major vehicle for the growth of knowledge. And yet, our knowledge grows also by other means. As individuals, perhaps the main way we learn new things or acquire newinformation is by instruction or by reading. Even, and in particular, scientists learn most of what they get to knowfrom other scientists or from the scientific literature. Personally, a scientist may make very few scientificdiscoveries, if any, during his lifetime; most scientific discoveries are products of collective efforts. Therefore, it sometimes difficult to judge who participated in, or contributed to, the discovery; sometimes it is perhaps a wholecommunity which should be credited. If the process extends over a long period of time, only the final step in theprocess is regarded as a discovery. Yet the contributions of the other participants are sometimes no less importantthan the contribution which constituted the breakthrough. The example of the electroweak unification in particlephysics, which is discussed in Chapter 8, illustrates this point. The graduate student 't Hooft, who made the

breakthrough which led to the theory, entered the field at a stage where almost everything was ready for thediscovery, and he solved the crucial problem which was presented to him by his supervisor, Veltman. So, shouldwe regard him as the discoverer of the theory, or only as the discoverer of the solution of the specific problemwhich his supervisor asked him







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to solve? This issue will be elaborated when the social dimension of discovery will be discussed.

On the other hand, an individual may discover something which would not count as a scientific discovery since itdoes not constitute a novelty with respect to the body of knowledge or to the system of beliefs shared by thescientific community. For example, someone might ''discover" today that the earth rotates around the sun. Weshould refer, therefore, to the total, or collective, knowledge of a culture or a community, such as the scientificcommunity. This would lead us to the following characterization of the act of scientific discovery: the acquisitionof an item of knowledge which constitutes an increment in the body of knowledge of the scientific community.

One may discover the neutrino, a black swan, the theory of general relativity, that phlogiston theory is false, thatleaves change their color, or that Mary has eaten her breakfast. The last example, however, does not seem to be ascientifc discoverynot even an ordinary discovery. In order to exclude cases such as this, we might require that thprocess of discovery will result in a new knowledge item, in the above sense, which is either (a) unexpected, (b)has a special interest or (c) constitutes an increment of general knowledge or a change in our general beliefs, asopposed to beliefs in particular matters. Thus, seeing a black swan may be unexpected since it may contradict ageneral entrenched belief (that all swans are white). A discovery may contradict an implicit generalization of whiwe become aware as a result of the discovery. Hence, discoveries may lead to "negative" as well as to "positive"increments of knowledge; we may acquire a new generalization, or learn that some of our general beliefs are false

All the above cases exemplify discoveries made with respect to a given body of general beliefs; a discovery is aprocess or an act which adds something to our system of general beliefs, changes it or solves a problem whicharises in it.

In the above discussion, a sharp distinction was not made between knowledge and belief. A traditionalepistemological characterization of knowledge, which can be traced back to Aristotle, is expressed by the familiaslogan: "knowledge is justified true belief." There has been a long debate centering on this definition in twentiethcentury epistemology. Although it is out of the scope of this book to dwell in depth on this issue, we must takesides in the debate since discovery is a salient epistemological notion.

We do not have to accept the Popperian conception of knowledge in order to reject the above definition. Popper, defiance of the above definition, denies that our beliefs can be justified, hence all our knowledge is conjectural.

However, even if we admit some sort of justification or confirmation, we still cannot retain the qualification "truein the above definition without excluding practically most of science from the realm of knowledge. If we do notwant to exclude, for example, Newtonian physics from the corpus of eighteenth- or ninteenth-century scientificknowledge, or quantum physics







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from the corpus of twentieth-century scientific knowledgein fact, if we want to retain the notion of scientificknowledgewe cannot accept the traditional definition. Scientific theories can be confirmed but cannot be "proved"beyond any doubt to be true. Newtonian theory, which was perhaps the most established scientific theory in alltimes, confirmed by so many observations and experiments, turned out to be strictly false. Thus, according to thetraditional definition, it would not qualify as knowledge. We would not be able to say that Newtonian mechanics

was part of eighteenth-century scientific knowledge, for example. And there is no reason why the fate of twentietcentury physics would be better. In science, we accept not-yet falsified conjectures as knowledge, provided theyare well confirmed, in some non-logical sense of the word. Well-confirmed theories or laws may be regarded as"partially true" or may be treated as good approximations to the truth. Scientific knowledge consists mostly of partial truths and good approximations to the truth. Indeed, we may find out that something we have believed inand which has been treated as legitimate knowledge is false, or true only in a restricted domain.

No one would deny that Kepler's discovery of the laws of planetary motion was a real discovery, although the lawturned out to be strictly false. The reason for this is that in hindsight Kepler's laws are considered to be"approximately true." This means that the discovery of the laws constituted an indispensable step in a progressiveresearch program (to use Lakatos' terminology, to which I will turn in section 1.3) which led to the highlyconfirmed Newton's theory from which a revised version of the laws was derived. The revised laws are considereto be a better approximation to the truth. On the other hand, the "discovery" of the aether is not treated byhistorians of science as a real discovery, since it did not yield a progressive research program. Both Kepler's lawsand the theory of the aether were strictly false, hence, it is not the notion of truth which distinguishes betweenthem. Rather, it is a notion such as fruitfulness, or progressiveness, which may account for the distinction. Thus,only in hindsight can we say that the discovery of Kepler's law was a real discovery. Hence, paradoxically, thenotion of (absolute) truth does not prove to be helpful in characterizing knowledge. A discovery of a "false'' law theory might turn out to be an important step in the growth of scientific knowledge. Knowledge is construed hereas a dynamic entity rather than as a static entity which is either true or false. The dynamic character of scientificknowledge and scientific discovery will be discussed in section 1.3.

According to Popper's falsificationism (Popper 1959), theories do have truth values, and the only possibletheoretical discovery is the discovery that a theory we have (irrationally) believed to be true is false. Thus, we masay that according to Popper, scientific discovery is not a "success notion," but a "failure notion"contrary to our

intuition. Perhaps the only "positive" discovery possible, according to this view, is a discovery of a method of testing a theory.







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non which requires an explanation. He initiated the process of discovery which eventually led to the understandinof the phenomenon. Lenard, on the other hand, misinterpreted the phenomenon. Hence, he was not considered tobe the discoverer.

Ontological Aspects of Discovery

Besides having strong epistemological implications, the notion of discovery has important ontological aspects.Indeed, epistemology cannot be divorced from ontology. Some dictionary definitions of discovery may shed lighton the ontological status attributed to the object or product of discovery. We will find in the dictionary under theitem "discover" formulations such as: "to disclose a secret," "to expose (bring to light) something hidden" or "touncover." Implicit in these connotations is that something which is hidden from us is discovered; its existence isindependent of the process of discovery. This view is reflected in the expression: ''science reveals the secrets of nature." This issue will be discussed in section 1.4.

1.2 The Products of Scientific Discovery

1.2.1 What Do Scientists Discover When They Look At the World?

When ordinary mortals look at the world, they discover entities which exist in the world such at ordinary objectsproperties, events, phenomena, causes and regularities. When the scientist investigates the world, the mostimportant kinds of items he discovers are not entities in the world, but new concepts, ideas and scientific theorieswhich belong to the realm of his cognitive representation of the world. Epistemologically, the discovery of fruitfuconcepts and theories is more important than the discovery of entities existing in the material world, since theorieenable science to make further discoveries of natural objects, events and phenomena. Thus, on the one hand,physicists discover new kinds of particles, such as, the electron or the neutrino, and on the other hand, conceptsand ideas, such as the concept of spin or the idea of the field, or theories, such as quantum mechanics, which guithe physicists in discovering new particles and their properties.

Scientific theory is one of the distinguishing characteristics of modern science. In understanding its nature, we wiincrease our understanding of modern science. Therefore, my main concern in this section will be to elaborate on

the nature of scientific theories as objects or products of scientific discovery and in particular, to distinguish themfrom laws of nature. Accordingly, as we will find out in the following chapters, the process of discovering or generating a theory is substantially different from other kinds of processes of discovery in science, inparticularfrom discovering empirical generalizations and regularities. In fact, the notion of discovery itself, whichwas inher-







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ited by science from ordinary experience, may not be suitable for describing the way scientists arrive at a theory ohow they generate it.

Before we turn to theories, let us deal with less structured products of discovery: objects and events.

1.2.2 Objects and Events Contaminated by the Scientist's Intervention

The distinction between observational and theoretical terms or statements has a long history in twentieth-centuryphilosophy of science. It is now widely agreed that all descriptive statements are "theory-laden" so that there are purely observational statements. However, when we turn to discoveries, we may employ the followingmethodological definition: every object of discovery which can be discovered by observation, i.e. by the senses oby using observational instruments and methods, will be qualified as "observational" discovery. It is a matter of methodological decision or convention to determine what are the observational instruments.

In making an observational discovery, we have to rely on our system of categories or conceptual system throughwhich we grasp the phenomena we observe. In the process of observation by the senses, i.e. in so-called directobservation, we process the raw data of observation using the conceptual and cognitive apparatus with which weare equipped. Our cognitive apparatus guides us in dividing our visual field into enduring objects and natural kind

We also rely on some tacit assumptions and on inferences we make spontaneously and unawares. For example,when we observe an object, we assume that what we observe is more or less what is there; that the light comingfrom the object is not radically distorted or that no one painted it or sculptured it in order to deceive us. All thesebackground presuppositions and beliefs would not make the observed object conjectural if we make themethodological decision to treat our cognitive apparatus as reliable and our innate or spontaneous presuppositionunquestionable. We would make this decision in order to retain the commonsensical notion of observation which general does not deceive us in everyday experience. In fact, in ordinary experience we do not make anymethodological decision such as this. Normally, we are not aware of our cognitive apparatus. Or, rather, we are nfocally aware of it, to use Polanyi's expression (1958, 55-6). We may express it by saying that in the process of observation our cognitive apparatus is "invisible" or " transparent ." 3

In "indirect" observation, which involves the usage of instruments, we rely not only on our innate (genetically andculturally determined) sensory and cognitive machinery; we also rely on established theories which govern theoperation of the observational instruments and methods. In science, we rely also on established theories whichsupply us with the categories and concepts by which we describe the phenomena exposed by using theobservational instruments. These theories are (provisionally) considered unquestion-







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able. For example, when the particle physicist observes the products of collision experiments, he describes thephenomena using concepts, such as particle charge or spin, electrons and protons, which he treats as belonging tohis observational vocabulary. Again, we may say that after the scientist acquired the skill of using his observationor experimental apparatus, he treats it as transparent. Or when a scientist relies on a set of theoreticalpresuppositions which he regards as unquestionable, we may say that these presuppostions are transparent.

Thus, the way we describe our object of observational discovery, depends on our cognitive apparatus, conceptualsystem and background knowledge. All this machinery determines what we observe. However, it does not uniquedetermine what are the objects of discovery exposed by the act of observation. Indeed, we may observe a lot of things, none of which will be considered to be a discovery. And different observers may be making differentdiscoveries by watching the same thing. Let us take the simplest kind of observational discovery. When wediscover a black swan, the object of discovery seems to be an individual or an object in the world. Withoutentering now into questions related to the realism-antirealism debate, let us assume that there is an objective stateof affairs which we encounter in our discovery. However, what we discover is not this objective state of affairs;our object of discovery is not identical with the state of affairs we encounter. It rather depends on our presentbeliefs, expectations and interests. If, for example, we have been believing that there are no black swans, we woube interested in the very existence of black swans. The product of discovery may then be the statement: "thereexists a black swan." If we are interested in the fact that the black swan was discovered in a certain place and/or aa given time, we may be interested in the event observed, which is referred to by the statement: "there is a black swan at time t in place x." If so, then what is the object of discovery? Is it the particular swan observed swimminin an Australian lake? Is it the fact that it was black? Is it the fact that it was swimming? Is it the fact that it wasswimming in a certain direction, at a certain speed, at a particular hour in the day, in particular weather conditionat a particular distance from the shore, etc? Thus, given the same state of affairs, many discoveries may be madefact, an infinite number of different discoveries. The object of discovery depends on both the state of affairs in thworld and on the discovereron the discoverer's expectations, point of view and interests.

It seems, therefore, that even if there is an objective state of affairs which is partially described by our conceptualsystem, the object of discovery is not a totally objective matter. Rather it is a certain aspect of reality, a certainfacet of the state of affairs encountered. Thus, the object of discovery has both epistemological and ontologicalaspects; what we discover depends in part on what is there and in part, on our interests and on what we know or

believe. Thus, when someone who does not have any prior beliefs about swans, or believes







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that there are black swans, observes a black swan, the observation of a black swan does not constitute a discoveryfor-him. On the other hand, when someone who believes that all swans are white observes a black swan, the blackswan constitutes a discovery-for-him which results in a refutation of one of his general beliefs. A discovery hasthe effect of adding something to the discoverer's system of beliefs or modifying it. Hence, even the simplest objeof observational discovery is not something which exists out there in the external world independently of our stat

of knowledge, awaiting our discovery. When X discovers D, D is not determined only by the state of affairs in thworld, but also on the cognitive state of X.

Yet, not everything which is observed and which is unexpected or interesting constitutes a scientific discovery;confirmation is part of the discovery process. If we refer to ordinary observational objects or events, there is anentrenched procedure of confirmation: the act of confirmation is carried out by repeating the observation. It seemtherefore, that a non-repeatable event cannot be an object of observational discovery. Indeed, "discoveries" such the purported discovery of gravitational waves in the early seventies, are discarded by the scientific communitysince no one could repeat them (Collins 1975). Yet, a singular or unique event which is not repeatable cannevertheless be confirmed if it was independently observed by several qualified observers or if similar events werobserved in the past. For example, astronomical events, such as a supernova are legitimate objects of observationdiscovery in science.

Thus, the following three factors contribute to the product of observational discovery: (1) A conceptual system orsystem of categories constitutes a precondition for making an observation. (2) A background knowledge and priorpoint of view (an expectation, a belief, a theory) determine what observational finding would be regarded as adiscovery. (3) The act of confirmation determines whether the object is indeed a discovery. All three factors"contaminate" the object of discovery with our cognitive intervention. This is obvious for the first two factors. Aswe will see in the following chapters, the act of confirmation, too, is not an objective matter; it is not devoid of psychological and social components. Thus, even the most "naive" objects of scientific discovery, observationaldiscoveries, are not objective entities in the world.

In science, the effect of factor (2), which determines which observational findings will be regarded as discoveriesis exhibited in the following way. The objects of observational discovery are objects and events, such as a newparticle, species, chemical element and compound, star, galaxy, particle decay, chemical reaction or supernova. A

object or an event are considered to be a discovery if it is unique of its kind or if only few of its kind have beendiscovered. A supernova belongs to the last category. What about a discovery of a new particle? The discoveriesthe neutron, the p-meson and the neutrino were regarded by elementary particle physicists as genuine discoveries







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since the number of so-called elementary particles was relatively small at the time of these discoveries. However,since the 1960s, when the number of particles increased, an observation of a new particle or resonance was notconsidered a discovery in its own sake. An observation of a new particle or state of matter was treated as adiscovery if it confirmed or refuted a regularity or a theory. Thus, the discovery of the omega-minus particle in1964 was an important discovery since it strongly confirmed the SU(3) symmetry of strongly interacting particles

(hadrons). Thus, in a science which is in its theoretical phase, an observational discovery may be theory-laden inone more respect than an observational finding; an observational finding is a genuine discovery only if it leads tothe confirmation of a not-yet established theory or law or to the refutation of an established theory or law.

In astronomy, the standard is different. A new star is considered to be a discovery, although many stars have beeobserved. Perhaps the reason for this is the same reason for considering a new biological species as a discovery.Every new species is unique; there is no law of nature or regularity which will enable us to predict the existence oa new species. The same thing can be said of stars; there is not a theory or a law of nature which can predict theexistence of stars, as symmetry theories in particle physics or as the Periodic Table of elements predicts theexistence of particles or elements, respectively. Discoveries of unique objects related to the history of humankindor life in general or to the history of our planet, have a special interest for their own sake. This is understandablesince these sciences are not theory-dominated. Yet, even in theory-dominated sciences, there may be importantdiscoveries of specific events or objects. Perhaps the most important scientific discovery ever, would be adiscovery of a singular event: how our physical universe was formed (e.g. the "big-bang" event) or how life begaMoreover, the event or process by which life began would become even more thrilling had we shown that such anevent is unique or that its probability is vanishingly small; no sane scientist would reject a research project whichhas high chances for leading to the discovery of this event even if it would be known in advance that it will notcontribute a bit to our general knowledge. However, these kinds of singular events are non-observable and their discovery is heavily loaded with theoretical inference.

1.2.3 The Plasticity of Theories

We have seen that observational discoveries are contaminated by our cognitive intervention. However, when wecome to scientific theories, the contribution of the discoverer's cognition to the object or product of discoverybecomes much more significant. Theories are created by us, although not entirely by our free imagination; the

process of creation is constrained by the empirical data and by the conceptual resources available to the scientist.Here







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the scientist and the artist are in the same boat. The sculptor, as well as the physicist, is restricted by his medium ocreation.

The term scientific theory is employed in a variety of ways in the literature. Obviously, there is no a priori "right"definition of the term. I will propose a way to characterise this notion by distinguishing it from the notion of natural law, having in mind contemporary usages by scientists and by philosophers of science.

Laws of nature are specific kinds of regularities. The discovery of a regularity or an empirical generalization doesnot involve an introduction of new concepts which do not appear in the observational vocabulary. We makegeneralizations when we identify natural kinds which exhibit regular behavior or characteristics. The identificationof natural kinds is a matter of both our experience and our natural endowment. Our cognitive apparatus guides usin the general pattern of concept formation and our experience in the specific field of investigation guides us inidentifying the natural kinds in that field. Thus, regularities and empirical generalizations are contaminated by oucognitive intervention in the same manner as observational discoveries of singular events and objects are. And sothe above mentioned three intervening factors involved in observational discovery are also operative in this kind odiscovery. The only difference is that the act of confirmation is different. It relies on inductive "inference."Induction cannot be justified by logical or "objective" standards, so we may treat it as another natural endowmentwhich is part of our cognitive apparatus. Thus, the object or product of discovery is further contaminated by our

belief in induction and in the uniformity of nature. If we still believe that we discover here an entity in the worldwe may say that the object or product of our discovery is an invariable relation between properties in the world, example, between the property of ravenhood and the property of blackhood. If we are realists we may regardrelations as entities existing in the world, although in a more abstract sense than objects and events are.

Now, there is a difference between an empirical generalization, such as "all ravens are black," which seems to be"accidental," and a law of nature, such as the law of universal gravitation, which seems to be "universal." Bothempirical generalizations and laws of nature embody invariable relations in the world. So what is the differencebetween them? Philosophers have tried to answer this longstanding question by looking at the logical form of lawstatements, employing the machinery of "possible worlds." However, they have not yet found a satisfactory answin this direction. This is one of the examples where philosophers unsuccessfully try to find answers to questionsconcerning science in a logicist direction. Perhaps the answer lies in the realm of the dynamics of scientific

knowledge; perhaps it lies in the manner by which science progresses, rather than in the logical form of the law-statements.

When an empirical generalization is embedded in, or derived from, a strongly confirmed theory which holds overwide range of phenomena, then







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we might treat it as a law of nature. Indeed, in such a case, we can explain why the generalization is not accidentif the theory's postulates are true, then the generalization must be true. A unifying theory is confirmed by its widerange of successful predictions and explanations. So the theory gives the generalization a stronger confirmation;through the theory the truth of the empirical generalization is linked with the truth of other kinds of establishedphenomena. Sometimes an empirical generalization is so entrenched that it is treated as a law of nature even

without being embedded in a theory. But then it is assumed that, eventually, a unifying theory will be found inwhich the generalization will be embedded.

A physical law, such as the law of universal gravitation, is an invariable relation between physical magnitudes,such as masses, distances and forces, which can be thought of as properties. There are other kinds of laws, whichcannot be described as relations. For example, a conservation law, which states the constancy of a givenmagnitude, such as energy, or the second law of thermodynamics, amount to a restriction on possible processes, oto a limitation on the value of a given magnitude or property.

When we say, as it is customary to say, that a law "states" something, we do not mean that the law is a statementmade by us. It plays an analogous role to a judicial law in preventing certain states of affairs to occur, or inspecifying how properties or objects "should" behave. We represent the law by statements expressed, for exampleby mathematical formulae. However, these formulae or statements refer to the law which is part of reality. A law

of nature is not a proposition or a statement. The formula F=kq1q2/r2 is not Coulomb's law, as is frequently state(presumably as a shorthand) in textbooks. Rather, it is a law-statement which refers to Coulomb's law; the law isrelation between the physical magnitudes (properties) of the electric force between two interacting particles, theircharges and the distance between them. In summary, a law of nature may be an invariable relation or a restrictionon possible states of affairs or processes.

It is not within the scope of this book to deal with the ontological status of laws of naturewhether and in whatsense they exist. However, in order to understand in what sense they differ from theories as objects of discovery,will adopt the following mildly realistic view. I start from the assumption that objects, properties and events existin the world. According to this view, laws of nature are invariable relations between properties or restriction on thexistence of certain events or objects. That is, they do not exist in their own right in the sense objects and eventsexist in space and time (or in spacetime), but they correlate properties or dictate what objects or events cannot

exist.

Thus, laws of nature are somehow related to entities which exist in the world, in the same fashion as properties aWe may view them as properties of higher order, or as restrictions on what can exist or happen in the world. If whave only two possibilities where to accommodate them, in our cognition







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or in the external world, then as realists we will choose the second possibility. This is still an intuitive view whicis not fully analyzed. However, for the sake of distinguishing between laws and theories, I will not need more thathis.

Theories are the most important targets of scientific discovery, at least in the physical sciences. What sort of entities are they? What sort of entity is Newtonian mechanics, the Darwinian theory of evolution or Maxwell'stheory of electromagnetism? In order to answer this question, we have to find out what are the functions of theories in modern science. Among the functions attributed to a theory we can find the explanation and predictioof natural phenomena and laws of nature and the unification and systematization of our knowledge. Newtoniantheory explains why planets are encircling the sun according to (a modified version of) Kepler's laws. It alsoprovides a unification of diverse phenomena such as celestial and earthly motion. It seems, therefore, that theoriefulfill epistemic functions. They stay closer to our cognition than to the objects and events which exist in theworld. We would not say that Newton's or Darwin's theories exist in the world; rather they describe and explainwhat exists. Thus, if we do not wish to employ Popper's three-worlds machinery for accomodating theories and whave only the two above mentioned possibilities to categorize them, we would say that they are elements of knowledge rather than elements of reality; they are cognitive objects which represent reality.

When we discover a theory, we discover something which is related to external reality; for example, something

which represents reality in our minds or something which helps us in comprehending reality. So what kind of entity is it? Is it just a description, a statement, or an explanatory instrument? Traditionally, philosophers of science viewed theory as a set of statements, orsimplyas a statement (which is the conjunction of all the theory'sstatements). This might distinguish between a law of nature and a theory, since a law of nature is not a statementHowever, if we believe that a law of nature exists in the world, we would say that a law-statement refers to a lawWe might, therefore, ask what the theory-statement refers to?

Some theories may be viewed as a system of interrelated law-statements. For example, Maxwell's theory of electromagnetism consists of Maxwell's equations which yield formulas and equations expressing laws of nature,the laws of electricity, magnetism and electromagnetism. Yet, the system of laws consists of something more thana mere collection of laws. Within the theory the laws are interrelated via Maxwell's equations. The theory thusserves as a unifying entity. This might be expressed by saying that the theory refers to relations of a second order

relations between laws which are themselves relations between physical magnitudes. If we admit relations to ourontology, there is no reason for rejecting relations of any specified order. Thus, in discovering a theory, wediscover a set of relations between observable properties and measurable magnitudes.







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Yet, it is doubtful that even Maxwell's theory just refers to nothing more than to a set of interconnected laws of nature. If we are not instrumentalists or anti-realists we would say that there are ontological claims made by thetheory about the existence of some kind of entities, such as electromagnetic waves. And if one would argue that athese claims about waves can be reduced to relations, without committing oneself to the existence of anything elswe might take as another example the kinetic theory of gases, which deals with more tangible objects. This theory

does not exclusively consists of a system of equations. It has clear ontological claims: the existence of molecules motion etc. The theory's equations are derived from a model of molecules in motion. If we do not yield to thealready bankrupt positivistic views of reducing everything in theory to the measurable and the observable,dismissing any ontological commitment, then we would say that the theory states the existence of particles andtheir properties and behavior.

This difference between law and theory is substantial. A law-statement does not state explicitly anything about thexistence of any entities in the world. It just describes relations between entities which scientists have accepted aexisting before the law was discovered. A theory, on the other hand, in many cases states the existence of newentities, such as electromagnetic waves, subatomic particles and forces, i.e. new with respect to our state of knowledge before the theory was discovered. More generally, the theory is constructed from new ideas, concepts,models and analogies. These may be qualified as proto-theoretical entities, which are also objects of discovery. Iother words, the novelty of a theory is in the new proto-theoretical entities from which it is constructed, includingthe new entities it claims to exist. Thus, here the distinction between a law-statement and a theory-statement is nrelated to their form or their content but to their genesis.

In fact, the introduction of new entities, concepts, ideas, etc. is a necessary condition for the theory to beexplanatory. Newtonian mechanics, for example, introduced the concept of mass. Indeed, one of the commonprinciples of explanation is that explanation cannot be circular. Thus, a phenomenon is not explained by employinthe same predicates used for describing the phenomenon. For example, "the sky is blue" would not be explained b"the sky consists of blue particles." This might apply to the explanation of laws of nature as well: Coulomb's lawwould not be explained, on pain of circularity, by the "theory": "all charged particles obey Coulomb law." Or,Boyle's law for an ideal gas in a container cannot be explained by the statement that every volume element of thegas in the container satisfies Boyle's law. Thus, the explanans should include something newe.g., new kinds of objects, new properties, relations or structureswhich do not appear in the explanandum. This principle is not

mandatory in scientific explanation, since we encounter in science "bootstraps'' kinds of explanation. However, ifwe restrict ourselves to atomistic explanations or to explanations by reduction, which constitute







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the majority of scientific explanations and perhaps the ideal model of scientific explanation, the principle musthold.

When I say that a theory introduces "new" concepts or entities, I mean new relative to our state of knowledgebefore the discovery of the theory was made. Hence, if we view the theory as a final product, independently of thepistemic circumstances in which it was discovered, no sense can be given to the "newness" of the entities referreto by the theory or of the concepts employed by it. The theory-statement in this case just employs a set of concepwithout making explicitly any ontological claim. In this respect a theory does not differ from the statementreferring to a law of nature.

Thus, a substantial difference between the two would arise only if we view a theory from a historical or epistemicpoint of view. Only in a historical context can the theory be viewed as making explicit ontological claims. Butthen, a theory will be part of a historical process, transcending a mere statement. In saying that one of thedistinctive features of a theory is the new entities it predicts, relative to the previous state of knowledge, weattribute to the theory an epistemic role of advancing knowledge. Therefore, we cannot view the theory in isolatiofrom the historical process in which it emerged. Furthermore, in section 1.3, I will propose viewing the theory itseas a dynamic entity which brings about further discoveries after it was brought to life. According to this view, indiscovering a theory, it is not just a static description, or a statement, which is discovered. Rather, it is a basic ide

model or picture which guides a research program.

We would expect, therefore, that the process of discovering a theory will differ from the process of discovering aregularity, for example. In discovering a theory, we discover a guiding tool for advancing knowledge. This meansthat the object of discovery in this case is neither something in the world nor a mere statement. A model or apicture cannot be fully described by a statement. It is not an entity which refers to something in the world. Ratheit is a cognitive or epistemic object which helps us in representing the world or in grasping it in a dynamicfashion.

This view of theories can by no means be categorized as instrumentalism. If we were instrumentalists, viewingtheories as instruments for organizing and predicting observational data, then the object of discovery would be aset of directions for deriving predictions, a superstructure for organizing the data, etc. The main difference betwee

the view expounded above and the instrumentalist view is that according to the above view the theory as acognitive tool is mirroring reality, whereas the instrumentalist view does not make such a claim.

From this point of view, the transition from the pretheoretical stage, when a science deals only with empiricalgeneralizations, regularities and laws of nature, to the theoretical stage, is a radical transition. It does not involve change in degree, such as the change embodied in the transition from a less







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general theory to a more general and abstract theory, as exemplified by the transition from the kinetic theory of ideal gases to the molecular theory of matter. It rather involves a category-change. Discovering a regularity or alaw of nature and discovering a theory are entirely different things . In one case, we discover something in theworld, in the other casea cognitive object. One difference is that although discovering a regularity or a law of nature may require cognitive intervention and human ingenuity, a regularity or a law of nature is something we

find in the world rather than create or invent. Proto-theoretical entities and a full-fledged theory, on the other hanare our own creations or inventions. They are new tools for acquiring knowledge or new information channelsthrough which we interact with the world. This categorial difference will be reflected in the process of discovery.At first sight, the difference seems to be so big that one may wonder why we subsume both kinds of processesunder the same title of "scientific discovery."

Until now I have not distinguished between different stages in the development of a theory. It seems that even if growing theory is not a statement, a mature theory comes close to being a statement. When a theory matures andbecomes well established it is relegated to the unquestionable background knowledge of science. In its maturestage, the basic structure of the theory almost does not change over long periods of time. The theory is mainlyapplied for explanation and prediction, and is employed as a premise in scientific reasoning. It would be temptingto say that at this stage a theory is a statement, referring to a portion of reality. Namely, we may treat the matureversion of the theory as what remains of the dynamic tool. Indeed, when people say that a theory is a (set of)statement(s), they have in mind a mature version of the theory. Thus, we may view the established version of thetheory as an object of discovery, which may constitute a substantial advance over the initial version. As we willsee when we discuss kinds of discovery processes, the process of discovering a theory may indeed be a prolongedynamic process resulting in a mature version of a theory. Thus, in addition to the discovery of the initial versionof a theory, there is another kind of discovery, which is a dynamic process in which the theory is adjusted to thedata and further elaborated. For example, Bohr's discovery of the initial or "naive" version of the structure of thehydrogen atom was the major discovery. However, the mature version, including elliptical orbits, relativistic effecand spin, constituted a discovery in its own right.

Yet, even a mature theory need not, and perhaps should not, be seen as a static entity referring to some definiteentities in the world. Classical mechanics, for example, the paradigm of scientific theory, gives a generaldescription of the worldgeneral equations which can be applied for describing different kinds of systems in the

world. The application of the theory to a new kind of physical system is in many cases a creative task in its ownright which does not involve mere computations. Here we should distinguish two kinds of applica-







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tion: the application of the theory to a general system, such as the physical pendulum or the planetary system,which results in a "model" for this general system, and the application of the theory to a concrete, specific,pendulum or planetary system. The structure referred to by this kind of "model" can be viewed as a generalizedlaw of nature applying to a general kind of system.

The application of a theory to new systems is an essential part of the development of the theory proper. Indeed, ththeory can be viewed as a theoretical core plus the range of general kinds of systems to which the theory appliesIn the early stages of the theory development, the core is changing in order to adjust it to new kinds of systems. Ithe mature stage, the core may change only marginally, but the range of applications expands. Hence, we can saytwo things with respect to a mature theory. First, even in its mature stage, a theory is developing. Second, themature theory is not a statement about reality. Rather it specifies general ways of treating different kinds of systems. Its domain of application expands and this is one of the major ways through which a theory grows. Only"model" (in the above sense), describing a certain kind of system, functions as a statement referring to a generalstructure or to a generalized relation existing in the world.

In summary, the statement-view is not appropriate for describing the two major aspects of the growth of a theoryas a dynamic entity. It is not appropriate for describing a developing theory which is changing in its basic structuAnd it does not do justice to a mature theory extending its domain of application. In both cases the theory serves

a guide for the growth of knowledge about the world rather than as a statement referring to something in theworld.

Due to the dynamical nature of scientific theories, the process of discovering them requires a high degree of creativity. Furthermore, the plasticity of theories makes them liable to creative changes and in particular tounintentional or serendipitous changes. As I will argue in Part II, scientific creativity is equated withunintentionality and serendipity. And this is what makes scientific progress an evolutionary phenomenon.

1.2.4 Explanations, Problems and Solutions

There are three additional kinds of products of discovery which deserve our attention, since they are related to thetheoretical structure of science and to its evolutionary nature.

Explanations

There are two kinds of scientific explanation: an explanation of the properties and structure of general systems,phenomena, regularities and laws of nature and the explanation of specific events and properties. The first kind ofexplanation is derived from the theory in conjunction with some assumptions regarding the structure or thedynamics of the explanandum. For example, a modified version of Kepler's laws was derived from Newton'stheory







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of universal gravitation in conjunction with Kepler's model for the solar system. An example of the explanation oa phenomenon, i.e of a general kind of process or event, is the explanation of the phenomenon of tides which isprovided by gravitational theory in conjunction with some assumptions about the initial condition of the systemconsisting of the earth, the sea and the moon.

In the second kind of explanation, the explanation is given by a law or a theory in conjunction with initial or boundary conditions, possibly in con-junction with auxiliary hypotheses or assumptions. This is the "deductive-nomological" kind of explanation treated by Carl Hempel (1965). However, the first kind of explanation is morecommon and more important in a theoretically advanced science. The advance from the phenomenological stage empirical generalizations to a theory brings about the explanation of the phenomenological regularities by thetheory.

To find an explanation is not the same as finding a cause. If we adopt the hypothetical realist view, a cause is anentity existing in the world. The cause of the tides is the moon moving in a particular trajectory. The cause of thepain I feel in my head is the object which hit it. Both causes are events, which exist in the world. However, theexplanation of the phenomenon of the tides, or of a particular occurrence of a tide, is a human product. If we treascientific explanation along the lines proposed by Hempel, for example, we have to find the theoretical premisesand the statements describing the initial conditions, from which we can derive the explanandum. It may happen

that we know all the premises from which such an explanation can be constructed, without being able to constructhe explanation. Discovering an explanation involves finding the right ingredients, and the right combinationsthereof, from our repertoire of theories, laws and facts, from which we can derive the explanandum. We encountthe same situation in puzzle-solving. Here the discovery is not made by looking at the world, but by looking at ourepresentation of the world. In Chapter 6, I will discuss a theory which describes the process of discovery asconsisting of quasi-random formation of combinations of "mental elements." The product of the process is a stabl"configuration" which is finally selected. In the above mentioned process of discovering an explanation, theproduct of the process is, indeed, a "configuration'' of mental elements, i.e. of ideas, theories, laws, facts, etc.,which solves the problem.

Problems and Solutions

A very general category of discoveries is a solution of a problem. When we resolve an inconsistency in a theory between theories, or a disagreement between a theory and data or when we find an explanation for a puzzlingevent or when we explain a set of empirical generalizations by a general theory, we solve a problem. In general,when our scientific standards require a specified manner of explanation or understanding, we face a problemwhenever we have not yet achieved the goal set up by these standards. Problems may arise in theoretical andpragmatic contexts.







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However, an important kind of discovery is the discovery of a new problem. In many cases, the discovery of asolution of a given problem leads to the emergence of new problems. A discovery of a new problem may lead tosignificant progress of science, sometimes more so than a discovery of a solution of a known problem; such a neproblem may open up a whole new field of investigation. For example, the problem called "the ultravioletcatastrophe" in blackbody radiation was crucial for the discovery of quantum mechanics. Problem solving can be

construed as an evolutionary phenomenon. We will turn to this point when we discuss the subject of serendipityand the evolution of science.

1.3 The Kinds of Discovery Processes

Let us divide processes of discovery into two main categories which may be termed "exposure" and " generation.Paradigm cases of discovery by exposure from everyday experience is when we discover the hidden content of aclosed box by opening it, when we discover something in the darkness by throwing light upon it or when we inferthe hidden cause of an event (discovering who is the murderer in a detective story). An example of generationaldiscovery in everyday experience is when we discover the maximum tension which a rope can stand by hangingincreasingly heavier weights on it. Or, when we discover how the color of the rope changes when we put it in acertain solution. Another example is when we discover the effects of growing some plants in a greenhouse. In allthese experiments, the new effects discovered by us are in a sense created by us. However, the salient cases of generational discovery occur in science (actually, the above examples are on the border-line between ordinaryexperience and science), whereas in everyday experience exposure cases are more typical. In fact, generationaldiscovery is one of the characteristics of modern science. In general, discovery by exposure does not createanything new in the world or in our representation of the world, whereas generational discovery, in a sense,perturbs the world, interferes with the natural course of events, creating new, or new kinds of, observational or theoretical entities. The sense in which generational discovery perturbs the world will be discussed in section 1.4.The distinction between exposure and generation will be essential to the evolutionary view of discovery: it isgenerational discovery which exhibits the characteristics of natural selection.

1.3.1 Exposure

Discovery by Observation

Discovering a new object, event or a new observable property by looking or sensing, or by using observationaltools and methods. Examples: The discovery of Jupiter's satellites by Galileo, using his tele-







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scope, or the discovery of the structure of a macromolecule, using an electron-microscope. Observation is by nomeans a passive act, since it involves looking at chosen directions, employing instruments and making inferencesHowever, it is not a generational process, since the act of observation does not create, or significantly effect, theobject of discovery. We have to qualify this statement with regard to the observation of macroscopic systems. Inquantum physics, observation does perturb the observed system.

Discovery by Searching

Scanning a given portion of space looking for some prescribed event or object. Examples: Looking for oilresources by searching a given area. Scanning bubble-chamber photographs in order to discover certain events.Searching for a solution to a problem in a space of possible alternatives. This procedure is practiced in problemsolving and in heuristic search in artificial intelligence. Search may be conducted where there is a finite number opossible hypotheses for explaining a given phenomenon. Here search means eliminating alternative hypotheses, tproduct of discovery being the remaining alternative. If there is a finite number of alternative hypotheses for thegeneral cause of a phenomenon, this method is reduced to "inductive" inference, i.e. eliminative "induction"; if wcome to the conclusion that there are n possible causes for a given general phenomenon, we may eliminate n-1possibilities by conducting appropriate observations or experiments. The result will be the discovery of the causethe phenomenon. In fact, eliminative "induction" of this kind, were the number of possible hypotheses is finite, is

deductive inference.

Calculation and Computation

Mathematical calculation may lead to important discoveries in everyday life as well as in science. For example, bmeasuring the length of a metal rod at two different temperatures (L and L0, at t and t0), we can determine itscoefficient of thermal expansion (a) by using the formula L=L0[1 + a(t-t0)]. If we have a table of thermalexpansion coeficients for different metals, we can use this result to discover the chemical identity of the metal.This is an example of a procedure in which one starts from some premises which include certain mathematicalformulas and the numerical results of some measurements and arrives at the result by substituting the numericalresults in the formulas and carrying out the required mathematical operations. The mathematical formulas may bederived from a full-fledged theory or may be just rules of thumb. This procedure is a specific case of deductive

inference when one starts with some premises and arrives at a logical conclusion by following the rules of inference.

Inference

The question is why do we categorize calculation, and deductive inference in general, as a process of discovery bexposure rather than by generation? The reason is that the process of deductive inference leads to informationwhich is already logically contained in, or necessarily implied by, the







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premises. Thus, deductive inference cannot create any new information or new theoretical entities referring to newkinds of objects, events or phenomena in the world; it is just a process which exposes to us or uncovers what is"hidden" in, or implied by, the set of premises.

Deductive inference is the paradigmatic case of discovering by exposure what is hidden in our representation of thexternal world. Similarly, discovering the content of a closed box by removing the cover is the paradigmatic caseof discovery by exposure in the external world. In the first case we discover information contained in a set of statements which is beyond the grasp of our intellect without carrying out a sequence of logical transformations,whereas in the second case, we discover objects in the world which are beyond the reach of our senses withoutpulling up the cover. In both instances, our knowledge grows as a result of the discovery. Indeed, our knowledgenot deductively closed. If our knowledge is represented by a set of statements K, not all logical consequences of Kare known to us. Otherwise, we would have to accept the claim that a child knows all the theorems of Euclideangeometry as soon as he learned its axioms.

By deductive inference we can arrive in mathematics not only at new numerical results but also at new theorems.In physics, we might arrive at new laws of nature expressed in mathematical formulas. For example, in Newtoniamechanics, the laws of planetary motion were discovered by deriving them from the inverse square law of universal gravitation. Non-mathematical deductive inference does not carry us as far as mathematical derivations

do but it is still valuable as a means of discovery.

In computer science and artificial intelligence, one may arrive at far-reaching discoveries by logical inference. Bygiving the instruction FIND to the word processor I am working on, I can discover a "lost" word throughout mytext. Here we have a case where a physical object "hidden" in the text can be found by logical steps (made by amachine) which guides a physical search.

However, inference is not restricted to deductive inference. By inductive inference we may discover causes of phenomena and laws of nature. The most common inductive inference is arriving at a new generalization byenumeration, i.e. by generalizing from particular cases. What is common to these kinds of inference is that theylead to new information which is not logically included in the premises. The premises of an inductive inferencewhich leads to a generalization include information only about a finite number of past instances, whereas the

conclusion refers to an infinite number of past and future instances. Yet, this sort of discovery process can be stilviewed as a process of exposure. First, it does not generate new concepts or theoretical entities referring to newkinds of objects or phenomena; the conclusion (e.g. "all P's are Q") in an inductive inference does not contain nepredicates which do not appear in the premises (which refer, for example, to single instances of P's which are Q)Second, the new information generated by







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inductive inference can still be seen as "hidden" in the premises. Indeed, we can view inductive generalization, foexample, as an inference which relies on a principle of induction which is tacitly assumed, e.g. the principle whicsays that if a large enough number of instances of observed P's were found to have the attribute Q, and no instancof P was found not to be Q, than all P's are Q. If this principle is taken as a tacit premise, than the inductivegeneralization follows deductively. Hence, when the principle of induction is transparent, inductive inference can

be qualified as discovery by exposure rather than by generation. Here, too, the choice of the "right" predicates onwhich we make our inductive generalization is a crucial stage in the inference. If we use natural language, theproblem may not arise since the system of possible predicates by which we refer to the objects in the world isgiven in the language. In science, however, the system may change; this is in fact part of scientific creativity. Thileads us to the issue of natural kinds. Choosing a different system of natural kinds involves a creative act and theprocess would be qualified then as generational.

There is another type of inference, where the rules of inference are "material" rules. Here the rules themselvescarry information about the world, and the conclusion of the inference might contain predicates not appearing inthe premises. However, these predicates are not new since they appear in the inference rules. Hence, if rules of scientific discovery can be represented as material rules of inference, we may treat the discovery process asdiscovery by exposure. The issue of material rules of inference will be discussed in Chapter 2.

Dynamic Theory-Construction

As we have noted, in many cases a theory is not constructed in one act. Possibly after an initial discovery of an"ideal" version, or a first approximation, of the theory, the theory is gradually built through a dynamic process inwhich it is adjusted and readjusted to experimental results and to established theories. This process yieldsthroughout its history a sequence of different theory-versions. The sequence may be called (following Lakatos1970) "research program." For example, the discovery of the structure of the hydrogen atom, starting with theBohr-Rutherford model and ending up with quantum mechanical theories of atomic structure, can be seen as aresearch program. In general, when we are guided by an analogy or a background model in constructing a theorythe process of "spelling out" the model or the analogy is a process of exposure which may contain generationalelements.

1.3.2 Generation

In generational discovery the object of discoverywhether it is an object in the world or in our representation of thworldis in a sense a product of the







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discovery process, hence we cannot say that it existed before its discovery in the same full-blown sense as doobjects discovered, for example, by direct observation or by searching.

Experimentation

By devising controlled experiments, which may involve sophisticated instruments and experimental methods, the

scientist may discover things which he would have never discovered in natural conditions. The objects or producof such a discovery come into existence to a large extent as a result of the experimenter's action. This claim maybe illustrated by the case of watching the behavior of animals in captivity. The patterns of behavior we mightdiscover in these circumstances do not necessarily reflect the animal's behavior in its natural habitat; to a largeextent these patterns of behavior appear as a result of the artificial conditions we create. As we will see, certainprocesses of observation in particle physics belong to the category of generational discovery; in these processes tobserved particle is sometimes produced in the process of observation. Thus, the border-line between observationand generation is not sharp. As we will see in section 1.4, one of the ways of exposing the deep structure of natursystems is by generating artificial products, such as new short-lived particles.

Theory-Construction

As we have observed, the construction of an explanatory theory involves the introduction of new concepts or newtheoretical entities which do not belong to the observational vocabulary or to the old theoretical vocabulary. Thusthe processes of constructing theories, such as the kinetic theory of gases, Newtonian mechanics or the germ theoof disease is generational.

The direction of scientific explanation or unification is the direction of the growth of knowledge in the strongsense. In this sense the advance of science is not restricted to the accumulation of new empirical information, or new information on a given theoretical level. Rather it is characterized by progressing to deeper levels of explanation and reality. What is common to experimental and theoretical generation is that discovery by generatiois related to probing into deeper levels of reality.

Yet, even when we arrive at a theory by generation, the process of discovery must include a stage of exposure.Only after testing some of its far-reaching predictions can we discover that the theory is successful. The theory

may be constructed first, and then it is tested and highly confirmed. Or, construction and confirmation may procetogether. Only after the theory is confirmed does the scientist find out that the generated theory is a discovery. Thconfirmation may come in a dramatic event, or it may be a prolonged process. The act or process of confirmationmay be viewed as an act of exposure; we derive a prediction from the theory and discover that it fits observationadata. Ideally, the derivation of the prediction is a process of deductive inference, by which we expose the predictiwhich was hidden in the known







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premises, consisting of the theory and the relevant background knowledge, including the initial conditions.

The Link between Experimental and Theoretical Generation

The above two categories of generational discovery, experimental and theoretical, are closely linked. In order toput a theory which is remote from the phenomenological level to a stringent test, the scientist has to devise

controlled experiments which create artificial environments. In this way, experimental generational discoveries armade. On the other hand, in order to explain the results of highly sophisticated experiments the scientist has togenerate highly abstract theories. The result is that highly abstract conceptual systems and constructs which areremote from our everyday conceptual system and mental representation of the world are generated in order tocomprehend highly artificial phenomena generated in the laboratory which are remote from everyday experience.Thus, the two processes are fed by each other.

1.3.3 Poincaré: The Poverty of Creation

Henri Poincaré's observations on discovery focus on mathematical discovery, however they are of value for understanding the process of discovery of ideas, theories and solutions of problems in general. Poincaré maintainthat selection is the focal point of discovery: "Discovery is discernment, selection." Selection is much more

important than generation. Everyone can form new combinations with mathematical entities. However, the numbof these combinations is unlimited and most of them are useless. Thus, the creative part of the process, i.e. forminthe unlimited number of combinations, is valueless. The discoverer chooses the unexpected useful combinations orelationships or hits upon them. In describing the way these combinations are created, Poincaré turns topsychological speculation. An unlimited number of combinations or hypotheses may be generated in thesubconsciousness. However, in the discoverer's consciousness mostly useful combinations appear. "Everythinghappens as if the discoverer were a secondary examiner, who had only to interrogate candidates declared eligibleafter passing a preliminary test" (quoted in Taton 1957,17). Thus, what distinguishes the discoverer from everyonelse is that he has an internal power of discrimination between the unlimited number of ideas and candidate-solutions. Most of the selection is done subconsciously. The sudden appearance of inspiration is due tosubconscious activity, mainly of selection of the most fruitful combinations, according to some feeling of "mathematical beauty" and ''aesthetic sensibility." These feelings are part of the tacit knowledge shared only by th

scientists (in this casethe mathematicians). Perhaps it is a necessary condition for being a discoverer to be capableof internalizing these shared tacit standards. In Chapter 6, I shall discuss a psychological theory which treats theabove process less speculatively.







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Two conclusions might be drawn from Poincaré's view. First, the more possible ideas or hypotheses we have for solving a problem or explaining some phenomena, the less we are close to our target. Note that the oppositestatement is not necessarily true: we might have a very few ideas, none of them is useful! Second, in contrast witthe common image of scientific discovery, the creative part of the process of discovery is valueless. However, wemay view the process of creation as generation and selection taken together; generation without selection is

fruitless. Third, the discoverer is somewhat less responsible for the act of discovery than what is commonlythought. Indeed, the main process is an unintentional or natural (psychological or even biological) process which carried out without the intervention of a human conscious act. We have here a first hint towards a specific kind ogenerational discovery process, discovery as an unintentional or involuntary phenomenon. We will turn to this kinof process in Part II. Thus, Poincaré's view diminishes the value of method of discovery. Unintentional or involuntary acts cannot be governed by method.

1.3.4 Eureka Events and Unintentionality

A dramatic moment of discovery may occur in a sudden act of revelation or as a gestalt switch, without anyintentional effort on the part of the discoverer. The story of Archimedes' discovery of his law in the bath, the storof Newton's discovery of universal gravitation triggered by the falling apple and Kekulé's story about the discoveof the ring-shaped structure of the Benzen molecule while daydreaming about a snake chasing its tail are perhaps

apocryphal. But we do not have to look too far for real cases of this sort. Most people have had the experience ofseeing something in a new light, of sudden understanding of an enigmatic phenomenon, discovering a relationbetween previously unconnected phenomena or finding a solution to a problem after many unfruitful attempts.Again, it is not uncommon to "see" suddenly that an idea or a theory which was employed for other purposes, or which had been forgotten, solves a new problem or provides an explanation for new phenomena. This associationof an idea or a theory with a problem or with an explanandum may occur as an eureka event.

In order to count as an eureka event, unsuccessful attempts must have already been made to solve the problem orto explain the phenomenon conceived. Such an event may come as a result of a long process of making intentionefforts to solve the problem and possibly after a period of incubation.

Not every process of discovery ends up with a momentous eureka event. We cannot always find a simple "mome

of discovery." Sometimes the process of discovery is gradual and can only be identified as a process of discoveryin retrospect; all depends on the object of discovery. If that object is a product of generational discovery, such as full-fledged theory, there might







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not be such a moment. For example, quantum mechanics (that is, the full quantum theory, not only Planck's idea the energy quantum) was generated-discovered through a lengthy process. However, there are cases of generationdiscovery which culminate with a final eureka event. Indeed, after a long process of trying to construct a theory oto solve a problem there might remain a missing link without which the theory is not satisfactory. The missing linmay then be found in an eureka event. For example, Darwin describes the creative flash he experienced after he

had read Malthus, which presumably supplied him with the missing link for completing his theory.Here we encounter again unintentional creative processes for which the discoverer cannot claim full responsibilityAccording to Simonton's theory expounded in Chapter 6, it is the same phenomenon described by Poincaré.Norman Storer presents some descriptions of creative people in the arts, which refer to a similar phenomenon(Storer 1966, 678): Creative people "have felt possessed by their work, which seems to have an independentexistence." A composer describes his experience as if "the work has come through, rather than from, him." He cia musician saying: "I feel as if I am an instrument through which something is speaking. ... It's as if I am standingoff from myself and watching while someting else takes over." In these processes the product, or the process, of discovery has objective existence entirely independent of the discoverer intentions. "It has a vitality of its own sothat it has been able to use the individual in order to 'make itself real.'" The creator is ''more a spectator at the act creation than the author who has been fully and consciously in command of the process." The creator who has thexperience tends, therefore, to be modest since he feels that he was only a spectator at the act of creation. As wewill see, this is not the only kind of non-intentional process of discovery of which the individual discoverer is notin full command. Another kind is related to the social dimension of science.

1.4 The Creative Element in Discovery and the Issue of Realism

1.4.1 Discovery, Invention and Creativity

As we have seen, a major connotation of the prescientific notion of discovery is to expose, to uncover or todisclose a secret. Hence, if we view science as a tool or method of discovery, and look upon discovery in thissense, we may be led to the very popular view that the aim of science is to expose the secrets of nature. Thefollowing three conclusions are implied by this conception of scientific discovery:

1.The aim of scientific inquiry is to reveal something objective which exists independently of thescientist's efforts to bring it to light, just as an inner







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component or mechanism of a clock exists whether or not there is someone attempting to expose it.2.There are obstacles facing the scientist in his efforts to find out what is hidden behind the observed phenomena.

3.The process of scientific discovery is the process of removing or overcoming these obstacles;whenever the latter are removed, the secret is revealed intact. Thus, science does not create anythingnew in the world, it only serves as a unidirectional mediator, or information channel, between theworld and the human mind.

This picture reflects a simplistic conception of scientific discovery embraced by naive realism. It views discoveryas exposure. According to this view, discovery is clearly distinguished from invention. Discovery and invention athe two ways by which novelty is generated in human culture. Discovery is the process of exposing somethingwhich exists independently of the inquiring mind. The latter is the object of discovery. The product of discovery ia new item of knowledge which represents the object of discovery. Invention is a process of generating somethinnew according to human design, to achieve certain purposes. The product of invention is a new tool, in the broadsense of the word. This distinction can be seen clearly in the discovery of X-rays which was followed by theinvention of X-ray photography for medical diagnosis. The discovery of X-rays was a discovery of a natural

phenomenon. It was an unintentional discovery. It seems, therefore, that the discovery was made without any actiintervention of the human mind which acted only as a passive receiver of the information. The invention, on theother hand, required a human design, which aimed at utilizing the discovery for certain purposes. Similarly, alphaparticles and protons were employed after their discovery as tools for further research in nuclear and particlephysics, i.e. for bombarding target particles and nuclei. This pattern of discovery-followed-by-invention seems tobe reflected in the interrelation between basic, or pure, science, which is engaged in discovery, and applied scienand technology which are invention-oriented.

Yet, in science, the process of unveiling the secrets of nature leads to the creation of material artifacts and theorieUsing a new observational instrument or method has a similar effect as creating a new artificial environment. Thueither the object of inquiry or the observational tool is an artifact. In fact, in many cases the boundary between thobservational tool and the observed system is arbitrary and determined by convention. For example, in the case o

the discovery of radioactivity, the photographic plates may be seen as the observational tools or, alternatively, aspart of the system investigated. In a collision experiment where particle A collides with particle B the process mabe viewed as observing the structure of particle B, where B is treated as a







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target and A functions as a probe. However, in particle physics, the two-particle system is treated as a whole,where A is treated as part of the investigated system.

Ordinary observation may involve throwing light upon the observed object, where the light is regarded as a meanof observation. Similarly, in a high energy photoproduction experiment the structure of a proton, say, can beprobed by "throwing" high energy photons on it. Of course, in this case, structure means something different fromthe ordinary spatial notion. However, it is mainly the photon-proton system which is studied without distinguishinbetween a projectile and a target. In general, the principle is the same: the colliding projectile, serving as a probedraws information about the properties and structure of the target object. In photoproduction experiments, for example, the so-called form factors of the proton can be determined. And these quantites are related to thestructural properties of the proton. However, in this case the process of "observation" may involve the productionof particles and resonances which were not present before the observation. Here the generational effect of the actof observation is manifest in its highest degree.

On the other hand, our description and explanation of the phenomena is colored by our conceptual systems andcategories. And in a highly theoretical science, which departs significantly from the observational or phenomenological level, the scientist is not only guided by the available conceptual system and by his prior expectations in conducting his observations and in describing the phenomena. He also looks for deeper

explanations. In order to expose a hidden cause or hidden structure behind the observed phenomena, the scientistgenerates sophisticated instruments and experimental methods, on the one hand, and a highly abstract conceptualsystem and an intricate theoretical machinery, on the other hand. Moreover, in trying to expose the secrets of nature, the discoverer creates, in a sense, some of the objects of his inquiry. The products of this kind of process discovery seem to be human artifacts; they seem to be products of human design. In fact, any experimental systemwhich is designed to carry out controlled experiments can be viewed as an artifact. Hence, their products, theexperimental results, must be artifacts as well. Furthermore, these artifacts serve, in a sense, certain purposes, sucas testing a theory or explaining the data. Thus, the discoveries produced in these experiments seem to have all thcharacteristics of inventions.

On the other hand, inventions have some characteristics of scientific discoveries. In many cases, as in the abovementioned X-rays' case, an invention follows the discovery that a natural phenomenon can be exploited for certai

purposes or that an available tool may be applied for performing a new task. In other cases, the inventor carries oa process designed for achieving a certain purpose and discovers in the end that the product of the process can beapplied for achieving a different task. In general, an artifact becomes an inven-







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tion only after the inventor discovers that it achieves some purpose. This is similar to the discovery that a theoryprovides a successful explanation. Thus, a discovered theory may be viewed as an invention designed for the taskof providing explanation, whereas an invention can be viewed as a discovery that a certain artifact achieves acertain task. Furthermore, if a material invention is indeed successful in achieving a prescribed task, it means that reflects some elements of the natural or artificial environment in which it operates. The success is achieved only i

the artifact fits certain aspects of the world to a marked degree. Thus, information about the world is embodied inthe product of invention. The very success of the invention may, therefore, constitute a discovery about the worldFor example, the airplane embodies in its structure information about the aerodynamic properties of the atmosphethrough which it was designed to fly. Indeed, in many cases, an invention leads to scientific discovery. For example, the invention of the steam engine paved the way for the development of thermodynamics. Thus, inventimay lead to discovery and invention may follow discovery, such as in the X-rays case.

Inventiveness plays a major role in the generational discovery of theories. Theories are invented in order to explathe observational or experimental phenomena and to resolve anomalies. Their success depends on how much theysatisfy the explanatory "needs" or requirements of the scientist in light of their agreement with observedphenomena. Experiments are designed to help in inventing and testing theories.

In summary, discovery and invention embody both the structure of reality and human creativity. In addition,

inventions are sometimes discovered and discoveries are sometimes results of human inventiveness. Onlydiscovery by exposure can be sharply distinguished from invention. We would not say that Columbus inventedAmerica, that Mendeleev invented the Periodic Table of Elements, that Boyle invented his gas law, or thatsomeone who derived a deductive conclusion from a set of premises invented the conclusion.

1.4.2 The case of Particle Physics: An Active Look at Matter

The issue of creativity and reality in scientific discoveryboth observational and theoreticalis most forcefully posedin particle physics. Two peculiar features which have emerged in contemporary particle physics draw our attentioone is related to the observational or experimental side and the otherto the theoretical side of this frontier field of science (see Kantorovich 1982).

Experiment: Creating Material Artifacts

In the experimental arena what immediately captures our attention is that particle physicists seem to be studyingartifacts which they produce in the laboratory. For example, in the interaction p-pÞK0p, the K meson and thelambda are produced from a negative pion colliding with a proton. Or, in inelastic electron-proton inter-







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action e-pÞe-N*, higher mass resonances, such as N*(1518) and N*(1688), 4 are produced. These resonances, arshort-lived states of matter. For the "outside observer" it seems that in the last three or four decades, particlephysicists have been continuously engaged in producing at high energies more and more short-lived particles or states of matter which provide the data for their theorizing. So the question is: in what sense are we entitled to saythat high energy physicists investigate and discover the structure of matter? Or, in what sense is it "pure" nature

which they study and not nature which is highly contaminated by human intellective and active intervention?Here the experimental method has been stretched to its extreme. The experimental physicist has always createdartificial systems or objects in controlled experiments. The chemist or the nuclear physicist even produced newkinds of material objects, but the artificial material changes were always seen as an analysis, a synthesis, or arearrangement of preexisting fundamental constituents of matternot a creation of new ones. For example achemical reaction is a rearrangement of atoms; atoms are not created or annihilated. Of course, this description interms of fundamental constituents, such as atoms, already relies on some established theory of matter which isregarded as unquestionable. But this is true for scientific experiments in general; in planning and conducting anexperiment, the scientist always has a background knowledge, or at least an initial hypothesis, about his domain oinvestigation. From this basic picture, he starts his theorizing. In particle physics, we encounter a situation whereaccording to the prevailing conception, the artificial products do not seem to be constructed out of preexistingmaterial objects; the new artifacts emerge as new states of matter.

The question is, therefore, does the particle physicist discover these short-lived particles or resonances in nature odoes he create them? The same question arises in any experimental science in a milder form; controlledexperiments always create artificial environments and the question is in what sense the scientist discovers naturalphenomena in such an environment. Or why should we say that he exposes, rather than generates, thesephenomena. An answer to this question may help us to understand why a generational discovery is indeed adiscovery. In the following, I shall offer three interrelated answers to this question.

(i) One answer is that if we wait long enough, we would find the new states of matter in natural conditions, for example, in cosmic rays. Thus, distant galaxies can be viewed as natural laboratories in which these processesoccur and the new states of matter produced. In this sense, the scientific laboratory serves just as a means of discovering these kinds of processes and states more quickly, and in a controlled manner. The physicist is viewed

therefore, as reconstructing or "preconstructing" natural phenomena in the laboratory. However, if we wait for certain phenomena to be discovered in natural circumstances, we might have to wait longer than the life-time of humankind or







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of life on this planet. Hence, the physicist's role seems to be more essential than the role of pre-constructing natuphenomena, since it may happen that without the physicist's intervention, these new states of matter would never have appeared on earth. Thus, the physicist discovers in the laboratory something which potentially exists in naturbringing it from potentiality to actuality. The potential existence is the objective thing whereas the actualoccurrence is contingent, depending on initialnatural or artificialconditions. Hence, in generational discovery such

as this, the physicist discovers something objective which exists independently of the discovery process.(ii) This brings us to a second answer to the above question. In discovering a new phenomenon in the laboratory,the only manner by which the physicist intervenes in the natural course of events is in setting up the appropriateinitial conditions; nature does the rest. When the physicist sets up the appropriate experimental arrangements andsupplies the right amount of energy, for example, he creates the conditions which are necessary for thephenomenon to occur; he thus creates the conditions by which the phenomenon undergoes the transition frompotentiality to actuality. Whenever these conditions are created, the natural process will take place independently the experimenter's intentions or design. In this respect, there is no real difference between a Galileo on the tower Pisa and the modern high energy particle physicist in Fermilab. In the falling bodies experiment, the experimenterjust brings the body above the ground level and set it free. The body will then fall down along distances which arproportional to the squares of the time periods. The law of free fall, i.e. the product of discovery, is independent othe experimenter's intentions. In the same way, when the particle physicist generates electron and positron beams an appropriate electromagnetic field and supplies the right amount of energy in a colliding-beam experiment, hemay produce many new states of matter or particles, provided all the relevant conservation laws, such as theconservation of energy and electric charge, isospin and unitary spin, are obeyed. Through these particle-productioexperiments, he may discover some of these conservation laws. Thus, the experimenter sets up the initial conditioand then nature takes the lead, allowing only the products which obey the laws of nature to appear.

This brings us back to the distinction between discovery and invention. The inventor constructs his artifactaccording to his design. He may wish to employ known natural phenomena for achieving the task. However, he isnot waiting for the answers of nature as the scientist does. Unlike the scientist, he does not wish to let nature takethe lead and surprise him, yielding unintended results which will spoil his plans. An unintended result constitutesdiscovery. However, with respect to the original intentions of the inventor, such a discovery is an undesirableresult, whereas for the discoverer, the discovery is of course very much desired, in particular, if the discovery is

something unexpected. Indeed, an unexpected discovery reflects nature's contribution to our







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knowledge which is relatively independent of our expectations and presuppositions. In such a discovery humanintellective contribution is minimized and nature's contribution is maximized. Thus, the scientific discoverer wishto discover phenomena and laws which reflect as much as possible nature's workings rather than humancontribution.

The criterion of surprise may, therefore, distinguish the discoverer from the inventor. The discoverer who aims atdiscovering natural phenomena, rather than the products of his own fabrications, should seek the unexpected. Thicriterion is related to the view presented in Chapter 5 that serendipity is a major source for scientific discovery.According to this pattern of discovery, the discoverer sets out to find a given kind of phenomenon and findshimself discovering a different kind. According to the principle of serendipity, the discoverer should welcomeunintended discoveries. This is an epistemological principle related to the growth of knowledge. The main functioof discovery is indeed epistemic. Invention, on the other hand has a pragmatic role. The inventor aims ataccomplishing a specified task. He, therefore, designs the process of invention according to what he already knowin order to produce the required tool. The process of invention seems to be intentional, employing for a usefulpurpose what has already been discovered.

Yet, important inventions also come about serendipitously; one aims at producing a tool for one purpose and findout that his final product can also, or only, be utilized for another purpose. In this case, the inventor actually

discovers unexpectedly that something is useful for certain purposes. Thus, neither creativity and human design,nor intentionality or the criterion of surprise can clearly distinguish between discovery and invention. Generationdiscovery and invention stubbornly exhibit a high degree of similarity. This is not surprising if we adopt the naturselection model for sociocultural evolution and the evolution of science. According to this view, inventions anddiscoveries play the role of "blind mutations" in this evolutionary process. Hence both are not goal directed. Thisview will be expounded in Part II.

(iii) The third answer to the discovery vs. generation question is that in producing "artifacts" in the laboratory, themain aim of the scientist is not to discover the new artificial phenomena or states of matter; as I indicated in thelast section, the production of the artifacts serves mainly the purpose of discovering the laws of the deep structurebehind. For example, after the hope that the electron, the proton, the neutron and the pi-meson are the fundamentconstituents of matter faded and the list of "elementary" particles became increasingly longer, the particles were

not treated as fundamental any more and the word elementary was omitted from the title "elementary particlephysics." As a result, the importance of discovering a new particle for its own sake was diminished (cf. section1.2). In the sixties and early seventies, the production of new particles and resonances served the purpose of discovering or testing theories of internal symmetry of hadrons or theories of hadron dynam-







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ics, such as SU(3) symmetry and higher symmetries or Regge poles and Smatrix theories. The discovery of theomega-minus particle, for example, was an important event since it provided high confirmation for the SU(3)theory. Indeed, a typical particle theory predicted, among all other things, the existence of certain particles andresonances which had not yet been discovered.

In general, one of the aims of the physicist is to find conservation laws and invariants. This can be done bygenerating all possible material changes in the laboratory, finding out what remains invariant. Theories of symmetry in particle physics are generalizations of such conservation laws. Hence, what the particle physicistproduces in his laboratory is not his main object of discovery. These are the laws of nature and invariant relationswhich matter in this case, not so much the list of new particles.

Discovering by generation of the various particles also serves to expose the deep structure of matter. This is theprinciple which was mentioned in the last section: by generational discovery on the phenomenological or observable level of matter, the physicist exposes the deep, unobservable, structure of matter. Indeed, some of theconservation laws related to the internal symmetries of hadrons, such as unitary symmetry, were viewed asreflecting the deep structure of matter. Thus, when the experimenter produces the variety of particles, or discoverthem by generation, he exposes these conservation laws, or the deeper structure of matter. The deep structure of matter is the natural, or human-independent, component of the discovery.

Theory: Creating Abstract Entities

In order to explain and comprehend the complex data generated in the highly artificial environment of experimental physics, the theoretical physicist employs highly abstract theories, such as quantum relativistic fieldtheories, quantum chromodynamics (QCD) or superstring theory. The wave functions, fields, particles, colors andstrings appearing in these theories have at most only a very faint resemblance to their counterparts in classicalphysics or in ordinary experience. These entities "exist" in abstract spaces, such as the infinite dimensional Hilbespace. The quarks, for example, which are the ultimate constituents of matter, according to contemporary theoriesof matter, exemplify this abstractness. They have "color" but cannot be seen. They are "particles" but defy allattempts to be individually detected as electrons, protons and mesons. Quarks appear only as constituents of baryons and mesons but cannot be found in isolation. The primordial model of a corpuscle had already been

stripped of its original qualities in the classical theory, where we encounter, for example, point particles or particles which possess only the quantitative properties of mass and momentum. Quantum theory drew its basicanalogy for the particle aspects of atomic entities from the classical corpuscle model, where the possession of kinematical and dynamical properties, such as velocity and mass, and the adherence to equations of motionconstituted the so-called positive analogy, whereas pic-







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turability or amenability to a causal description in space belonged to the negative analogy. Quarks are even furthremoved from the commonsense notion of a particle. Thus, in order to comprehend the data of high energy particphysics, theoretical physicists generate highly abstract theoretical constructs. The attempts to further develop andtest the theory yield more data which need further theoretical development and so forth.

It seems, therefore, that the physicist starts as a naive realist, trying to comprehend what he observes. However, hattempts to explain the phenomena he encounters lead him to create increasingly more abstract theories whosetesting requires the production of an increasingly artificial phenomena in the laboratory. The question of scientificrealism is thus forcefully posed.

1.4.3 Epistemological Realism: Construction, Transaction and Representation

In recent years realism has been split into many versions, such as hypothetical, metaphysical, epistemological,convergent, naturalistic, modal and constructive realism. In relation to scientific discovery, it will be useful toadopt the distinction between metaphysical and epistemological realism (see Stein 1990). Metaphysical realism isbelief about the world: the belief in objective reality or in an external world which is independent of human actioor thought. Epistemological realism is the view that we can know objective reality. We will be interested inepistemological realism since it is a view about discovery: the process of discovery provides us with an access to

objective reality. From this it is implied that the object or product of discovery is a real entity, or that it refers toreal entities. Epistemological realism presupposes metaphysical realism. I will concentrate now on epistemologicarealism. In doing so, it will be helpful to introduce the naive-sophisticated scale of epistemological realism, whicwill encompass some of the other versions of realism.

A somewhat naive realist may view our conceptual systems and experimental and theoretical tools as our means interaction with the world; we do not construct the world or invent it, rather we interact with it. We construct or generate the means of interaction: the experimental devices and the conceptual and theoretical machinery. Byemploying new modes of interaction which are products of human creativity, we might expose new relations andregularities which exist independently of the interaction. Human creativity just helps us in exposing existingobjects, relations and regularities; it helps us in "pulling back the curtain on pregiven," to borrow Bruno Latour anStephen Woolgar's expression (1979, 129).

A more sophisticated realist would maintain that our means of interaction give us only certain aspects of reality,depending on our cognitive apparatus, needs and interests, but we would never know the "things in themselves," tuse the Kantian terminology. By the borrowed term "things in themselves"







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I refer here to objective reality in two senses: (1) reality in its totalitynot just aspects of reality (which interest us which are related to our needs), and (2) unperturbed reality, i.e. reality which is free from our active and cognitivintervention. These two senses are partially overlapping; when we look at one aspect of reality, the picture we getis not free from our cognitive intervention. Thus, according to the above view, our picture of reality, which is aproduct of our interaction with reality, reflects both our own constitution and the structure of reality.

The anti-realist would say that the means of interaction are not neutral channels of information; they create a new"reality" which cannot be attributed to something objective that is independent of us. One traditional alternative torealism with respect to theories is instrumentalism, an approach which holds, roughly speaking, that theories arejust instruments for organizing the observational data and for predicting new events and phenomena. A theory donot refer to real objects, structures, natural laws or relations existing in the world and does not possess a truthvalue. This was the way to save empiricism which maintained that only observational terms refer and aremeaningful. Thus, theoretical terms do not refer; they are parts of the theoretical system which only functions as instrument.

One of the recent non-realist views is reflected in the title of Andrew Pickering's book Constructing quarks (1984Its main theme can be encapsulated by the claim that scientific knowledge is socially constructed. According to thview, which is termed "constructivism," "construction" is contrasted with "representation" (Giere 1988, 57).

However, constructivism need not be contrasted with realism nor constructionwith representation. This is evidentfrom the transactional approach to the epistemological process. I will treat this approach, which refers mainly tothe individual knower, as one component of a wider conception of constructive realism. The other component, thsocial component of constructivism, will be treated in my discussion of the social dimension of science. Thesimilarity between transactionalism and constructivism is reflected in the similarity between the key concepts,taken from the realm of commerce, that are employed by the two approaches. The key concepts are "transaction''and "negotiation." The first refers to transactional relations between the knower and the world, including his sociaenvironment. The second refers to negotiations between the members of a community of knowers that result inscientific knowledge. According to the second approach it seems that science is a trade-game unrelated to theexternal world. When I discuss the social dimension, I will try to fuse the two approaches so that the resultinggame will bear essential relations to the real world.

According to the transactional approach, the knower builds his picture of the world through an active transactionwith it. W. Buckley, pursuing this approach and referring to transactionalists like Dewey, Mead and Piaget,describes knowledge as follows:







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Knowledge is not passively and finally given merely through information input to the sensory apparatus, butrather is actively constructed and reconstructed through continual interchange between the individual andhis physical and social environment... the world as we see and act on it is to a great extent created by us, ina sense that we gradually build up a construction of it by interacting with it. (Buckley 1972, 189, 1934)

The last words hint at a "convergent realist" view, the view that in our learning from experience, we are graduallprogressing towards truth. Piaget's most revealing message is that genuine knowledge is acquired only throughaction: "to know an object...is to act on it" (Piaget 1977, 30). Piaget finds a parallelism between the development individual knowledge and the growth of scientific knowledge. His classical works on the evolution of perceptionthought and intelligence in the child can provide us, therefore, with clues for understanding the development of scientific knowledge. Thus, the particle physicist who investigates the structure of matter by manipulating particleat high energies is playing the same game as the child who gets better results in memorizing designs of littlebuttons by acting on them rather than only watching them (Piaget and Inhelder 1971).

A related thesis (attributed to Vico) which says that we know or understand best what we produce by physicalaction or by creative thought can shed light on some of the most distinctive constructivist patterns in science. TheEuclidean and Archimedean ideal of deductive systematization, for example, may be viewed in this light, sincedeductive systems have been perceived as genuine human products. Thus, philosophers of nature and scientists

throughout the history of science have devised deductive systems of theoretical representation in which they coulreconstruct natural phenomena by deductive manipulations, in order to make the phenomena intelligible. On theexperimental level, we see scientists reproducing or preproducing natural phenomena in the laboratory.

Understanding through material or experimental self production is intimately related to understanding gained bymental or theoretical construction. In order to be able to reproduce an effect at will, in a controllable way indiverse circumstances, the scientist has to know the underlying "mechanism" or laws of nature which yield theeffect. Since he has no direct access to the hidden secrets of nature, i.e. to the underlying mechanisms and laws onature, he himself may invent them by active theorizing. The theory guides him in setting the appropriate initialconditions for producing the desired reconstructed natural effects. In case the results are not satisfactory, the theomay be modified or replaced. In this way, the scientist gradually approaches the understanding of the phenomenaby mental and material creative actions







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which are interlinked. This applies as well to our ordinary experience. Indeed, this is exactly what Piaget saysabout action and knowledge:

To know an object is not to furnish a simple copy of it: it is to act on it so as to transform it and graspwithin these transformations the mechanisms by which they are produced. To know, therefore, is to produceor reproduce the object dynamically; but to reproduce it is necessary to know how to produce, and this iswhy knowledge derives from the entire action, not merely from its figurative aspects. (Ibid., 30)

Knorr-Cetina expresses a similar view:

The constructivist interpretation is opposed to the conception of scientific investigation as descriptive, aconception which locates the problem of factility in the relation between the products of science and anexternal nature. In contrast, the constructivist interpretation considers the products of science as first andforemost the result of a process of (reflexive) fabrication. (Knorr-Cetina 1983, 11819)

However, according to the transactional view, there is no real contrast between construction and representationwhich is implied by the above passage.

There is nothing distinct in science in this respect; the child who plays with clay constructs or manufacturesdifferent shapes and pieces of clay. However, these products are not the final targets of his activity. The final targis the "law of nature" which he eventually discovers, or indeed fabricates, i.e. the law of conservation of matter, fexample. The child's knowledge is not purely descriptive. Scientific knowledge, a fortiori, is not purely descriptivIf we grant that its main aim is explanation and understanding, then in generating our "representation" of the worlwe cannot help being constructive.

In terms of the distinction between discovery by exposure and by generation, we express the same thing by sayingthat generational discovery enables us to expose the deep structure of reality. Those who make the distinctionbetween construction and representation do not distinguish between the shallow and the deep levels of reality.

The distinction between the shallow and the deep levels of reality is an epistemic distinction. If we view thegrowth of scientific knowledge as a stratified process, we can treat every given stage of knowledge as the shallow

level, from which we seek a deeper understanding, which means exposing a deeper level of reality. Thus, thestratified structure of knowledge is perhaps related to a stratified structure of reality, or of the section of realityexposed by science.







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The transition from the classical picture of matter at the end of the nineteenth century to atomic physics and thetransition from atomic physics to nuclear and then to subnuclear (particle) physics may be viewed as such aprocess, where in order to understand some anomalous phenomena on a given level, science had to construct a nelevel of theoretical knowledge and a new level of experimental technique in order to penetrate the deeper physicalevel. In this process, generational discovery on the nth level leads to the exposure of the structure of the n+1th

level.Thus, we may view observational tools (in the broad sense, including experimental methods, as well asexperimental systems employing high-technology), as the scientist's channels of communication with nature. Theintroduction of a new tool means the creation of a new communication channel that provides the scientist withinformation about new aspects of reality. The discovery of a new information channel is therefore a creativeprocess. In a similar fashion, the discovery of new conceptual system and theoretical structure amounts to acreative discovery of a new comunication channel with the world. As we have noted, both kinds of communicatichannelsthe observational-experimental and the conceptual-theoreticalare interlinked.

Thus, generational discovery of new communication channels expose new aspects of reality. As we will see, thiscreative process can be viewed as an evolutionary phenomenon.







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Chapter 2The Scope Of Method

In this chapter I will assume that scientific discovery is governed by reason and method. I will pretend that thesocial dimension is irrelevant to the process of discovery and that unintentional discovery belongs to the realm ofcuriosities. In short, I will adopt the inference-view of discovery. As we will see, the inference-view accounts forsome important features of discovery by exposure and even for some kinds of generational discovery. Yet theattempts to capture the creative elements of discovery by logic or method do not yield significant success.

2.1 The Nature and Function of Method

As we have seen in section 1.2, the objects or products of scientific discovery are very diverse in their kind; theymay be as diverse as the discovery of a specific event and the discovery of a full-fledged theory. Yet whenphilosophers of science talk about the method or the logic of scientific discovery, they do not always explicitlydistinguish between the different kinds of discoveries. In this chapter, I will refer mainly to the discovery of lawsof nature, theories and explanations. Even this category is still very heterogeneous; we have observed, for examplthe essential difference between theories and laws of nature.

In this section, I will raise metamethodological questions regarding the nature, function, form and origin of method, rather than describe or characterize in detail any particular method.

2.1.1 Who Needs a Method?

It is frequently claimed that a scientist arrived at a discovery "by intuition." This is meant to say that the scientistdid not systematically employ a method. Since this occurs frequently, we might treat it as a phenomenon whichmay be explained by psychological theory. Indeed, great scientists throughout the his-

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tory of science either did not employ particular methods in their discoveries or did not tell us about their methodsIn many cases, they left prescriptions which are supposed to constitute the method of discovery. However, it is noclear that they indeed did employ this method in their actual discoveries. Sometimes it is clear that they did not.Sometimes their prescriptions seem to be reconstructions after the fact of the discovery process. In this way, theytried to justify discoveries which were made unintentionally or even by mistake. When I discuss the role of

serendipity in discovery, I will mention some examples of great discoveries which were made as a result of errorsin applying some method or simply errors in calculation.

Some of Newton's "Rules of Reasoning in Philosophy" (Newton 1962, 398400), appearing in Book III of thePrincipia, can be viewed as rules guiding discovery. Rule IV, for example, says:

In experimental philosophy we are to look upon propositions collected [inferred] by general induction from phenomena as accurately or very nearly true, notwithstanding any contrary hypotheses that may beimagined, till such time as other phenomena occur, by which they may either be made more accurate, or liable to exceptions.

It is very questionable whether such a rule would assist an ordinary scientist in making a single discovery. It is togeneral and some terms appearing in its formulation are too vague. It actually says that the scientist should

discover good inductive generalizations from the phenomena. This is not a very useful direction for making adiscovery. In order to emphasize this point by way of exaggeration, we might compare it to the following uselessrule of discovery: "Construct the best theory which accords with the facts."

In fact, we do not have to invent such a rule. No less a scientist and philosopher than Descartes provides us with most instructive example of a method of discovery, which applies to every possible discovery and which is(therefore!) entirely empty. In his Discourse on the Method , Part II, he provides us with the following four rules oa method of discovery:

The first of these was to accept nothing as true which I did not clearly recognize to be so: that is to say,carefully to avoid precipitation and prejudice in judgements, and to accept in them nothing more than was presented to my mind so clearly and distinctly that I could have no occasion to doubt it.

The second was to divide up each of the difficulties which I examined into as many parts as possible, andas seemed requisite for it to be resolved in the best manner possible.

The third was to carry on my reflections in due order, beginning with objects that were the most simple andeasy to under-







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stand, in order to rise little by little, or by degrees, to knowledge of the most complex, assuming an order,even if a fictitious one, among those which do not follow a natural sequence relative to one another.

The last was in all cases to make enumerations so complete and reviews so general that I should be certainof having omitted nothing. (Descartes 1967, 92)

The first rule has more implications for justification or validation than for arriving at discovery. The second ruleapplies in particular to problem solving. The third rule applies to discovery of regularities in complex systems. Thfourth rule is supposed to apply to the last step in the discovery process. Leibniz reacted to these rules by sayingthat they amounted to the following prescription: "Take what you need, and do what you should, and you will gewhat you want."

Recommendations related to the general ways of problem-solving are given also by the mathematician CharlesHermite. He suggests paying attention to exceptions to the rule, to anomalies, to errors and to a gap or fault in aproof. These suggestions seem to be no better than Descartes'; they do not help us much. He advises us to correcterrors, faults, gaps, and anomalies, but he does not give us even a hint on how to do so. He does not do so sincethere is no way to correct all possible errors etc.

We can, therefore, formulate the following metamethodological "rule": The usefulness of method is inverselyrelated to its degree of generality. In this respect there are two extreme kinds of method: the most general and thmost specific. The most general, as we have seen, is empty. The most specific is very useful in very specific casewhich yield no real discoveries. For example, an algorithmic recipe for baking a cake is very specific and veryuseful but yields no exciting discoveries. At most, the cake will taste a little better. The most specific methods of the recipe type consist of a list of directions for repeating a known process under specified conditions. For instance, how to grow a certain plant in specified conditions, how to produce a specific chemical reaction withgiven quantities of materials or how to solve a given system of linear equations. Not much room is left for inventiveness or creativity in using a recipe-type method for the exact task the method was designed to fulfill. Amethod for growing a general kind of plant under various conditions, or a method for solving a general category systems of linear equations, leaves more room for creativity. The more general is the rule, the more creativity isneeded for applying the method in a specific case. Thus, creative minds are needed for applying very general

methods. And the most creative minds are needed for applying the most general methods, which are emptymethods or no methods at all. No wonder that a Newton or a Descartes provide us with the most general methodFollowing this type of argumentation, we arrive at







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the conclusion that the scientific genius is needed to make discoveries in cases when no appropriate method isavailable.

So the question is whether genuine science is an elitist enterprise which can only be carried out by a few greatscientists who do not follow any explicit method, or can it be done by an army of scientists who follow prescribemethods. The answer is that modern science needs both kinds of scientists: the great discoverers who do notemploy prescribed methods, or invent them in the course of their investigations, and the scientists-technicians whfollow prescribed recipe-methods. Big and democratic science needs more of the latter than elitist science. And othe scale between the great discoverer and the technician there is a whole spectrum of combinations thereof. Yeteven a technician may hit upon a great discovery "by chance," without employing a method.

When we ask who needs a method, be it a method of discovery or a method of evaluation, we must note thesymptomatic fact that scientists do not study "scientific method" as part of their ordinary scientific curriculum.They only study the specific methods required for research in specific areas. Scientific method is studied byphilosophers and historians of science. They study it mainly since they think it reflects the rationality of science.Thus, we may arrive at the seemingly counterintuitive conclusion that perhaps rational behavior in science isintuitive or unintentional; the rational agent acts intuitively, unaware of the method he is actually using, if any.

The answer to the question whether there is a method of discovery depends on the kind of discovery we arereferring to. If we adopt Kuhn's distinction between "normal" and "revolutionary" science, we might say that innormal science, where the scientist is engaged in problem solving, great discoverers are less needed thantechnicians. Great discoverers are needed in a revolutionary phase, where the known methods of problem solvingare not applicable. Indeed, as we will see later, many of the great scientific discoveries were not made with theguidance of an existing method. However, the distinction between normal and revolutionary science is not as shaas Kuhn presents it; revolutionary developments may gradually emerge from normal research. In some cases, it isthe collective work of many normal problem-solvers which yields a great discovery, although a great scientist mabe needed for recognizing the discovery, i.e. for discovering the new picture which has emerged, or for making thfinal decisive step in the process. The discovery of the special theory of relativity was to a large extent this kind odiscovery.

2.1.2 What is a Method of Discovery Supposed to Do?

It should be stressed that we are not dealing here with the so-called scientific method. In the twentieth century,under the reign of logical empiricism, the term scientific method refered mainly to the methods of justification orevaluation of the products of scientific discovery rather than to the methods of gen-







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erating, or arriving at, discoveries. The reason for this attitude is that it was believed that the rationality of sciencelies merely in justification and validation, whereas the process of discovery is a psychological phenomenon to bedealt with by empirical investigations, rather than by logical or epistemological analysis. As well will see in thefollowing chapter, the distinction between the context of discovery and the context of justification, which hasraised important objections, has lost its currency. So perhaps the term scientific method should refer to the metho

of discovery no less than to the methods of evaluation, restoring its original meaning which was employed byFrancis Bacon and William Whewell, for example.

What, then, do we expect a method to do for us? First, we should ask, what is our goal. We might be interested inrationality, for example. We might ask what method would guarantee that rational decisions will be made byscientists. This would apply to questions of selection and evaluation which have implication for the acceptance anrejection of laws, theories and explanations. The question of rationality would also apply to the manner in whichwe arrive at our discoveries. However, rationality might have two connotations: categorical rationality andinstrumental rationality (see Giere 1988). Categorical rationality is independent of any particular goal we have.Questions referring to the rational way of achieving a specific goal are related to instrumental rationality. In thiscase, the method of discovery will provide us with effective means for achieving the goal. For example, we mighask, what is the rational way to arrive from point A to point B in the shortest time. Or, how should we constructour theories if our goal is to make successful predictions, to be useful to society or to approach truth. Perhaps wecan relate the two notions of rationality by saying that when our goal is truth, instrumental rationality coincideswith categorical rationality. Thus, our views about the goals of science will bear upon the methods of science,including the methods of scientific discovery. Traditionally, philosophers of science thought that only the contextof justification or evaluation, in which theories are selected, has a rational dimension. In the next chapter I willoffer some arguments as to why a theory of rationality should have implications for the process of discovery.

Perhaps we would be very pleased if we had an algorithm which, when fed with the data and with basic theoreticassumptions, would yield a successful explanatory theory. Or perhaps we would be happy if we had possessedalgorithms for solving problems and resolving anomalies. If these were available, then scientific investigationscould be carried out by computers and the era of great discoverers would pass away. Of course, we are far fromthis dream. And perhaps it is not such a good dream at all, since many hope that scientific rationality is notmechanistic and that science is a genuine human enterprise which cannot be replaced by a machine. What would

happen to the ethos of science if a Copernicus, a Galileo, a Newton, a Darwin or an Einstein could be replaced ba discovery machine, and the discovery of the heliocen-







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tric world picture and the theories of universal gravitation, natural selection and relativity would not differ inprinciple from a production line? Thus, the less we demand from a method of discovery, the more we leave for thworking of human creativity.

The following are some functions we may expect a method of discovery to fulfill and some general requirementswe may expect it to obey.

(a) If the method of discovery should yield a statement, such as an empirical generalization or a statementexpressing a law of nature or a theory (in the traditional sense), we may require that a method of discovery willlead to a true product. However, this requirement is too strong and its implementation cannot be validated. It is tostrong since it will not account for the discovery of laws of nature which were stepstones in the history of sciencebut turned out to be falseas I mentioned in Chapter 1. Perhaps most of the laws of physics are strictly false and thdoes not diminish their value; each such false law yields successful predictions and explanations and contributesthe advance of scientific knowledge. Thus, we might say in a Popperian spirit that the way towards truth is pavedwith bold "lies." Moreover, if the product is non-analytic universal statement, we have no way of determiningwhether our method leads to truth. Empirical generalization, laws and theories yield predictions about events whiwill occur in the future. As long the future is open, we have no way of knowing whether these predictions will turout to be true and thus we have no way of knowing whether our purported discovery is true. So that even if we ha

a truth-producing method, we would never know that we had it. It is thus senseless to pose a requirement which wcould never know when it is fulfilled. Thus, instead of asking that a method of discovery will yield a true product,we might require that it will generate a satisfactory product, i.e. a product which satisfies the standards or desiderata prevailing in science. Such a method may yield a product which is approximately true, plausible,acceptable, complies with the world picture and established theories or provides a good explanation according tothe prevailing standards of explanation. Each of these standards will determine the nature of the method.

(b) A weaker requirement is that the method of discovery will yield a product with a high probability of being truor satisfactory. For example, the cannons of inductive generalization may guide us in constructing generalizationwhich are highly probable. Also Bayesian theory may advise us in this respect; for example, we will see that whewe construct a hypothesis with a high "prior probability," it will have higher chances of being confirmed. Hence, we have a method for constructing hypotheses with high prior probability, it will enhance the chances of making

discoveries. Thus, under this requirement, a method of discovery may produce good candidates for pursuit or for selection, rather than produce the ultimate product of discovery. Such a method, supplemented by a method of evaluation and selection, will constitute a







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method of discovery in the strong sense, which leads to a unique product of discovery.

(c) The method of discovery should yield an efficient discovery process. This is a necessary requirement since itwould be possible to arrive at many discoveries if we guessed blindly or waited long enough for chance discoverito occur. In this case, the progress of science would be too slow. For example, let us assume that we confineourselves to non-revolutionary science where the process of theoretical discovery employs a given scientificvocabulary without introducing new concepts. If we conceive our objects of scientific discovery as statements in given scientific language L, we might look at the process of discovery as a search process in L. The process woulbe searching for theoretical statements expressed in L. Thus, among the unlimited number of strings of wordswhich can be formed in L, we would search for those which are grammatically correct, which are meaningful, anwhich satisfy our requirements for explanation. We will have to wait some time before we discover the strings ofwords expressing a simple law of nature such as Boyle's law, and a longer time for the string expressing a theorysuch as, the theory of superstrings in particle physics. Since we will be searching in an infinitely large field, thetask of finding the simplest law might never be accomplished if we do not have some method for narrowing therange of search. This is the same as waiting for the Eiffel Tower to be constructed by chance events, withouthuman intervention. To be sure, there is a non-zero probablity for this to happen. Efficiency is, therefore, not amarginal requirement. Thus, we may view a method of discovery as supplying criteria for limiting the range of search or for making systematic search.

Yet, even systematic efforts may be inefficient and time consuming. Discoveries can be made by carrying outtedious calculations and making lengthy efforts. We can make an analogy with arithmetic operations. We candiscover the product of 258×983 by carrying out 258 additions of 983, or by using the multiplication method of multi-digit numbers. The second way is much more efficient and elegant. The method of discovery in this case isdiscovery in its own right. Furthermore, it is more important than the particular discoveries it produces. Inmathematics there are many examples of this kind. A discovery of a simple or short proof or a method of calculation or computation is sometimes no less important than the discovery of a new theorem. This is true of empirical science as well. Indeed, there are cases where a solution of a problem or a new explanation isenthusiastically accepted by the scientific community as a great discovery since it was discovered in an elegant ansimple way, in the sense that the process of arriving at the product of discovery was quick and efficient. Thus, thirequirement applies to the process of discovery rather than to its product.

Two important conclusions can be drawn here. First, an efficient or elegant method of discovery is a discovery inits own right. Second, an efficient or







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elegant method would contribute to the positive evaluation of the product generated by using this method.Therefore, the product may be considered to be a discovery mainly because the method of generating it wasefficient. This is one of the cases where the ''context of discovery" is relevant to the "context of justification" (seenext chapter).

A method of discovery which fulfills requirement (b), i.e. which generates plausible products or products with higprobability, is more efficient than a method which does not fulfill this requirement, since the former generates asmaller number of candidates for pursuit which have higher chances to be selected, so that time is not wasted ontoo many candidates.

(d) An important requirement is that the method will be general enough. A method which is designed to generateonly one discovery or a specific kind of discoveries in a restricted domain, cannot be treated as a method of scientific discovery. For example, a method for discovering the chemical composition of a material, or of a certakind of material, is not a method of scientific discovery. This should be made clear if we ask what is the purposeof the philosopher of science in investigating the issue of discovery. When philosophers of science look for themethod of scientific discovery, they look for something which reflects the nature of science per se, rather than foa method in a specific area of science, which is derived from the specific knowledge of that field. Philosopherswho are interested in the epistemology of science or in the rationality of science would not be interested in

methods of solving Schroedinger's equation or in methods of discovering the chemical composition of a materialThis is the territory of the scientists themselves. Philosophers would rather be interested in the general methodsreflecting rational ways of knowledge acquisition.

In this respect, the interest of the philosopher of science may differ from the interest of AI scientists or techno-scientists. The latter are interested in finding a method which will assist them in solving their specific problems.Both AI scientists and techno-scientists would benefit from the discovery of a general method of scientificdiscovery. However, since they are not interested in epistemology or in the nature of science per se, they would bhappy if they had area-specific methods of solving problems. This is exactly what is provided in AI by expertsystems. The heuristic method of experts for solving problems in a specific field is programmed into an expertsystem which directs problem-solving in that area. The shortcoming of such an approach is that every research arneeds a different expert system. Thus, the interest of the AI scientists in general methods or in the general

characteristics of expert systems is only pragmatic. By the same token, the techno-scientists do not need a generamethod of discovery since they are interested only in solving their specific problems.

Nevertheless, in recent years many philosophers of science have been interested in content-specific methods of discovery. This trend has emerged as







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a result of the unsuccessful attempts to find a universal logic of discovery. It can be seen also as an influence of Aresearch in heuristic-search and expert systems on the methodology of science. This trend is presented sometimesas one of the characteristics of the new approaches to the philosophy of science. The exclusive engagement withcontent-neutral logic or method of science is sometimes even claimed to be a mistake of traditional philosophy oscience. Methodological pluralism is one of the popular slogans of these approaches. However, if the philosopher

of science deals with area-specific methods, he abandons the task of investigating the nature of science and treatsscience as an ad hoc grouping of different areas of research. The only thing which might then be left tocharacterize science is its subject matter, i.e. the study of nature, human society, etc. However, this will not be adistinctive characterization, since science deals with almost everything in the world, natural, human and artificialIt is thus the method or the nature of science, rather than the subject matter, which distinguishes science from othfields of knowledge or other human activities.

Furthermore, the scientists engaged in active research are the best experts in investigating their area-specificmethods. Thus, no room is left for the philosopher or methodologist of science except perhaps in recording andexplaining these methods for the benefit of philosophers or historians, and at most in systematizing them. This byitself would not justify their occupation as philosophers of science. Only when they study the area-specific methoin order to find their common features, might their investigations be of genuine interest and value. But if they stuthe common features, they are engaged again in the general methodology of science, i.e. in the study of thescientific method.

(e) A general function of a method of discovering theories, and scientific method in general, is making the growthof scientific knowledge minimally continuous. No discovery of theory comes "out of the blue." Any new idea,theory or a solution of a problem should bear some relationship to the present body of knowledge and thestandards of knowledge. The present body of knowledge and the standards of truth, plausibility or goodexplanation set up restrictions on the product of discovery. Even a revolutionary discovery is subject to someminimal restrictions. Thus, the method of discovery should supply a link between the old and the new. Otherwisewe would not be entitled to talk about "growth" or "progress."

(f) Finally, a more fundamental question should be raised: Do we expect the method of discovery to be normativeprescriptive or descriptive? If our methodology of discovery is derived from an a priori philosophical theory, suc

as an epistemological theory or theory of rationality in the traditional sense, then it would attribute a normativeimport to method. Thus, a partial answer to this question will be given in the next section, when I will discusspossible sources of method. A fuller answer will be given in Chapter 4.







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2.1.3 The Origin of Method

Now that we know what functions a method of discovery is supposed to accomplish, we may ask what might guius in finding the method(s) of discovery.

(a) Logical Sources Deductive logic may help us in exposing the logical content of our statements but will not he

us in arriving at novel truths. Inductive logic and theories dealing with probable and plausible inference will helpus in devising methods of discovering plausible statements. Efficient methods may be derived from decisiontheory. All these are formal theories dealing with inference and choice and do not refer to the content of theproduct of discovery.

(b) Epistemological Sources Philosophical views from which the methodology of discovery may be derived are otwo kinds: epistemological and metaphysical. Since discovery has an epistemic dimension, philosophical theoriesof knowledge may direct the philosopher of science to construct a methodology of scientific discovery. Empiricistheories of knowledge might recommend, for example, constructing theories from observational statements;whatever "constructing from" means. Certain versions of empiricism would have implications for the product of discovery. For example, they might recommend avoiding the usage of theoretical statements which cannot bereduced to observational statements. They might requirein the spirit of logical positivismusing only statements

which are verifiable. The Popperian theory of knowledge would recommend trying "bold" falsifiable conjectures.Verifiability and falsifiability are examples of criteria which would have implications for the method of discovering a law of nature or for constructing a theory. They would specify what kinds of building blocks areallowed for constructing the product of discovery. Thus, when the scientist tries to construct a theory, he wouldhave in mind these criteria as part of the method of discovery; they would partially guide him in the process of discovery. He would intentionally try to construct his theory in such a way that the product will obey these criteria

(c) Metaphysical Sources Metaphysical beliefs about the nature and the structure of the world will haveimplications for the process of hypothesizing laws and theories as well as for the acceptance or rejection of hypotheses. Those who believe that the structure of the world must be simple, would try to construct the simplestpossible laws and theories. For example, the metaphysical principle that nature always chooses the simplest pathguided the medieval scholar Robert Grosseteste to suggest a law relating the angle of refraction and the angle of

incidence for a light ray entering into a denser medium. His argument was the following. The law of reflectionstates that the







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angle of reflection equals the angle of incidence. Hence, the ratio 1:1 was already "occupied." The next availablerelation in the order of simplicity was 1:2. Hence, he suggested the law that the angle of refraction equals one halof the angle of incidence. Another medieval scholar, William of Ockham, adopted another principle, known as"Ockham's Razor," which stated that our theories about nature should be simple. Nature itself is God's creation, anthere can be no rules restricting God in creating the world. We would say in our terminology that God does not

need method to guide him in inventing the world. We need rules for guiding us how to discover what God createHowever, theories about the world are our own inventions, so that we can demand of them to be simple. Amethodological rule implied by this principle would instruct us not to introduce more concepts in our theories thanare absolutely needed for explaining natural phenomena. Indeed, this principle is reflected in the first of Newton's"rules of reasoning in philosophy" which says: "We are to admit no more causes of natural things than such as arboth true and sufficient to explain their appearances" (Newton, ibid.). Thus, whereas Grosseteste's methodologicaprinciple originated from a metaphysical belief, a belief about the nature of nature, Ockham's principle of conceptual parsimony may be related to an epistemological view, a view about the means of acquiring knowledgabout nature.

The birth of modern science is signified by another metaphysical belief, the Pythagorean outlook, which wasadopted by Copernicus, Kepler and Galileo. The Pythagorean view was expressed by Galileo's famous dictum thathe book of nature is written in the language of mathematics. Both Copernicus and Kepler believed thatmathematical harmony is what really exists behind the appearances. Kepler was guided in discovering his laws bythe Pythagorean mathematical models.

Moreover, the very fact that scientists look for laws of nature and theories is based on the metaphysical belief inthe uniformity of nature or the belief that natural phenomena are governed by laws. This is the most fundamentalmetaphysical belief behind natural science. This heuristic principle paved the way to the discovery of the laws ofnature. It stands, therefore, implicitly at the basis of every method of discovery in science. The principle of theuniformity of nature posits one of the major goals of science: to find the laws and invariable relations governingnatural phenomena. The method of discovery should, therefore, tell us something about how to find the regularitiand laws of nature. For example, methods of generating inductive generalizations tell us something about this tas

Descartes aimed at deriving the laws of nature from metaphysical principles. Modern science does not adopt this

approach. Metaphysical views sometimes serve as heuristics for discovery. For example, we may view atomism a metaphysical view which modern science inherited from Greek philosophy. Atomism guided chemists andphysicists in discovering some of the most suc-







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cessful theories of matter. Thus, we may treat metaphysics as supplying science with a repertoire of ideas for constructing theories. However, metaphysics does not dictate to science what ideas to adopt; it is science whichselects the ideas from the metaphysical repertoire, according to the methodological criteria prevailing in science.

Thus, metaphysical views affect scientific discovery on two levels: (1) On the subject matter level, views about thstructure of the world (e.g., atomsim) supply optional ideas for generating discoveries (e.g., composite models). (2On the methodological level, general views about the structure of reality (e.g., the uniformity of nature) yielddefinite prescriptions for generating the method of discovery (e.g. inductive methods).

(d) Learning from the History of Science Another source for method is the history of science. Scientists adoptmethods and models which prove successful. According to Kuhn, normal science is characterized, among all elseby certain models which everyone tries to imitate. Thus, science learns from its past, in the domain of method aswell as in the domain of content.

(e) Naturalistic Theories of Science If we treat science and scientific discovery as a natural phenomenon, or as paof the domain dealt with by science, various theories of science itself will guide us in constructing our methodology. For example, psychology may aid us in devising methods of learning from experience and for acquiring new knowledge. Sociology will be a natural source for method if we believe that science has an essenti

social dimension. And so is anthropology, in case we view science as a cultural phenomenon.

2.2 Inferring and Reconstructing

Now we come to the methods of discovery themselves. I will sometimes use the word method in a broad sense torefer also to the logic, procedure, heuristics or strategy of discovery.

If a method is effective, it means that scientific discovery is not entirely a matter of chance, intuition or a flash ofinsight. However, we can hope that a method-guided discovery and creativity do not exclude each other. We canorder all kinds of methods according to the degree of novelty they can produce. By deductive inference, we canonly expose information hidden in the premises of an argument. It, therefore, does not produce new information. may only produce epistemic or psychological novelty. Inductive inference produces empirical generalizations

which contain new information, e.g. about the future or the past. A method of generating a theory should generatnovel concepts and ideas, whereas the most radical methods, if they exist at all, may generate new conceptualsystems or new world pictures.







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2.2.1 Reasoning vs. Creativity

There is a widespread belief that scientists reason to their products of discovery. According to this view, the highesteem given to the discoverer is due to his bright arguments and sharp reasoning. In this respect, the physicist orthe biologist would not differ from the logician, the mathematician or the philosopher. If great discoveries innatural science were due to chance or unexplicable intuition, the proponent of this view may ask, why should thediscoverer be more admired than the successful gambler or the fortune teller. In general, we do not attribute anintellectual or cognitive ability to someone who is a successful gambler. Extrasensory powers, and evenextraordinary memory or computational ability, are treated as interesting phenomena rather than as intellectualattributes. Human faculties which draw our esteem are only those to which we hold the individual possessing themresponsible. A high power of reasoning is among these faculties, whereas luck or extrasensory perception, and evextraordinary memory or computational ability, are not. The latter would belong to the category of interesting or curious phenomena. We would not admire, for example, someone who can mechanically repeat everything hehears or reads; a parrot or a machine can do the job. In this respect, intuition is on the borderline between cognitiability and a natural phenomenon. Sometimes we may admire a scientist having an intuition in the sense of havinan insight which is not derived from reasoning and which cannot be fully communicated. However, this notion ointuition is too general and too vague. It only indicates that we cannot explain how a scientist arrived at hisunderstanding or at his discovery.

However, a power of reasoning is not the only thing required of a scientist. It seems that discoverers in scienceneed to have some additional capability. One can reason well within a given framework of thought, i.e. within agiven world picture or a given conceptual system, employing given methods, tools or patterns of problem solvingand research. Reasoning in these cases consists of devising arguments within the existing framework. This requiran analytical power rather than imagination and creativity. However, in many important cases problems are solveand understanding is gained by going beyond the existing framework, e.g. by generalizing or abstracting, bymaking connections or analogies with other phenomena or domains or by inventing new concepts or new methodand tools of investigation. In order to depart from the existing system, imagination and creativity are needed; thediscoverer does not only play with the existing concepts, ideas and tools, he also invents new ones. Thus, creativiis necessary for arriving at new ideas and systems. The power of reasoning is needed for deriving the implicationof the new ideas and for finding the relations they have with existing ideas. Creativity, as well as analytic

capability, is essential to the processes of problem-solving and theory-construction.







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Creativity, no less than analytical power, draws our high esteem, since unlike luck or extrasensory perception, weregard the individual possessing this faculty responsible for it. Unlike extraordinary memory, computing capabilitor psychic powers, creativity involves making judgments and decisions. It seems that creativity is a naturalendowment which cannot be learned or instructed by method. In Part II I will discuss theories of creativity whichmight help us in cultivating this natural talent. We have already encountered one possible mechanism described b

Poincaré. It consists of generating combinations of ideas and selecting the good ones. Poincaré pointed out thatgenerating new combinations or new ideas is a trivial and valueless task. However, creativity does not merelyinvolve combinatorical capability or a wild imagination or association. The creative act involves finding or constructing a new combination which is useful and fruitful, which solves a problem or explains some phenomenand which "no one has thought about before." Poincaré's view is that the discoverer's subconscious process of selection emits ideas which are already preadapted so that the remaining task is a relatively easy task of consciously selecting the final idea which is the product of discovery. This view would diminish the value of theconscious act of discovery and the discoverer would not be regarded as fully responsible for the discoveries heproduces; rather he would be treated as a human discovery-generating machine.

2.2.2 Discovery as Inference or Reasoning

If the discoverer arrives at, or generates, his discovery via a process of inference, it means that he arrives at his

object or product of discovery in the first place by arguing to it. There are cases where the scientist tries to justifythe product of discovery by arguing to it only after he has arrived at the discovery by chance, by error or as a resof a process which does not seem to support the product of discovery. This might be done when the discoverer wants to make sure that the product is supported by some firm argument, or when the discoverer wants to persuadthe scientific community to accept his product, which otherwise will not be considered to be a discovery. But thethe inference does not fulfill the role of method of discovery, i.e. a method of arriving at a discovery, exposing orgenetrating it in the first place.

If the product of discovery is arrived at, or generated, by proper inferencei.e. by applying established rules of inference and starting from reliable premisesthe product is born justified due to the inference procedure. In thiscase, the inference has both generative and justificatory functions, yielding a full-blown discovery. In the casewhere it seems that no proper inference was made in generating the product, an inference is brought in to carry ou

the justificatory role. Let us make a comparison with mathematical discovery. The mathematician may arrive at atheorem, by empirical investigations (in case of a theorem in Euclidean geometry, for example), by intuition or bychance,







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believing he has exposed or generated a true theorem. However, in order to convince himself and others in thetruth of the theorem he has to discover a proof. Only after the theorem is proved, is the discovery completed.

However, unlike in the case of mathematical discovery, in natural science the context of justification has anempirical dimension. An empirical generalization or an explanatory hypothesis would not be declared a discoveryunless it undergoes some empirical tests. The reason for this is that in these cases the process of discovery isampliative or content-increasing. In other words, the product of discovery contains information which was notcontained in, or logically implied by, the state of knowledge before the discovery was made. Thus, in naturalscience, unlike in mathematics, a proper ampliative inference cannot by itself generate a discovery. This was notthe situation before the advent of modern natural science. Some philosophers of nature believed they could derivethe laws of nature from general metaphysical principles. Even some of the founders of modern science stillbelieved in this. Descartes, who witnessed the birth of modern science and was himself an active scientist, soughto discover the laws of nature by deductively inferring them from some "a priori" or "necessary" truths. Thejustification of the laws thus derived was, therefore, granted, without any need for a posteriori, or empirical,testing. To be sure, an important role was given to observation in Descartes' scientific method; in order to derive statement about a particular event or phenomenon, one has to include among the premises statements describingthe observed initial conditions of the particular process, as well as statements expressing laws of nature. Howeverthese predictions could not serve as tests for the laws of nature since the latter drew their validity from the a priortruths from which they were derived.

Thus, in viewing the whole process of discovery in natural science as an inference, we must include the aposteriori tests as part of the process of inference. This can be done by adding the data obtained through the teststhe premises of the inference. Yet, the a posteriori part of the inference will not be generational. Hence, if wemaintain that the discoverer argues to his discovery, then one part of the argument is generational and the other pis justificatory. Both parts are essential to the discovery process. The justificatory part in turn divides into a pre-testing ("a priori") part and an a posteriori part.

In his discovery-generating argument, the discoverer starts with a set of premises p and ends up with the discoverd as a conclusion. The process can be symbolized as pÞd, or "p entails d." Thus, in order to represent the processdiscovery as an inference we have to specify what are the premises p and what are the inference rules. If in a

particular historical case of scientific discovery, we think we know what were the premises and what were theinference rules but we see that d cannot be derived from p, we have two options. The first option is to conclude ththe inference view of discovery is refuted by this case. The second option is to adopt what may be called an ad hstrat-







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egy. If we believe in the inference paradigm, we can do what the scientist would do in the occasion of adisagreement between his paradigm and the observed phenomena. If, for example, the Newtonian astronomer observes a deviation of a planet's orbit from what is predicted by his established theory, his explanatory paradigmwould guide him to look for a yet unobserved heavenly body which might have caused the deviation. Similarly, wwould introduce ad hoc modifications or auxiliary hypotheses in the description of the phenomenon, i.e.in our

casein the description of the inference. The logician of science has at his disposal an arsenal of possible ad hocmaneuvers. In most cases, scientists do not specify all their assumptions or presuppositions. Thus, the logician ofscience who believes that the scientist argued to his discovery, might hypothesize that there were some missing osuppressed premises which were not explicitly expressed by the discoverer or that were overlooked inreconstructing the process of discovery. Another option at his disposal is to introduce modified or new rules of inference which, as he might claim, were effective in the process of discovery; these rules are rarely statedexplicitly and in most cases one has to conjecture what rules might have been implicitly used. Of course, in ordeto be acceptable, these ad hoc hypotheses should yield an appropriate explanation of the process of discoveryaccording to the logician's standards of explanation. For example, the ad hoc modifications might be required to brelatively simple and fruitful in explaining additonal cases of discovery. Thus, the task of the logician of science ito solve a problem within the framework of his inference-paradigm. If we adopt the Kuhnian conception of normscience, we might say that this is the same situation which confronts every scientist when confined to normal

science activity.Now, let us review the different inference procedures at our disposal.

(a) Discovery by Deductive Inference As a first candidate for our logic of discovery we might start with deductivlogic. On the scale of novelty-generating methods, deductive inference will be situated at the bottom, since itcannot generate new information at all. As we have seen, it can serve as a method of exposing the information-content hidden in our set of premises p. To be sure, this kind of exposure is a very important kind of discovery.For example, the prediction of the existence of electromagnetic waves was exposed in Maxwell's equations by thikind of inference, without generating any new information which was not contained in the equations. However, thdiscovery of Maxwell's equations themselves was a generational discovery. Historically, the above discovery byexposure was part of the process of discovering Maxwell's theory. Indeed, every generational discovery of a theoris followed by the derivation of predictions which confirm the theory and which are discoveries in their own righ

An example of deducing a law of nature from known premises is Newton's deduction of the inverse square law ogravity from Kepler's Third Law of planetary motion (see Zahar 1983).







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Deductive logic played a central role in the Cartesian system where in the deductive hierarchy of statements thelaws of nature were inferred from the a priori principles. However, even if the laws of nature were theorems in adeductive system, deductive logic will not suffice for discovering them. Theorems can be generated by successiveapplications of the rules of deductive inference, beginning with the postulates or the axioms of the system.However, if we apply the rules at random, without the guide of some method or heuristic, or with the guide of an

unsuitable heuristic, we would very rarely hit upon an interesting or useful theorem. Pythagoras's theorem, for example, was first discovered empirically (for specific triangles), with the guidance of land measurementexperience, and only later was a proof discovered within Euclidean geometry. As we have noted, a method of discovery should make discovery efficient. Deductive logic unaided by heuristic principles is not an efficient wayfor discovering interesting theorems. Actually, it is not a method at all! Indeed, someone who knows all thenecessary rules for deducing a given theorem in Euclidean geometry would not necessarily discover the theorem he does not have the right intuition or creative power. And he might not discover the proof of the theorem whenthe theorem is given. Indeed, the discovery of a deductive proof is not a deductive process. One has to find or evinvent the steps in the proof, applying the various rules in an appropriate order. It is no different from the situatiowhich faces the chess player who knows all the rules of the game but does not know how to overcome hisopponent. It is again a heuristic search or an intuitive or creative act. Thus, intuition, creativity and heuristicprinciples are sometimes needed for making discoveries through deductive inference, although these are discover

by exposure which do not produce new information. Thus, discovering the logical content of p is not entirelyanalogous to the opening of a closed box and exposing its content. It is more like digging for gold or drilling for oil. The availability of oil drilling techniques are only a necessary condition for finding oil. The oil driller shouldconsult the geologist in order to enhance the chances of finding oil. The "premise" here is earth, but the oil drillernot interested in most of the material he finds hidden in the ground; everything, except oil, found hidden in theground is indeed there, but is useless for him. If p is true, everything deduced from p is true, but most of the truthshidden in p are uninteresting, and therefore are not discoveries.

(b) Discovery by Inductive Inference The next candidate for the logic of discovery is inductive logic which is anampliative logic. The conclusion "all ravens are black" goes, indeed, beyond the premises which describe all raveobserved until now, none of which has been non-black. Thus, induction by enumeration is a novelty-generatingrule of inference. However, since in a "valid" novelty-generating argument it is possible that the conclusion is falwhile the premises are true, we may not use the term valid for describing a







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good inductive argument. Such an argument may be better termed inductively ''strong" rather than inductively"valid." Hence, the truth of the premises does not guarantee the truth of the conclusion; it only endows theconclusion high probability, whatever this means.

(c) Retroductive or Abductive Inference Inductive inference can generate empirical generalizations, but notexplanatory theories (in the traditional sense of statements). Newton's theory of universal gravitation cannot beinductively inferred from the data on planetary motion and even not from Kepler's Laws. Although it can be showthat the inverse square law can be deductively derived from the Third Law, Newtonian theory includes novelconcepts beyond the mathematical relation expressed by the law; for example, it includes the concept of mass andit applies to all material bodies, not only to the Solar System. Induction by enumeration or inductive generalizatiocannot lead from the data on gas behavior, or from the empirical gas laws, to the kinetic theory of gases. For onething, the explanatory theory employs new concepts which do not appear in the pre-theoretical vocabulary. Theseconcepts cannot be generated by inductive generalization, since every predicate appearing in the conclusion of aninductive argument must appear in the premises. It is customary to think that the first stage in a development of ascience is the descriptive or phenomenological stage, which is concerned with inductive or empiricalgeneralizations, and the next stage is the stage of theoretical explanation, which involves conceptual growth. Thussince there seems to be a method governing scientific discovery on the phenomenological level, i.e. the inductivemethod, it is tempting to look for a method which may govern scientific discovery on the theoretical-explanatorylevel. This method should lead from the data, the phenomena or the empirical generalizations requiring explanatioto the theory which will explain them. The name "retroduction" which is sometimes given to such a method maygive the impression that it belongs to the same family of scientific methods or logics to which deduction andinduction belong. However, beyond the hope of finding such a method, which presumably looks like an inferencnothing substantial is standing behind the name. Although the content of this method is very poor, yet another titlwas given to it by Charles Peirce: "abduction." On the scale of novelty-generating methods, retroduction, or abduction, is situated above induction, since it is supposed to generate not only new information but also novelconcepts.

Retroduction (RD) can be compared to the hypothetico-deductive (HD) method (see, for example, Hanson 1958,52-3). According to the HD scheme, observational consequences are deductively derived from premises containina given hypothesis h and a known set of initial conditions i. If the predictions agree with the observations, the

hypothesis is said to be confirmed. The notion of confirmation is not a logical notion. Indeed, if from h and i onededuces a







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statement which turns out to be true (or at least accepted as true), then logically, one can say nothing about thetruth value of h even if i is accepted as true. In practice, scientists accept theories as discoveries in case they yieldsuccessful predictions, especially if these are far-reaching or unexpected predictions. By the notion of confirmatiophilosophers of science try to explicate this intuitive notion.

Since confirmation is an essential part of the process of discovery, HD can be viewed as a non-generational part the method of discovery. The RD method is supposed to complement the HD method, as the method of generatinthe explanatory hypothesis. The HD method provides a confirmation to h according to the following inferencepattern:

HD: (1) h predicts an unexpected phenomenon e (e is entailed by h&i).(2) e agrees with observation.(3) Therefore, h is highly confirmed.

We assume here that the statement i expressing the initial conditions is true or highly confirmed.

In a somewhat analogous fashion, we may represent RD according to the following pattern:

RD: (1)e is a surprising phenomenon.(2)e would be explained as a matter of fact if h were an accepted theory (e would be entailed by

h&i).(3)Therefore there is reason to accept h as an explanatory theory.

The above RD scheme is a paraphrase of Peirce's theory of retroduction. One difference between his scheme andthe above scheme is that the latter refers to an accepted theory rather than to a true theory.

In the HD scheme, h is given (i is accepted as true), whereas e is discovered as a result of testing the prediction.

(Note that the HD scheme also accommodates the case where e is already known but no one thought that h mightaccount for it). The discovery of e contributes to the acceptance of h itself as a discovery. The discovery of e is bno means a straightforward matter. One may have to devise sophisticated experiments, the results of which mayhave to be analyzed and interpreted. For example, the SU (3) symmetry of hadrons was confirmed following thediscovery of the W- particle. However, the latter discovery was an enterprise involving highly sophisticatedexperiments, and the interpretation of the results required elaborate theoretical and statistical analysis.

In the RD scheme, e is known, whereas h is discovered as a result of trying to explain e. The scheme does notinstruct us how to generate h. Hence, it







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is not an inference which generates an explanatory theory. As in the HD method, h appears in the premises of theinference pattern. Indeed, Peirce's RD theory was criticised for not being a method of discovery at all. Behind thicriticism lurked the attitude that a method of discovering a theory is supposed to generate the theory. RD entersinto the discovery game only after h is already available. At most, RD may help us in selecting a hypothesis amoseveral available candidates. Yet, the process of selection is no less important than the process of generation, as

Poincaré would view it. Moreover, sometimes it is the main stage in the process of discovery. Indeed, the processof discovery is in many cases a process of finding the theory among a limited number of available hypotheses. Inaddition, RD is a method of confirming h and confirmation is part of the process of discovery. Both HD and RDschemes can be viewed as inferences from observed phenomena to the confirmation or acceptance of a hypothesThus, they are ampliative inference schemes which are extensions of inductive inference. In fact, Mary Hesse(1974, 98) refers to HD as a rule of inductive inference.

2.2.3 The Quest for Certainty or: How Ampliative Inference Can Be Converted into Deductive Inference

Inductive inference causes many difficulties for the philosopher. It can be justified only on pains of circularity. It not clear what a "valid," strong or good inductive argument is. We base our inference on the data collected untilnow, but the future is open. So the question is how the conclusion of an inductive argument is supported by theavailable evidence. All attempts to construct inductive logics failed. The tension between reason and novelty-

generation is evident here. If we want to arrest novelty-generation in an inference pattern, the price paid is that thinference becomes somewhat awkward. If we want, at all cost, to represent discovery as inference, we must eitheconclude that discovery is non-creative or maintain that discovery has inferential as well as creative dimensions.The first option is counterintuitive. Thus, what is left for us to do is to isolate the inferential component of discovery, pinpointing the places where the creative component might enter into the process.

If the discovery process carries us beyond what is already known or implied by what is known, we do not have adeductive support for the discovery. However, we cannot start from secured premises anyway, since no knowledgis absolutely warranted. Hence, even deductive inference would not secure truth; it will necessarily lead to truthonly if we start from true premises. It is, therefore, equally insecure to proceed via deductive or via inductiveinference. We must rely on some assumptions. We may assume that certain statements, such as observationalstatements, are true, reliable, or warranted, and then proceed via deductive inference. We may further assume that

inductive inference is reliable and proceed also by inductive inference. Both







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ways are risky, whereas in the latter case we are taking more risk since we rely on one more assumption. Howevewithout taking risks we can make no epistemic profit. With the rise of modern science, the no-risk policy, or thequest for certainty, was recommended by an influential philosopher such as Descartes. Rationality was equated tocautiousness. However, Cartesian philosophy did not reflect the nature of modern science. The rise of modernscience is characterized by boldness and imagination. Modern philosophy of science only in recent decades has

freed itself from the formula of rationality equals no imagination, no creativity and no risk, a formula which wascarried to its extreme by the movement of logical positivism.

Scientific rationality consists perhaps of proper dosages of both risky and "responsible" behavior. Responsibilityimplies that we start with conventional methods. The first step may, therefore, be to see what we can gain fromdeductive inference. We may try to see whether inductive inference can be reduced to deductive inference. If weare deductivists and we want to bridge the inferential gap in a seemingly inductive argument, we may adopt theabove mentioned ad hoc strategy, representing inductive inference as an incomplete deductive inference. Thebridging might be provided by a statement which would express the principle on which we base our inductiveinference. If we could formulate such a statement, we could include it as a premise in every inductive inference,thus converting the inference into a deductive inference.

It is sometimes said that the principle of the uniformity of nature is the principle which underlies our inductive

inference. But how shall we express this principle in a statement? The statement "nature is uniform" is not veryinformative. It is an a posteriori "rule" which describes the fact that science has discovered regularities or uniformities in nature. It does not tell us in advance what are the uniformities which are projectible, i.e. whichcorrespond to natural laws. We can identify the phenomena and the properties in our field of observation in aninfinite number of ways. The regularities we find depend on the manner we make this identification. Thus, theregularities we find depend on our point of view.

Instead of inserting a world-embracing principle among the premises, we might insert more modest principles. Wmight start our argument, for example, from the premises stating that all the large number of observed objectsidentified as P's have been found to have the property Q, with no exception. We will then deductively infer thestatement "all P are Q" if we added the following premise expressing the principle of induction by enumeration:

IE: "for any X and Y, if a large number of objects identified as X's are observed to have a property Y, and nocounter-example is observed, then all X are Y."

This is how we might make an inductive inference to appear as a deductive inference. The method is to take theinductive inference rule and convert it into







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a premise. If we had satisfactory inductive rules of inference, then inserting these rules among the premises of inductive inference would indeed amount to deductive inference. However, IE by itself is useless. It is effective asa rule of discovery only in case we have a definite set of natural kinds by which we can categorize the phenomenBut this is exactly where the creative component of discovery enters. In our ordinary experience, we categorize tobjects and phenomena in the world by using concepts which are available in our natural language. However, this

conceptual system is not appropriate for describing the phenomena investigated by modern science. Scientists,therefore, have to invent new conceptual systems, referring to new natural kinds, such as the quantum mechanicalfield-theoretical or cognitive-theoretical conceptual systems. Discovering the new natural kinds is outside thescope of inductive inference.

Alan Musgrave employs a similar strategy for converting a variety of ampliative arguments into deductivearguments. He uses bridging principles which are not universal (such as IE) but domain-specific (Musgrave 1988His method is to find the suppressed assumptions in the discovery-arguments expounded by scientists. Indeed,there are always common presuppositions and beliefs shared by the members of the relevant community which,therefore, need not be explicitly stated in scientific discourse. Musgrave adopts this strategy in order to convince that there is a method of scientific discovery, applied to all kinds of discoveries, and it is no less than deductivelogic. Let us follow his examples.

The first example is from everyday experience. When we want to put forward a hypothesis about the color of emeralds, we do not guess blindly and test our guesses one by one. This would be a very inefficient way toproceed. We might guess that emeralds have no common color. We might hypothesize that in the winter they areyellow and in the summer their upper part is blue and lower part is black. Popper tells us in his Logic of ScientifiDiscovery that there is no logic of scientific discovery and recommends making bold conjectures. However, if theis no method restricting our imagination, we would be wasting our time and might arrive at no discovery. Inpractice we start with an assumption or a premise such as p1: "all emeralds have some common color." Thisassumption is not world-embracing; it is rather domain-specific. In this manner, Musgrave avoids the abovementioned problem of inventing the natural kinds; he considers a situation where the natural kinds are alreadyavailable. The premise p1 can be reduced to a deductive conclusion of the following more general domain-specifpremise p'1: "emeralds belong to a family of kinds of precious stones whose members have a common color." Ofcourse, there is no justification for p1 or p'1. But the point is that an argument starts with some assumptions and it

rationality (according to the traditional interpretation) resides in its validity rather than in the justification of thepremises. Another premise, p2, which is drawn from observation, says that some particular emeralds are green. Wthus have the following argument:







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p1: All emeralds have some common color.

p2: A particular emerald is green.

Therefore C: All emeralds are green.

Thus, the "inductive" argument whose premises are statements referring to observed green emeralds and whoseconclusion is C is in fact a deductive argument with a missing premise p1, for example.

The conclusion C does not constitute a novelty with respect to the premises p1 and p2. Consequently, C is certainrelative to the premises. The uncertain element, however, did not disappear; it was pushed to the premise p1. Thuswe have here a method of discovery based on deductive logic. This method presupposes that the discoverer startswith some working hypotheses which are plausible and established in his mind.

Not much novelty is generated by the above inference, since the novelty-generating premise p1 or p'1 is a verycommon kind of assumption which proved successful in ordinary experience. Creativity will be needed when weturn to an unfamiliar environment, occupied with unfamiliar objects and phenomena. Creativity is needed in orderto find what natural kinds are there, on which inductive generalizations, such as p1, can be made. No wonder thatinductive inference such as in the above example, which presupposes a stable set of natural kinds, can be "dresseup" as deductive inference. This is a process of discovery by exposure. We have p1 in mind and then a discoveryof a single green emerald amounts to the discovery of the generalization "all emeralds are green."

Musgrave's second example is of generating a hypothesis about the relationship between two measurable quantitiL and M. We make the general hypothesis (derived from considerations such as Grosseteste's principle of thesimplicity of nature) that the relation is a linear one. Then we make two pairs of measurements and find out theexact relation. The deductive argument might be, for example, the following:

q1: L and M are lineary related, i.e.L=a M + b for some real numbers a and b.

q2: When M=0 then L=3.

q3: When M=1 then L=5.Therefore, L=2M + 3.

Here we discover a specific relation by making a general mathematical hypothesis. Again, this is not a novelty-generating discovery, since the major working hypothesis is included in the premises.

Encouraged by his success in "dressing up" inductive arguments as deductive ones in cases where no novelty wasgenerated and no creativity was needed, he turns to another example which is a typical generational discovery.







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The example is Ernest Rutherford's discovery of the structure of the atom. Unlike the first two examples, thisdiscovery resulted in a great novelty. Since this example is instructive I will describe it in some more detail.

Rutherford Discovering the Emptiness of the Atom 5 In 1908 Hans Geiger used the scintillation method to measurthe scattering of alpha particles. When a thin sheet of metal was inserted between the slit which limited the beamand a phosphorescent screen, scintillations corresponding to particles deflected from their straight paths wereobserved. It was found that the number of particles deflected through a given angle decreased rapidly as the angleincreased. It was found also that the number of deflections increased with the thickness of the foil, and the heaviewas the deflecting atom, the greater was the deviating effect.

Later, young Ernest Marsden joined and, at the suggestion of Rutherford, searched for alpha particles scatteredthrough a large angle. Rutherford later recalled in a lecture he gave:

I may tell you in confidence that I did not believe that there would be, since we knew that the alpha particlewas a very fast massive particle, with a great deal of energy, and you could show that if the scattering wasdue to the accumulated effect of a number of small scatterings the chance of an alpha particle beingscattered backwards was very small. Then I remember two or three days later Geiger coming to me in greatexcitement and saying, 'We have been able to get some of the alpha particles coming backwards.'...It was

quite the most incredible event that has ever happened to me in my life. It was almost as incredible as if youfired a 15-inch shell at a piece of tissue paper and it came back and hit you. (Ibid., 111)

Why had the results struck him as so strange? The model of billiard balls which worked so well in the kinetictheory of gases led to the belief that atoms are behaving like solid particles. Rutherford expressed this belief asfollows: "I was brought up to look at the atom as nice hard fellow, red or gray in colour, according to taste" (ibid115). However, the picture changed as a result of the experiments made with cathod rays. Philipp Lenard made avery small hole in the side of the Crooks tube covered with aluminum foil thin enough to let through the electron(the cathod rays). He found that swift electrons passed through comparably thick foil. Calculations, which relied othe known number of atoms in a given volume and the approximate size of the atom, showed that only if theelectrons passed freely through the body of atoms in the foil could the observed penetration be possible. This ledLenard to conjecture that atoms were made of particles which he called dynamids. Each dynamid con-







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sisted of an electron closely associate with a unit of positive charge, being as a whole neutral. He showed that thedynamids of solid platinum must occupy no more than 10-9 of its volume.

Later, J. J. Thomson suggested his "plum pudding" model of the atom. According to this model, the atom was asphere of positive electricity, with electrons imbedded in it, arranged in a series of concentric rings in one plane.This structure corresponded roughly to the periodic chemical properties.

The work of Geiger and Marsden was completed in 1909. Only early in 1911 Rutherford found an explanation tothe results. He came to the conclusion that each of the large-angle deflections of the alpha particles must be due ta single collision with a very small and very massive charged particle, the nucleus.

Musgrave's Reconstruction The whole process is encapsulated by Musgrave in the following argument:

A1: The same (similar) effects have the same (similar) causes.

A2: Atoms and the Solar System behave in the same "dense and diffuse" way with respect to bodies entering them[i.e. most bodies entering them pass straight through them, but a few collide violently with them].

A3: The Solar System "dense and diffuse" behavior is explained by its structure, a relatively small but massive

body orbited by much lighter bodies.

Therefore C: Atoms are structurally similar to the Solar System...

Here Musgrave "dresses up" an argument by analogy, which is considered to be an inductive argument, as adeductive argument. This is a typical example of how a process of discovery can be reconstructed without givingus a clue about the method which could have guided the discoverer to his discovery before he made the discoveryA2 is the crucial premise in the above so-called inventive argument. However, it is a premise which can be statedonly after the main step was made in the process of arriving at the hypothesis. The fact from which the discovererstarted here, and which he wanted to explain, was the "dense and diffuse" behavior of atoms with respect to bodientering them. So whence sprung the idea about the Solar System into the argument? Everything is similar toeverything in some respect. The problem is to find a fruitful similarity. The fruitful similarity between the atomic

structure and the structure of the Solar System was the creative step in Rutherford's discovery. The reconstructor already knew this. Had we not already known about Rutherford's discovery, we would not know how to reproducit here, since we are not presented with any method to direct us in how to arrive at this particular model. There arinfinitely many systems in the physical world. There were many systems which had been successfully describedand explained by







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physical models and theories before Rutherford's discovery. The discoverer's task was to find the particular systemwhich supplied the successful explanation. Hitting upon the similarity between the atomic structure and theplanetary system was the creative act in the discovery and no method is given to us as to how to make such adiscovery. Probably there is no method for arriving at such a creative association. It took Rutherford more than ayear to free himself from his entrenched belief and to hit upon the idea.

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In the above examples, the method is applied to a marginal step in the process of discovery. The general methodhere is to convert the discovery to deductive inference where the premises contain certain hypotheses which bridgthe inferential gap. But the creative step in the discovery is generating these hypotheses. When these have beendiscovered, the process indeed does not generate any novelty, it just exposes information implied by the premises

2.2.4 The Hierarchy of Material Logics

Another ad hoc strategy referred to by Musgrave is to convert deductive inference with a suppressed premise intoan inference with "material" rules of inference. Here, the inference rules are domain-specific. For example, in theinference: "gravitons are massless, therefore gravitons move with the velocity of light," the missing premise p is:"massless particles move with the velocity of light.'' Since the last statement is common knowledge amongphysicists, there is no need to mention it. In a community of experts there are many suppressed assumptions, somof which are tacit. This is the reason why the novice in the field would not understand many discussions betweenthe experts. It is, therefore, tempting to categorize these suppressed premises as material rules of inference of theif-then form. The rule of inference r corresponding to the above missing premise p would be: "From 'x is amassless particle,' infer 'x moves with the velocity of light.'" Unlike deductive rules of inference, which are formaor content-free, material rules of inference are content-dependent. They are, therefore, ampliative, or content-increasing. However, these rules are not content-increasing relative to the background knowledge of the expert whhas internalized them. Thus, in the material logic of the physicists the inferential rule r is not ampliative relative tothe background knowledge of the community which uses this logic; relative to this background knowledge, if the

antecedent in the rule r is true, the consequent must be true.Musgrave raises the following possible objection to material logic. Logic is not an empirical science so that thematerial rules of inference, which seem to be loaded with empirical content, cannot constitute a logic. He indicat







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that the distinction between empirical and logical matters belongs to the heritage of logical positivism. However,according to logical positivism, the "heuristic principles" on which the material rules of inference are based are nfactual statements; some of the heuristic principles are empirical generalizations which would hardly pass thecriteria of factuality. Heuristic principles which are theoretical statements definitely would not count by the logicpositivists as factual. Some heuristic principles are metaphysical principles, which are the antithesis of factual

statements. Since the heuristic principles are not falsifiable, they would also not be considered empirical accordinto the Popperian tradition, which regards only falsifiable statements as empirical.

I propose to order domain-specific logics, or community-dependent logics, in a hierarchical order. The mostgeneral logic is deductive logic. It is the logical theory underlying the inferential practice of the broadest humancommunity whose members can communicate with each other. We might view even this domain as domain-specific, although the domain is the widest domain of knowledge and experience shared by human beings. It isspecific to humankind. Perhaps the corresponding logic of intelligent creatures which evolved in another galaxywould be different. Inductive logic is also shared by all human beings. However, a precondition for applying it isthe identification of the natural kinds on which inductive projections can be made. Some of the natural kinds willbe common to all human beings. In more specific domains of experience, one should learn to identify the naturalkinds. Hence, although the inference rules are not domain-specific, their application is domain-specific.

A community sharing a narrower domain of specific experience may develop an inferential practice whoseunderlying rules of inference are specific to that domain. For example, every community of professionals or experts may have such a logic. This includes the whole scientific community or narrower scientific communities,such as the community of biologists or physicists or even of a narrower community such as that of particlephysicists. Those who do not belong to a particular logic community would have difficulties in communicatingwith members of the community. A non-scientist will not understand scientific discourse. And this is not onlybecause of the lack of knowledge, but mainly because of the suppressed premises or the material rules of inferencCommunication is difficult even between different subdisciplines. We know, for example, that physicists who wato contribute to molecular biology, have difficulties in communicating with the molecular biologists, although theknow everything they have to know in the field. The reason for this is that they were brought up in a different logcommunity. This idea may remind us of the Kuhnian notion of incommensurability between different paradigms.But the similarity is only partial since the "rule" is that people belonging to a narrower logic-community share all

the wider logics in the hierarchy. Thus, there is a one-way communication along the hierarchy, whereas nocommunication is possible across paradigms.







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Every community of experts has tacit knowledge and implicit assumptions underlying their discourse. Some of thsuppressed heuristic principles are included in the tacit knowledge and are not listed anywhere. They are rather acquired by the novice via the process of apprenticeship. We encounter the same situation in ordinary reasoning.Deductive logic explicates the rules behind ordinary inferential practice. However, ordinary people who areparticipating in this practice do not learn deductive logic. They acquire the tacit rules by an apprenticeship-like

process, when they learn their mother tongue and when they participate in ordinary discourse. Perhaps the abilityreason correctly is genetically determined. However, the main point is that for the non-logician, the inference ruleare tacit. Thus, when we identify suppressed assumptions which are regularly employed in arguments made in agiven community, we have one option of treating them as missing premises, and another option of treating them arepresenting material rules of inference.

Noretta Koertge makes the distinction between inference patterns which are legitimate in all possible worlds andthose which are heuristically successful in our world. She maintains that the first kind of inference patterns arelogical whereas the second kind of inferences are rational (Nickles 1980, 48). Presumably, logical implies rationabut not vice versa. According to the above view about the hierarchy of material logics, logical (read deductive)inferences are valid in all the possible worlds which can be comprehended by us, whereas heuristically successfulinference patterns are rational in their specific domains. Thus, rationality in this sense is domain-specific.Rationality in Koertge's sense is categorical, referring to "our world" without distinguishing different domains of experience. According to my approach, rationality is domain-specific. In any given domain, it is manifested by thmaterial logic of that domain, whereas categorical rationality is manifested by obeying the rules of the materiallogic governing the discourse in the widest domain of human experience, i.e. deductive logic.

In Chapter 4, I will develop an approach according to which the justification of the rules of deductive logic residin part in their being an explication of the rules underlying our inferential practice. Furthermore, logical theory wbe treated there as a theory in natural science. In this sense, even deductive logic is empirical, as every theory innatural science is. This approach might, therefore, be suitable for treating the hierarchy of material logics, whichcorrespond to the inferential practice of the different communities.

If we identify the material logic underlying the discourse of a specific scientific community, we might understandtheir reasoning patterns. We would be, therefore, able to decide whether and how they reason in arriving at their

hypotheses. However, we have to be cautious in distinguishing between generative and justificatory reasoning.







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2.2.5 The Discovery Machine

There are discovery processes which are carried out effectively by scientists and which can be reconstructed or simulated in simple cases by a real machine. On the other hand, there are discoveries which are more effectivelycarried out by a computer rather than by a human agent, e.g. recursive computational processes of discovery.

Machines can create novelty; new statements, information and formulas can be generated at random or by aheuristic-guided process. We might simulate, for example, natural selection by generating quasi-randomhypotheses, some of which will be selected according to predesigned criteria. The selected hypothesis will be aproduct of a creative act. For example, the machine may be fed by data and the task will be to find a mathematicfunction which will be best fitted to the data. The programmer may design a hypotheses-generator which willgenerate mathematical functions quasi-randomially. The first function which will be "caught up" as providing a fwhich falls under the predetermined range of variation tolerance will be the product of the process. If, asevolutionary epistemology postulates, science simulates the process of natural selection, there is no reason for excluding the possibility of simulating scientific discovery which transcends an established paradigm by a machiwhich simulates natural selection.

In general, we can equip the machine with criteria and procedures for deciding whether a novel product is useful

or achieves a predesigned goal, such as explaining some phenomena or solving a certain problem. We can evenequip the machine with a repertoire of problems which the machine will scan, with different selection proceduresso that it can decide what product solves what problem. In this manner, the machine may even generate solutionsfor unexpected problems. We may also devise the program in such a way that the criteria of selection will changefollowing the ongoing experience of the machine. Of course, to translate this possibility "in principle" to a workinsystem which makes judgments and which learns from experience is achievable, for the time being only for a verrestricted range of problems.

Imagine a discovery machine programmed by a programmer who knows everything known to physicists justbefore Planck solved the problem of blackbody radiation. We can supply the machine with the major ideas andmethods employed by physicists during the last half of the nineteenth century. One of these ideas, was the idea ofcalculating certain integrals in thermodynamics by equating the energy with integer multiples of a certain fixed

quantity, and then calculating the limit where this quantity goes to zero. This was a computational deviceemployed by Boltzmann. After despairing from solving the problem in other ways, Planck used this trick withoutgoing to the limit (see Chapter 5). How can we instruct the machine to find this idea or method? The programmeshould be wise enough to include Boltzmann's trick in the repertoire of ideas







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supplied to the machine, and then the machine should hit upon the idea and generate the required modification ofthe idea. The probability for this is very small. The probability will increase only if the programmer will narrow tsearch field. But in order to do this in the right direction, the programmer should already know how the discoverywas made by Planck.

At the present, the computer lacks an important dimension of the discovery process: the social dimension. We caenvisage a network of intercommunicating computers replicating the scientific community, including itsinstitutions, but for the time being, this belongs to the realm of science fiction. When this "vision" is fulfilled, wewill not be far from replacing human society by a computer society. The social dynamics of the scientificcommunity includes the judgments made by each scientist on whom he can rely or what weight can be given toeach of his colleagues. In such a process, rhetoric, personal influence and other faculties which (for the time beingcannot be mechanized play major roles. In view of the cooperative or historical dimension of discovery, themachine cannot be as creative as science is. Until the social dynamics or a historical process of discovery can besimulated by a machine, a major dimension of creativity will be missing in machine discovery. No hardwaresupplemented by any amount of software can replace the whole scientific community. All major discussions of machine discovery have ignored this aspect of discovery.

Yet, although the discovery machine cannot simulate the whole process of discovery, it might aid scientists in the

decisions and acts at particular stages of the process. A scientist is aided by calculators and computers in hiscalculations and data processing. The discovery machine might be another aid to the scientist in case a decisionwhich involves taking into account too many factors should be made.

Let us follow a specific example, presented by Herbert Simon (1987). Simon describes a computer program,BACON, developed in collaboration with Pat Langley, Gary Bradshaw and Jan Zytkow. Let us see how thisprogram discovers Kepler's Third Law of planetary motion. BACON is supplied with data on the periods of revolution (P) and the distances (D) of the planets from the sun. It is applied to the data according to the followinrecursive heuristic rule: REC: "If two variables co-vary, introduce their ratio as a new variable; if they varyinversely, introduce their product as a new variable and test it for constancy." With this rule, BACON first noticethat P and D co-vary. It thus computes P/D, which is found not to be invariant. Then REC is applied recursively the new variables P/D and D, which are found to co-vary. Their ratio P/D2 is found not to be invariant. Then

BACON finds that P/D2 vary inversely with P/D, so it multiplies them, obtaining P2D3, which is found to beconstant. The constancy of this variable is indeed an expression of Kepler's Third Law.

In this example, the discovery machine is doing only part of the job. The first important step is choosing thevariables P and D. The choice of the "right"







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variables sometimes constitutes the main step in the discovery, after which the regularity is immediately exposed In this particular case the programmer and Kepler alike did not have many available alternatives to choose from;and D were inherited from the prevailing scientific tradition of circular planetary motion. This situation where thevariables are available and no new ones are introduced is typical for a discovery which does not involve theconstruction of a new explanatory theory in which novel theoretical terms are introduced.

Simon claims that the new variables constructed from the original ones are theoretical terms. However, neither P/Dnor P/D2 can be treated as genuine theoretical terms. The reason for this is that a theoretical term should appear apart of a unifying or an explanatory theory. Both variables do not have any role in any theory; they are formed juas steps in the computation. They do not refer to any physical phenomenon or to a significant physical magnitudeThey do not appear in any law of nature. In the process of developing a theory, many expressions are obtainedalong the way. We would not call all these expressions "theoretical terms."

Yet, Simon mentions another variable which is created in the process and which corresponds to a new theoreticalconcept . By using the word concept , he presumably means that this is a theoretical term having a physicalsignificance. The new concept, which he calls "gravitational mass," is created in the following way. In a givenplanetary system, the magnitude P2D3 has a constant value K. If BACON is applied to different planetary systemsuch as the satellites of Neptune, different values of K will be obtained. In this way, the concept of gravitational

mass will be discovered, since in Newton's theory of universal gravitation, K is proportional to the gravitationalmass of the central body in the planetary system. This seems to be a creative discovery since a new physicalmagnitude appears to have been discovered here. However, this is only an apparent discover. If a machine or aplaying child who are supplied with two physical magnitudes such as P and D, would form from them a newcombination which turns out to play a role in a theory such as Newton's mechanics, it by no means means that thechild or the machine discovered the new concept. Had BACON discovered a theory or a law, in whichgravitational mass plays a significant role, could we say it discovered the new concept. The concept of gravitationmass has more content in it than just being related to a certain combination of P and D. BACON plays the role of"Kepler machine" but not of a ''Newton machine."

The process carried out by BACON is not an inference. Indeed, the recursive heuristic rule (REC) programmed inBACON is not equivalent to a rule or a set of rules of deductive or inductive inference. Nevertheless, REC guide

a discovery process which is not generational but is a process of exposure; it exposes a regularity hidden in thedata. If a mechanical procedure generates discoveries in a data-driven process, it means that the heuristic rules aregood ones. Thus, an important step of the discovery is the discovery of the







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heuristic rules. BACON is by itself a product of a creative discovery or an invention. It is a machine which whenfed with the right data, discovers regularities hidden in it. We can make the analogy with an observationalinstrument. For example, after the telescope was invented or discovered, Jupiter's moons were discovered byexposure. The telescope magnifies our sensual capabilities whereas the heuristic-instructed machine amplifies oucapability of discovering regularities. A successful heuristic rule is, therefore, an instrument for the discovery of

regularities, just as the telescope is an instrument for observational discovery. Thus, in order to make significantdiscoveries by exposure, we sometimes have to discover first an appropriate instrument; the discovery of theexposing instrument is a generational discovery or an invention. If we look at the whole process of discovery inthese cases, it is not a pure discovery by exposure but a generational discovery which leads to discovery byexposure.

BACON is thus an example of how the machine can magnify our discovery capabilities. Thus, the computer mayhelp the human discoverer in the case of recursive procedure. The computer also magnifies our computationalcapabilities and data-processing capabilities. These are examples where the computer is an important device for tprocess of discovery. However, from this we cannot draw the sweeping conclusion that (in all, or even in most,cases) "discovery can be mechanized."

2.2.6 Theory-Construction and Research Programs

A typical pattern of theory-generation in a framework preserving setting is when the theory is constructedaccording to a general model, or a general heuristic principle, available in the field. For example, in Ptolemaicastronomy, there was only one basic explanatory model, the epicyclic model. Planetary motion was described interms of a given configuration of epicycles. When a planet was found to deviate from its prescribed circular motion, the heuristic rule would tell the astronomer to solve the problem by adding new epicycles in order tocomply with the principle of circular motion. Yet, the heuristic rule did not specify how to do this.

Another example of heuristic-guided theory-construction is the evolution of theories of the structure of matter since the nineteenth century which seems to have been guided by the Meyersonian heuristic principle. According this principle, theories of material changes, e.g. theories of chemistry, have to be constructed out of conserved"substances," or "material causes," such as atoms and fundamental particles, and conservation laws; the general

"recipe'' is that whenever some new phenomena do not obey the conservation laws, science has to look for newconserved substances and new conservation laws (Meyerson 1908). For example, Dalton's atomic theory, whichappeared at the beginning of the nineteenth century and which was completed by Avogadro,







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yielded a set of conserved substances, the atoms of the chemical elements, and a set of corresponding materialconservation laws which stated that the number of atoms of each element should remain constant throughoutmaterial changes. In 1896 Becquerel and Curie discovered the phenomenon of radioactivity which showed thatchemical elements are not conserved. Eventually, this phenomenon was explained with the emergence of newconserved substances, the nucleons and the electrons, and with the corresponding new conservation laws stating

that the number of nucleons and the number of electrons are conserved. These conservation laws were found to bviolated and the developments in the physics of particles and fields also followed the Meyersonian recipe (seeNe'eman 1983). We have here an example of a heuristic rule which is domain-specific and content-free. It isconfined to a specific domaintheories of material change. However, it does not specify the content of the conservsubstances and the material conservation laws. It is the task of the discoverer to invent them.

The above discovery pattern may be represented as a "semi-inference"; i.e. an inference, in which the inferencerules are replaced by the heuristic rules. The premises of such an argument include the new anomalous data.However, there may be more than one "conclusion" to the argument. The heuristic rules do not uniquely determinthe product of discovery. For example, the Meyersonian heuristic would leave the discoverer with more than onepossible explanatory hypothesis.

In general, in a framework-preserving discovery, the discoverer will have at his disposal a very limited number o

basic explanatory ideas or models; the prevailing world picture and background knowledge would narrow thenumber of possible or plausible explanatory models. Thus, in some cases, whenever the discoverer encountersproblems awaiting a solution, or phenomena awaiting explanation, he might not be required to construct a newtheory afresh, but only to adjust the general explanatory model available in the field to the explanandum. Whenthere are several explanatory models in the field, it sometimes becomes immediately evident what model is theappropriate one, or it is a matter of simple inference to determine which model will explain the phenomena; severobservational results plus the background knowledge uniquely determine the appropriate model among the smallnumber of models available. The process of discovery is then reduced to "induction by elimination": When we han hypotheses-candidates, n-1 of which are eliminated by observational or experimental results, the remaining nthhypothesis is declared a discovery. This is, in fact, a deductive inference conditional on the assumption that thereare only n possible hypotheses capable of explaining the explanandum. If we denote the hypotheses by hi, thebackground knowledge by B, and the conjunction of falsifying observational results by e, we can represent the

discovery argument by the following deductive pattern:







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p1: B entails (h1vh2v...vhn-1vhn).

p2: e entails (~h1&~h2 &...&~hn-1).

p3: e&B.

Therefore hn.

Due to premise p1, this is a proper inference and the product of discovery is unique. In the special case where n=or after n-2 hypotheses have been eliminated, e is a result of a so-called crucial experiment which serves to decidbetween the two competing hypotheses.

Next, let us consider the very common situation when we are already equipped with a theory T and a new piece odata e brings about a new theory T' which is a result of adjusting T to the new data. T', the product of discovery,may be regarded as a modified version of T. The process can be symbolized according to the following formula:

The heuristic HEU guides us in modifying the theory. Again, the product T' is not uniquely determined. Thisdiscovery pattern can be viewed as dynamic theory-construction, where we start with an initial hypothesis andmodify it in order to adjust it to the data. In the field of AI, such procedures are carried out for discoveringregularities and laws. In a typical experiment, a robot arm mixes chemical substances according to some initialhypothesis. Following the results obtained during the night, the hypothesis is changed in the following morningaccording to certain heuristic rules (Buchanan 1982). This is another example of a recursive procedure.

The RP pattern is typically a data-driven process; it is the new data which brings about the need for modifying T.The data-driven process of dynamically constructing a theory is very close to the notion of research program, or tthe notion of a dynamic theory (see Kantorovich 1979). The latter notion refers to a theory which is expanded andmodified from time to time in order to adjust it to new observational data. (This notion of dynamic theory shouldnot be confused with the ordinary notion referring to a theory dealing with dynamic phenomena; here it is meant

that the theory itself, rather than its subject matter, is dynamic.) In the process of adjustment and expansion, thetheory retains its name and identity and its central claims. Within the Popperian tradition the Lakatosian notion ofresearch program refers more or less to the same thing. A Lakatosian research program is a methodological entityit replaces the falsifiable theory as the fundamental unit for appraisal in science. A research program is a successiof falsifiable theories which is characterized by a theoretical hard core, which remains by convention unfalsifiableand unchangeable, by the methods of research and by the resources of theory building. The latter are referred to athe "positive heuristic" of the program.







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We may combine the notions of dynamic theory and research program by saying that a dynamic theory isdeveloped in the framework of a research program. The process of constructing and modifying the theory can beprogressive or degenerative, according to the amount of successful predictions it yields. Thus, the process of generation and evaluation goes hand in hand.

The difference between the notion of research program and the notion of dynamic theory is that the latter does nonecessarily contain a predetermined hard core. Lakatos assigns to the hard core those parts of the theory under evaluation which are protected from falsification whereas the so-called protective belt, consisting of those parts othe theory which undergo changes, includes the auxiliary assumptions and other "softer" components constructedaround the hard core. The fact that certain elements of the dynamic theory remain unchanged throughout theprocess might testify for their adequacy, but it does not necessarily mean that an explicit decision was made at thstart of the process to protect them from refutation (see also McMullin 1976).

Indeed, a dynamic theory is not identified by a hard core. In the case when a model stands behind the developingtheory, it is the basic idea or the basic picture underlying the model which characterizes the theory. This idea or picture is not fully expressed by statements. Hence, the dynamic theory is not a closed system. Rather it has openpoints. As we will see below, the so-called neutral analogy of the model supplies such open points. The basic ideor the basic picture regulates the development of the theory. It replaces both the Lakatosian hard core and the

positive heuristic. The model supplies the heuristic which guides scientists in developing the theory.

A dynamic theory cannot be falsified in a purely logical sense, but it can lose its viability when repeated ad hocattempts to protect it from clashes with observational data result in a degeneration of the research program. Aresearch program degenerates if it does not produce new predictions or if none of its prediction is successful. Sincthe Lakatosian methodology is an outgrowth of the falsificationist tradition, it treats a research program as asuccession of falsifiable theories, each of which is falsified in its turn and replaced by its successor, while the harcore remains untouched. In the notion of a dynamic theory, I depart from the falsificationalist tradition and talk about a theory as a dynamic entity that retains its identity while being realized by successive theory-versions; theidentity is established by the basic picture or ideas behind the theory.

A dynamic theory or a research program evolves within the framework of normal science or a paradigm. It is

developed within a certain conceptual system or world picture and relies on some background knowledge. Withinthis general framework, the research program intends to solve specific problems. This is done by introducing andevaluating a specific model or a set of ideas. Examples are the Bohr-Rutherford planetary model of the atom or thbilliard ball model of the kinetic theory of gases. Both the general world picture







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and the specific model contain tacit elements, intuitive ideas and metaphors, which are being verbalized, clearedup, explicated and formalized throughout the development of the research program. As Max Black put it, "everyscience must start with metaphor and ends with algebra; and perhaps without the metaphor there would never havbeen any algebra" (Black 1962, 242).

The process of "explication" or "clearing up" involves a continuous interaction of the theory with observationaldata. One may say that the basic ideas and metaphor from which the dynamic theory starts to develop graduallymaterialize into an explicit theory only through the interaction with observational data. The research program starwith the discovery of a basic model or idea which is initially formulated as the first version of the theory.Sometimes this first version is referred to as a "first approximation," or an "ideal" or ''naive" version of the theorsuch as the first version of Bohr's model of the hydrogen atom, which referred to circular electronic orbits. Theprocess continues to evolvethe theory is continuously constructed and reconstructedwhere further observationalinformation keeps it going, producing more and more advanced theory-versions which accommodate the flow of information. On the other hand, the process of testing the new versions of the theory generates more data. Thedevelopment of a dynamic theory is thus brought about by the interplay between the basic ideas or the model andthe observational information. This is a process where a metaphor or an idea "ends with algebra" or with anexplicit theory.

Let us examine what happens in the prototypical case when the development of a dynamic theory is guided by amodel. The first theory-version which is generated by the research program may be seen as a simplified or a crudversion of the model, where an analogy is made between elements of the object system and some elements of themodel, whereas other elements of the model are considered to have no analogy with elements of the system; thesecases are "positive" and "negative" analogies of the model, respectively, to use Mary Hesse's terminology (Hesse1966). Some elements of the model remain unutilized explicitly. These elements constitute the "neutral analogy,"which serves as a guide for modifying and further developing the theory. For example, Bohr's model described thhydrogen atom as consisting of a central positively charged nucleus encircled by a negatively charged electronwhich can occupy descrete energy-levels, each of which corresponds to a certain radius of revolution. Energycould be absorbed or emitted by the atom in the form of photons which carry energies equal to the differencebetween energy levels corresponding to electron jumps between different orbits. Thus, the central motion and theclassical laws governing this motion belonged to the positive analogy of the model. The classical laws of

electromagnetic radiation and features of the Solar System, such as the heat radiated by the sun, belonged to thenegative analogy. In hindsight, we can say that the rotation of a planet around its axis belonged to the neutralanalogy, which later was utilized to invent spin.







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This simple model explained some basic features of the hydrogen's spectrum. The naive theory had to be adjustedto further data, such as the fine and the hyperfine structure of the spectrum. Some of the new features of thespectrum were explained by new versions of the theory. In one of the new versions, the notion of spin wasintroduced. The heuristic principle which led to the suggestion of this hypothesis is the above mentioned neutralanalogy of planetary rotation around the axis, which, as a result, was converted from neutral analogy to positive

analogy.Thus, with the guidance of the model, the new data generate a succession of theory-versions, where at each step,more of the neutral analogy turns into positive or negative analogy. The neutral analogy serves as a source and asguide for developing the theory, and, therefore, it may be regarded as a heuristic which is derived from the originhypothesis. In Bohr's model, we see also that an initial negative analogy may become a positive analogy, ashappened to the circular orbits which became elliptic in the developmental stage of the model called the Bohr-Sommerfeld model. Due to the presence of the neutral analogy, the original hypothesis, i.e. the model minus theinitial negative analogy, cannot be described as an explicit statement. Only additional data and the imagination ofthe scientist will determine the fate of the neutral analogy in the subsequent development of theory. The scientist'simagination is inspired by the original hypothesis but not always in an unequivocal and explicit way. The variousassociations and metaphors which are evoked by the model cannot be analyzed by the logicist's tools in the way awell defined set of propositions can, e.g. by deducing testable predictions from it at the outset. The heuristic,derived from the neutral analogy plus relevant parts of the background knowledge, leaves more than one possibilifor modifying the theory. Thus, even if we have a relatively well defined model, we have to decide at each stagewhat to do with the neutral analogy, since the data do not dictate a unique way to proceed. Although we maysymbolize the growth of a dynamic theory by formula RP, it is not an algorithmic method of generating discoveryit only describes a pattern of discovery which leaves room for creativity and for unpredictable developments.

2.2.7 The Calculus of Plausibility: Logic of Pursuit

A logic of pursuit determines whether an already given hypothesis is plausible in view of our backgroundknowledge and beliefs, and thus, whether it is worth pursuing and testing. Norwood Russel Hanson is renown forproposing such a logic or method. He gives the example of Leverrier who hypothesized the existence of a planetVulcan in order to explain the deviation of Mercury's orbit from a perfect ellipse. Hanson reconstructs the reason

which led Leverrier to his suggestion as reasoning by analogy. The irregularities in Mercury's orbit are similar tothose in Uranus' orbit. The latter were successfully explained by







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hypothesizing the existence of Neptune. Therefore, it is reasonable to conjecture the existence of a new planet,Vulcan. This argument can either be represented as an inductive argument (by analogy), or as a deductiveargument (as Musgrave represents Rutherford's discovery). Again, as in Rutherford's example, to present thisargument as an hypothesis-generating argument would be a mistake, since, the argument is brought in after theanalogy is already given. The argument does not show how Leverrier arrived at the analogy. However, Hanson

does not claim that this argument is generational. He presents it as the reasons for suggesting the hypothesis. Theare not the reasons by which the hypothesis was generated; rather they are the reasons for choosing a particular hypothesis out of the hypotheses available to the investigator: "...many hypotheses flash through the investigator'smind only to be rejected on sight. Some are proposed for serious considerations, however, and with good reasons(Hanson 1958, 85). This reminds us again of Poincaré's claim about the subconscious process of generation andselection. Yet, in order that the process of selection will have chances to hit upon a successful hypothesis, Hansonwould have to adopt Poincaré's claim that the candidates which consciously appear in the discoverer's mind arealready products of subconscious selection. However, it would be more plausible to assume that in the historicalcontext in which Leverrier made his suggestion, perhaps this was the only hypothesis which came to his mind,following the success of the Neptune hypothesis.

Reason enters into the game after the hypothesis is created, whereas the act of creation is "a matter of psychologyThis does not diminish the value of reasoning if we adopt Poincaré's claim that the generation of ideas or hypotheses is valueless; selection or discernment is the crucial factor in the process. Thus, the reasons for suggesting a hypothesis are reasons for selecting or choosing the hypothesis from a set of already generatedhypotheses. Indeed, in many cases the discoverer describes the act of discovery as an act of finding the hypothesiHanson says: "Our concern has been not with giving physical explanations but with finding them" (ibid., 72). Theexpression "I found a solution" is sometimes used synonymously with ''I generated a solution." However, theliteral meaning, which refers to searching and selecting among preexisting candidates, may reflect the true natureof the process. This brings us back to the notion of discovering X as literally finding, or exposing, X. In view of what has been said in the last section, in cases when all candidate hypotheses are at hand, the logic of pursuit is alogic of selection and it is identical with the logic of arriving at the discovery. Thus, in these cases the distancebetween exposure and generation is not so big.

In cases when the investigator has one successful model by which he successfully solved a previous problem so

that when posed with a similar problem he immediately turns to this model, there is no need for selection or choicThus, Kepler conjectured that Jupiter's orbit is noncircular, following his discovery that Mars' orbit is noncircular and the similarity between the







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two cases. In other cases, the reasons for suggesting a hypothesis may be pragmatic: e.g. the availability of themodel, the familiarity with the model, the ease by which one can calculate with the model, etc. In Chapter 8, wheI discuss the role of tinkering in the evolution of science, a new light will be shed on the significance of thesekinds of pragmatic considerations.

Note that the above examples refer to reasons for suggesting a certain type or kind of hypothesis (rather than aparticular hypothesis), e.g. a hypothesis referring to the existence of a new planet, a noncircular planetary orbit oplanetary system kind of model. A particular hypothesis is generated by applying and adjusting the general kind omodel to the particular problem in question. Thus, the logic of pursuit is a logic for pursuing kinds of hypotheses .However, it was suggested by Hanson that plausibility depends not only on the content of the hypothesis, but alsoon the credentials of the person proposing it or on his rhetorical powers. In these cases, the logic of pursuit is notdirected only towards the kind of the proposed hypothesis. Only if we treat the origin of the hypothesis or themanner by which it was produced as characterizing a kind may we still treat the above case as a kind of hypothesis, e.g. the hypotheses proposed by X.

Hanson does not present us with a detailed logic of pursuit. Rather he gives us a programmatic picture. The reasofor suggesting a hypothesis or a kind of hypothesis are mainly reasons incurred by analogy or by considerations osimplicity. In fact, all these reasons amount to saying that the suggested hypothesis provides a potential explanatio

for the explanandum. Thus, if the hypothesis is confirmed, it would be accepted as an explanation. We have toremember that there is an unlimited number of hypotheses which can (deductively or statistically) entail a finitebody of data, while another necessary condition for an hypothesis to become an explanation, and, thus, a discoveis that it comply with the criteria of explanation. Hence, the good reasons for suggesting a hypothesis are thosereasons which indicate that the hypothesis complies with the criteria of explanation and with the already availabledata. Some of these criteria, such as fruitfulness, predictability and simplicity, are content-neutral. Other reasonsare content-dependent, for example, compliance with current established explanatory models and theories, or withthe scientific world picture.

Hanson has been accused, together with Peirce, for confusing the process of generating a hypothesis with the act the initial evaluation of an already given hypothesis. However, as we have seen, in cases where there are a limitenumber of ideas in the idea pool of the scientific community, the reasons which lead scientists to a hypothesis are

not generational; rather they are the reasons for selecting it from the pool, or finding it as a good candidate for explanation. These reasons also provide the initial evaluation of the hypothesis. Thus, Hanson's account of discovery is appropriate for describing a wide range of cases, where the hypothesis is drawn from a given ideapool. In other







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cases, where an entirely new and successful idea is created in the mind of the discoverer, Hanson's and Peirce'sschemes still provide a partial account of the process of discovery. The creation of a new idea might be explainedby Poincaré's hypothesis; a new idea is selected among many combinations of ideas which are formed in thediscoverer's mind. Again, according to this view, selection is the most important part of the process and this can described by the logic of pursuit.

The task of the logic or the method of pursuit is, therefore, to narrow the range of candidates. Without such amethod, we have an infinite number of hypotheses from which a given set of data can be deduced (given the initconditions). As I have stated above, not every statement from which the explanandum can be deduced, isconsidered to be an explanation. Thus, I adopt here the following conception of theoretical explanation: A theoryexplains the explanandum E only if the following two conditions are met: (1) E can be deduced from T, (possiblyin conjunction with some initial conditions or auxiliary assumptions), (2) T complies with the prevailing worldpicture, including the explanatory models which have proved successful, and with the criteria of explanation,including the requirement of predictability. Thus, even if the trajectory of a planet can be derived from a certainconfiguration of epicycles, this will not provide the contemporary astronomer with an explanation of why theplanet's trajectory is what it is, whereas it will be considered an explanation by the Ptolemaic astronomer, since itcomplies with his paradigm of explanation. Thus, the logic of pursuit accounts for condition (2). The confirmationof the hypothesis, according to this conception, depends on both pre-testing considerations, encapsulated incondition (2), and on a posteriori considerations of evidential support or successful testing.

The logic of pursuit purports to determine the degree of plausibility of a hypothesis before it is submitted for testsThe degree of plausibility of a hypothesis is determined, among other things, by the explanatory paradigm, by theprevailing world picture and by the previous successes of hypotheses of this kind. I will describe now such a logbased on a Bayesian model of probability. The model is very instructive for our purpose, since it treats plausibilitconsiderations in a manner which is modeled on logical inference. Hence, we can draw sharp conclusions from thmodel. This is a heuristic model. I do not claim that scientists actually calculate probabilities before they accept atheory for pursuit. The status of the model in relation to scientific practice is similar to the status of formal logicwith respect to ordinary reasoning, or ordinary inferential practice. In ordinary discourse, people do not formalizetheir arguments and they do not draw their conclusions by explicitly following the rules of propositional or predicate calculus. However, formal logic provides a good explication of our intuitive inferential practice. The

process of explication provides us with a formal system, based on a small number of axioms, which reconstructour intuitions in a clear and concise manner. If the explication is







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fruitful, we will reconstruct with it most of our intuitions, we will find out whether they are consistent and we mapredict some new rules of inference which might turn out to be insightful and useful. The rules which areexplicated by a simple and fruitful formal system are not justified in the traditional sense which seeks a priorijustification. However, the formal system summarizes our intuitions in a concise manner and lends them formalstrength. In Chapter 4, I shall discuss the concept of explication in some more depth.

The Bayesian model can be employed for explicating the notions of plausibility, evidential support andconfirmation. According to this model, the probability of a proposition is interpreted as a subjective probabilitywhich measures one's degree of belief in the proposition. The probability p(h,e) of a hypothesis h, conditional onthe evidence e, is a measure of the evidential support e lends to h, or the degree of confirmation of h, given that eis the total evidence relevant to h which has been accumulated until now. The degree of confirmation, which ischanging with the accumulated data e, will determine whether h will be accepted as a discovery. According toBayes' formula, this probability is a function of p(h), the prior probability of h, i.e. the probability of h before theevidence was brought into consideration, and p(e), the probability, or the degree of expectedness, of e before theevidence was observed. The prior probability determines whether the scientific community will accept h for pursuThe condition that p(h) will be above some minimal value thus corresponds to the above mentioned condition (2)for explanation. In the following, I will describe the model in some detail.

The fundamental entity in the model is the probability p(a) of a proposition a, given the background knowledge oinformation, whereas the conditional probability of a, given b, is defined for any pair of propositions a and b as

If the initial or prior probability of a hypothesis h at time t0 is p0 (h) and a new empirical evidence e is acquired time t1, such that p1 (e)=1, then according to the so-called dynamic assumption of the Bayesian model (see, for example, Hacking 1967, 314) the posterior probability, or the degree of confirmation, of h after e was observed i

The assumption is that when the only reason for changing the degree of belief from p0 to p1 is the observation or the acceptance of e, then a rational change should be represented by a conditionalization upon e. In other words,only the new evidence should affect our belief-change. This reflects an empiricist attitude. Bayes' formula, whichcan easily be derived from eq. (1), relates the prior and the posterior probabilities of h. (From now on, the timesubscripts will be omitted from the probability functions at t0):







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If we consider an observational statement e which is entailed by h, then p(e,h)=1 and we get the simpler formula

Eq. (4) applies to the case when e is predicted by h (given the background knowledge at t0 which includes theinitial conditions, etc.).

According to this model, we should be able to calculate in advance at t0 what our degree of belief in h will be,when we accept e as true as a result of observation. Theories of probability such as that of Keynes (1921) or Carnap in his earlier views (1950), attribute unique conditional probability p(h,e) to a given pair of statements hand e. These approaches do not leave room for any arbitrariness in the inductive inference from e to h which maybe caused by extra-evidential factors, such as metaphysical beliefs or aesthetic and simplicity criteria. In theBayesian model, the dependence on these factors enters through the subjective prior probabilities, whereas thedependence on empirical evidence enters through the dynamic assumption. The prior degrees of belief may vary

from one person to another but a rational person is ready to change his beliefs in accordance with the dynamicassumption. It is claimed by some Bayesians that under these conditions, if a hypothesis has non-zero prior probabilities, its posterior probabilities converge to 1 or 0 with an increasing amount of empirical evidence(Edwards, Lindman and Savage 1963).

The relations of entailment and contradiction correspond to special values of the quantity p(h,e). If and only if hcan be deduced from e, it is evident that p(h&e)=p(e) and consequently, as can be seen from eq. (2), p(h,e)=1.Indeed, if and only if h can be deduced from e, the truth of h is conditional upon the truth of e. Hence, if and onlif one believes in the truth of e, one should believe in the truth of h, i.e. he should give it probability 1. When hcontradicts e, then p(h,e)=0.

Now we can see how Bayes' model provides an explication of our intuitive notions of plausibility, confirmation oevidential support. When a hypothesis is proposed, its prior probability corresponds to its degree of plausibility. A

hypothesis h is plausible or implausible only if p(h)>1/2 or p(h)<1/2, respectively. There are factors determiningthe value of p(h) which are common to all or most members of the scientific community. The prior probabilitywould be high only if the following conditions were met: (1) h conforms to the general beliefs and world picture the scientific community, (2) h accords with the accepted standards of simplicity or aesthetic value. Another condition which may raise the prior probability of h is when hypotheses of its kind succeeded in the past in simildomains. Of course, all these factors might be judged differently by different members of the community so thatthe values of







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the prior probabilities will diverge. There may be additional factors related to the credibility of the person or thegroup who proposes the hypothesis. Hanson, for example, maintains that, other things being equal, the plausibilityof h would be higher if we have confidence in the scientist proposing it due to his successes in the past or becausof the status of leadership he enjoys in the community. Another factor is related to the way h is presented. Thisfactor belongs to the realm of rhetoric, which is by no means absent from scientific discourse.

The notion of "e confirms h" may be explicated by the conditions: p(h,e)>p(h). In the case when e is entailed by h(in conjunction with some initial conditions), we find from eq. (4) that when e is accepted as true, e would confirmh only if p(e)<1. This means that if e would be expected to be true before it was observed, then its observationwould not lead to the confirmation of h. Whereas if p(e) is small, or when e is unexpected, its observation wouldconfer a high degree of confirmation on h. This accords with the intuitions of scientists. Note that the latter intuition was not taken into account in devising the model. It is, therefore, a successful prediction of the modelwhich confers higher confirmation on the model itself. However, in this case, the confirmation of the model is notbrought about by a prediction of a methodological rule which was unexpected when the model was proposed; onthe contrary, the rule was intuitively accepted by many scientists. This is an example for the following rule of confirmation: A hypothesis is confirmed by an evidence which was known when the hypothesis was proposed, buwas not taken into account in constructing the hypothesis (see discussion of this rule in Chapter 3). This is indeedone of the weak points of the model, since it does not account for this rule of confirmation. We might, therefore,reject the model. However, if we have good reasons for believing in the model, we might try to modify it in order to accomodate the above intuitive rule.

We can draw additional conclusions from the Bayesian scheme, some of which accord with the intuitions of scientists. However, our interest in the logic of pursuit will lead us to investigate mainly the role played by theprior probability. The prior probability depends on three kinds of factors: those related to the hypothesis itself,those related to the process by which the hypothesis was generated and those related to the rhetoric of itspresentation. Traditional approaches, such as logical empiricism, would regard the first factor as dependent only oobjective standards and would deny any dependence on the second or the third factors. In the Bayesian scheme thconditionalization upon the evidence balances the latter factors. This balancing well reflects the practice of sciencwhere psychological factors are balanced by empirical evidence, but they are not totally dismissed. Metaphysicalinfluence is indispensible, since it enriches the idea-pool of the scientific community. Psychosociological factors

are important, since in their cooperative enterprise, scientists cannot give the same credit to everyone. Thus, theBayesian model explicates this delicate balancing between empirical and non-empirical factors.







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The moral we can draw from the above story is that the process of uncovering the secrets of nature is by no meansa straightforward mechanical process of pulling up some curtain. It is a very intricate process in whichpsychological, social, rhetorical and metaphysical machinery is involved as well as mathematical proofs and metereading. However, to complicate the situation, it should be noted that even elaborated mathematical proofs andsophisticated experiments sometimes have rhetorical power, which might divert scientists from the rational track.

For instance, the von Neumann proof regarding the impossibility of hidden-variable theories in quantum mechaniwas accepted by the scientific elite without thorough checking because of the sophistication of the mathematicalproof and because of the reputation of von Neumann as a brilliant mathematician. Only after many years was itshown that the proof assumed hidden-variables axioms which were not compatible with Bohm's hidden-variablemodel which was supposedly "refuted" by the "proof." The self-explanatory title of Trevor J. Pinch's article on thsubject is most appropriate to describe the situation: "What does a proof do if it does not prove?" (Krohn et al.1978, 171215).

2.2.8 Discovery as a Skill: The Invisible Logic

The trained scientist who has experience in his field will recognize and discover things which the layman will nobe able to recognize. Discovery may therefore be viewed as a skill. Since skill cannot be taught by giving a list oinstructions, discovery would remain in this case beyond the reach of method. No description or recipe can repla

the expert. This is evident from the practice of expert systems in AI. Computer scientists try to translate theexperience of the expert into a set of machine-oriented instructions. They try to watch or to interrogate the expertin order to draw sets of heuristic principles which might be translated into sets of instructions. However, at thepresent state of the art the success of this method is very limited. A physician, for example, may diagnose the kinof illness his patient has by watching him, by listening to his bodily sounds and by feeling or sensing his organs.Although there has been some success in mechanizing limited kinds of medical diagnostics, the most sophisticatesoftware cannot faithfully replicate this skill.

Terry Winograd and Fernando Flores (1987) show how Martin Heidegger's analysis may account for the limitatioof expert systems. Heidegger distinguishes a domain of action from a domain of description. In bringing tacitknowledge into action, we do it without being aware of the knowledge we employ. In the translation of action intdescription by an external observer, something is lost. An expert system is a description provided by an external

observer of the expert's action. Since the translation is incomplete, the expert system does not function properly inew situations. It is non-adaptable to new tasks, as the human experts is.







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Practical skills, such as riding a bicycle or baking a cake, are carried out by human beings almost "automatically,without paying attention to them; furthermore, when one tries to pay attention to the way he is carrying out thetask, the performance may be disturbed.

A skill involves making the right judgments and performing the proper acts in a given domain of practice. It isacquired by experience. Past experiences are not stored in the memory such that in performing a task one simplyrecalls them. Bo Goeranzorn and his colleagues studied the nature of human skill and how a skill may be affectedby the use of different technologies (Vaux 1990). In the framework of this study, a professional photographer describes his experience as follows: "all of these earlier memories and experiences that are stored away over theyears only partly penetrate my consciousness" (ibid., 57). Thus, the rules an expert follows in performing a task anot expressed by propositions; they are expressed directly in action. This view is in line with Heidegger'sobservations. It also agrees with Ludwig Wittgenstein's view on tacit knowledge according to which following arule does not mean following a set of instructions; it means doing something in a practical way (Wittgenstein1968). One acquires a skill through apprenticeship, by imitation and by non-verbal communication.

In the context of scientific discovery we may conclude that the skill and discerning power of the discoverer isrestricted to the domain in which he has acquired experience. Thus, a scientist may be a great discoverer in onescientific field but not in another. This may be related to the different material logics employed by different

scientific communities. As I have said, a material logic is mainly part of the tacit knowledge which governs thereasoning practice and action of a given community. Thus, part of the discerning power of a discoverer in scienceis drawn from the internalization of the tacit material rules of inference. There may be rules governing a skill, buonly the experienced expert can apply them correctly. For example, in devising a mathematical theory in physicsone might be guided by a rule of simplicity. But only the experienced theoretical physicist would know how toapply the rule in constructing a theory, in choosing one or in adjusting it to new observational data.

Transparency, Invisibility and Black Boxing The tacit knowledge which the scientist internalizes includes thepresuppositions and background theories which are taken for granted and shared by the members of the relevantresearch community. These presuppositions appear as suppressed premises in scientific discourse andargumentation. In this sense, they are "invisible" to the expert; from the expert vantage point they are "transparenThe expert who employs these presuppositions or suppressed premises does not "see" them; he considers them to

be ''self-evident," and he is not fully aware of them. This is the reason he has difficulties in explaining to the nonexpert what he is doing. Indeed, we encounter many cases in which an eminent scientist is considered to be a "bateacher."







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The notion of transparency has been used mainly in relation to the practice of using observational instruments (sesection 1.2). In this context, it refers to "the attribute an instrument possesses when it is treated as a reliabletransmitter of nature's messages" (Gooding et al. 1989, 3). After the scientist has acquired the skill of using aninstrument, the procedure of using it become transparent. Gooding et al. employ this notion when they describe thhistorical development of the practice of using instruments such as the glass prism or the telescope. The notions o

invisibility and transparency might refer as well to the usage of the most advanced experimental equipment, suchas fast electronic detection systems in particle physics, where a much more intricate practice is involved. Theprocess of establishing the reliability of the instrument is called by the above authors "black boxing." When aninstrument becomes black-boxed, it is treated as transparent and the information it conveys is treated as themessages of nature. The scientist treats the instrument as if it were an extension of his organs. Thus, when theparticle physicist looks at a bubble-chamber photograph he sees particle trajectories. When the instrumentationbecomes transparent, "only the phenomena remain" (ibid., 217) and the process of discovery becomes discovery bexposure, although the black-boxed procedure may be highly generational relative to everyday practice, or relativto the previous state of knowledge. Black-boxing converts discovery by generation into discovery by exposure.Thus, we may say that observation and discovery are skill-laden (Nickles 1980, 300). If we adopt Polanyi'sdistinction between focal and subsidiary awareness, we may say that the scientist has only a subsidiary awarenessof his practice in using the instrument. Only the phenomena remain under his focal awareness. When we use a too

for performing a certain task, we are focally aware of the task. We have only subsidiary awareness of the tool(Polanyi 1958, 55).

The notion of invisibility can be applied to the use of theoretical tools, as well. In constructing his theoreticalarguments, the scientist relies on suppressed premises or material rules of inference, which are invisible to him, inthe above sense. For the trained scientist these theoretical tools are transparent. The scientist treats them as if theywere part of his cognitive apparatus. In this sense, his theoretical argumentation looks sometimes like deductiveinference. Scientific argumentation is contaminated with suppressed premises. This is the reason why in manytypical cases, when the scientist attempts to solve a problem, he can choose among a very few hypotheses; he donot have to choose among the unlimited number of logically possible hypotheses. It is the invisible paradigmwhich narrows the range of possible solutions. The scientist who has internalized the presuppositions of theparadigm, takes them for granted. He is not focally aware of them.

Let us consider as an example the discovery of the planet Neptune. In view of Newtonian theory, the anomalies the motion of Uranus were explained by Adams and Leverrier by assuming the existence of an unknown







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planet, Neptune, perturbing Uranus' motion, besides the perturbations caused by Saturn. The assumption about thexistence of a perturbing planet was guided by the presupposition that the motion of a planet is only affected bygravitational forces due to the sun and other planets. This heuristic was not derived from Newtonian theory but wtacitly assumed. No one thought about other possibilities, such as the possible existence of other forces affectingplanetary motion besides gravitation, or a change in the law of gravitational force. The theoretical presupposition

and the guiding heuristic did not have any logical validity but they were parts of the prevailing paradigm. We cantherefore treat this presupposition as an invisible assumption which was employed as a missing premise in theinventive argument which led to the conjecture about the existence of Neptune. The problem regarding Uranus'motion was solved by calculating the position of Neptune on the basis of Newtonian theory and the availableastronomical data. Although the mathematical solution involved some guessing, Adam and Leverrier arrivedindependently at the same result since they relied on the same presupposition.

Thus, whenever a theoretical assumption becomes established, it becomes transparent. Sometimes a presuppositiois so entrenched that a revolutionary move is required to replace it, as in the example of Rutherford who "wasbrought up to look at the atom as nice hard fellow, red or gray in colour..." Sometimes it is so established that thescientist is using it without being aware of alternative paths, as was the case of Herbert Simon who was not awareof the possibility of using different variables in reconstructing Kepler's problem. The totality of presuppositions,methods and tools which are transparent may be viewed as the prism through which the scientist sees the world.Some of these are the material rules of inference which determine the community-specific logic. The notions of transparency, invisibility and black-boxing enable us in certain cases to view generational discovery as inferenceor exposure. Yet, the process of discovering a new (material or conceptual) tool is a creative discovery. As we haobserved in section 1.4, this process amounts to discovering a new communication channel with nature. When thenew channel becomes transparent, the skilled discoverer treats it as a tool for exposing new aspects of reality.







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Chapter 3Why Did Traditional Philosophy Of Science Ignore Discovery?

3.1 The Distinction between the Context of Discovery and the Context of Justification

The distinction between the context of discovery and the context of justification (D-J distinction) is one of thecornerstones of logical empiricism. This is one of the weak points of traditional philosophy of science, which hasprovided one of the major reasons for ignoring discovery.

3.1.1 John Herschel's Distinction: Consequentialism

The context of discovery refers to the actual processes leading to a new idea, and the context of justification refeto the ways in which we evaluate the new idea. John Herschel was the precursor of the modern distinction betweethe two contexts. He departs from Baconian inductivism according to which we arrive at laws and theories byapplying inductive rules on observations. Herschel maintains that there is a second way to arrive at laws andtheoriesby creative hypothesizing. He gives the example of Ampere's theory of electromagnetism (Herschel 1830

2023). Ampere explained the attraction and repulsion between magnets by the existence of circulating electriccurrents within the magnets. The empirical laws of electricity and magnetism known at that time could be arrivedat by applying inductive rules on observations of electric and magnetic phenomena. However, Ampere could notarrive at the theory of circulating currents by applying inductive rules on these empirical laws. He had to apply hicreative imagination when he made the association between the magnetic phenomena and the phenomena of attraction and repulsion between electric currents. Herschel maintains that this creative process is not governed byrules. Had Ampere arrived at his theory by inductive inference, the process of generating the theory would conferpartial justi-







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fication on the product. However, the actual process of generating the theory was irrelevant to justification. Theconfirmation or justification of the theory would come only as a result of testing its predictions.

Here we encounter a clear distinction between two different approaches to justification which are labeled by LarrLaudan (1978) as " generationism" and "consequentialism." The generationist claims that theories can beestablished, or justified, only by showing that they can be derived from observations. In fact, we can generalize thnotion: an idea or a theory is generationistically justified by showing that it can be derived from established"premises," may they be observations, first principles or established theoretical foundations. Thus, according togenerationism, a hypothesis is justified in either of two cases: first, if it was generated in fact by derivation fromestablished premises, second, if it can be so derived, i.e. by "rational reconstruction'' of the process of discovery.In the latter case, the role of justification is to justify a hypothesis in case we have arrived at it without explicitlytaking into account all logical steps leading to it as a conclusion of a valid argument, or without establishing theconsistency of the idea with the rest of our system of beliefs. The act of justification in this case literally meansthat we try to justify an idea or to argue for it. This notion of justification is thus similar to that of a proof. Nickle(1987) gives the name "discoverability" to this criterion of justification. A discoverable hypothesis, i.e. ahypothesis which can be derived from what we already know, is justified. Generationism is therefore very close tthe inference view of discovery. The proper way to derive a discovery is by valid inference. If the discoverer hasarrived at his hypothesis by accident he has to show that it is discoverable by rationally reconstructing the processi.e. by proving the hypothesis.

The consequentialist claims that theories are tested only with respect to the success of their predictions. Thehypothetico-deductivists belong to this category. If we talk about evaluation, rather than justification, we caninclude also Popper in this category, since a theory is refuted by its false predictions, irrespective of the manner iwhich we arrived at it. Using this terminology, Herschel is a consequentialist; he maintains that there is no way to"prove" a theory (which is not an inductive generalization) or to derive it from secure premises. So that it can beconfirmed only by the success of its predictions.

According to the generationist interpretation, we argue to a hypothesis we propose and we are, therefore, entirelyresponsible for it; if it turns out to be inconsistent with the known facts or with some of our other beliefs, or if weargued for it fallaciously, we are to be blamed for making a mistake. This interpretation reflects a rationalist

attitude. However, in proposing a hypothesis about the world, it is not enough to show that it is consistent with ouother beliefs. We also have to show its empirical adequacy, i.e. that its predictions agree with observations. If thedo not, we should not be blamed for making a mistake, as Popper, for example, implies when he says that scienti"learn







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from their mistakes" when their hypotheses are refuted. When our conjectural law of nature or theory is refuted bobservation, our position is closer to that of the unlucky gambler rather than to that of someone who makes alogical mistake. The view that a refuted hypothesis constitutes a mistake is a remnant of the inference view of discovery; we argue to our hypotheses and if the argument is invalid it means that we have made a logical mistakYet, even if we do not make a logical mistake, our hypothesis may still not be empirically adequate; our system o

beliefs may be perfectly consistent but empirically false. Consequentialism accounts for this situation. We cannotderive a theory from secured premises. We can only confirm it by testing its predictions. The requirement that thetheory should be consistent with our other relevant beliefs is only a necessary condition.

3.1.2 Reichenbach's D-J Thesis: Generationism

The modern logicist version of the D-J distinction was introduced by Hans Reichenbach (1938). In addition to theirrelevance of the actual process of discovery or generation to justification, this version also implies that the task epistemology and philosophy of science is to deal only with the context of justification, whereas the context of discovery is left to psychology, which can deal with the actual processes of thinking. It should be noted thatHerschel did not exclude the context of discovery from the domain of the occupation of the philosophy of sciencsince he believed that some laws are arrived at by induction, which is rule-governed. The following passagesummarizes Reichenbach's thesis:

Epistemology does not regard the processes of thinking in their actual occurrences; this task is entirely leftto psychology. What epistemology intends is to construct thinking processes in a way in which they oughtto occur if they are to be ranged in a consistent system; or to construct justifiable sets of operations whichcan be intercalated between the starting-point and the issue of the thought-processes, replacing the realintermediate links. (Ibid., 5)

Thus, epistemology is prescriptive (this is indicated by the usage of the word ought ) by virtue of its logical force,whereas psychology would describe the actual ways we arrive at ideas. We may add also sociology, anthropologyand even biology to the descriptive sciences which can deal with discovery. According to this view, Poincaré'shypothesis about the subconscious processes of discovery or the social processes leading to discovery (which wilbe discussed in Chapter 7) should be treated by psychology and sociology; they are not a subject for the

philosophy of science.

In the above quotation, Reichenbach refers to justification by logical







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reconstruction, rather than to empirical confirmation. Thus, unlike Herschel, he is a generationist, rather than aconsequentialist. However, in contemporary discussions on the D-J issue with respect to hypotheses about theworld, the term justification is used also with the consequentialist interpretation, referring to the empiricalconfirmation of the hypothesis. Logic still plays a central role in this wider interpretation: the new observationalresults should bear some logical relation with the hypothesis in question.

There are three theses built into the D-J distinction: (a) that there is a sharp line separating the two contexts, (b) thonly the context of justification is amenable to logical analysis and (c) that descriptive science, such as psychologis irrelevant to the context of justification. Thus, the context of discovery can be dealt with by descriptive sciencewhereas the context of justification is prescriptive or normative. The proponents of this view maintain that thephilosophy of science is a logic of science which should, therefore, deal only with the context of justification. Thmost important consequence is: (d) information regarding the context of discovery is irrelevant to justification.There are two reasons for this: first, the context of discovery is a-logical and, therefore, it does not have epistemicor justificatory force, second, justification is concerned with the final product of discovery which is a statement oa set of statements. Hence, it does not matter how the discoverer arrived at his product. Logic will give us thewhole information about its truth. Thus, logical empiricism regarded the study of the process of discovery as anempirical inquiry to be dealt with by empirical science. The only respectable engagement of the philosopher of science was considered to be the logical analysis of the products of scientific discovery.

There are two paradigmatic cases which seem to confirm the above thesis. The first is the discovery of amathematical theorem. One can arrive at a theorem intuitively, by a flash of insight, for instance. But the proof ismatter of a logical act and it does not depend on the way the discoverer hit upon the theorem. The second is the scalled chance discovery or an unintentional discovery. It would be implausible to claim that an unintentionalprocess of discovery is amenable to logical analysis and that the context of discovery is relevant in that case to thjustification.

It should be stressed that the so-called context of justification encompasses all kinds of evaluative implications foa hypothesis. These include, in addition to confirmation and acceptance, also disconfirmation and refutation. Thuthe term justification is somewhat misleading. Indeed, Karl Popper, who rejects justification and accepts refutatioonly, joins in on the claim that the context of discovery is irrelevant to the logic of science. This is one of the

cornerstones of his philosophy, expressed in The Logic of Scientific Discovery (which denies the existence of itssubject matter): "The question of how it happens that a new idea occurs to man...may be of great interest toempirical psychology; but it is irrelevant to the logical analysis of scientific knowledge"







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(Popper 1959, 31). The term context of evaluation may, therefore, be more appropriate than "context of justification."

Thus, according to the proponents of the D-J distinction, a philosophy of science is a logic of science and a logicof science is a logic of justification or evaluation. This is perhaps one of the major assumptions which has shapemost of the twentieth-century philosophy of science, which had been dominated by logical empiricism and itsoffspring.

3.2 Objections to the Distinction

3.2.1 Justification and Discovery are Inseparable

The most obvious objection to the D-J distinction is that the two contexts are inseparable; each context is"contaminated" with elements of the other. This is an objection to thesis (a) and, as a consequence, also to the oththree theses, which depend on the validity of the first one. The context of discovery is contaminated withjustification or evaluation. Indeed, as I have emphasized, evaluation is an integral part of the process of discoverysince an entity would be considered a discovery only if it was proved to be true, successful, a solution to aproblem, etc. In particular, if we refer to a theory, we would not say we discovered it unless we have confirmed i

In scientific practice, as we have observed, if a scientist proposes a theory and did not prove or confirm it, hewould not always be considered to be the discoverer of the theory even in case it was later proved or confirmed banother scientist. He would be credited only for participating in the process of discovery. By the act of confirmation, we discover that the theory is indeed a discovery. Moreover, sometimes we discover that an idea ortheory which was generated in an attempt to solve a different problem, solves our present problem. The act of discovery consists here of association and confirmation. These two acts may be simultaneous, especially if thediscovery is an eureka event. Indeed, many ideas pass through our minds without any notice. However, we make discovery when we see that a particular idea in this flux solves a certain problem. Poincaré would tell us thatdiscovery consists mainly of selection, which is an evaluative act. There is no shortage of ideas, but there is ashortage of successful ideas. Thus, we would not say that Democritus discovered atoms. Dalton did, since heprovided us with a confirmation of the conjecture in a particular context.

Let us consider the validity of the D-J distinction in the two kinds of discovery: exposure and generation. Indiscovery by exposure, the context of discovery mainly consists of justification. When, for example, we discover new star with a telescope, the act of discovery may be identical with the act of observation. If we are empiricists,who take observation to be a warrant for truth, the act of justification is thus identical with the act of discovery. Iwe deduce an interesting or unexpected conclusion from a set of accepted







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premises, such as a theory, we make a discovery by exposure. The act of discovery is identical here with the act odeductive inference. It is again identical with the act of justification. Thus, discovery and justification coincide.

In generational discovery, the process of generation may precede the act of confirmation. In this case, the theory iconstructed and then tested and confirmed. We can then separate the context of generation from the context of justification, rather than the context of discovery from the context of justification. This is an ideal case for thelogician of science, when the theory is generated full-blown and then tested and confirmed by the data. Howeverin many, if not most, cases the theory is dynamically constructed as was described in section 2.2. Thus, the theoryis constructed by adjusting it to the data. The process of adjustment to the data, which belongs to the context of generation, is also part of the process of justification. In each step of the process, we modify the theory in such away that the new version will be generated partially justified. Then we submit it to further tests and the processcontinues, where the dynamic theory may gradually become increasingly more confirmed. Hence, in this casegeneration cannot be separated from justification.

Now, what about an unintentional process of discovery? In subconscious or involuntary processes of discovery, afinal stage of justification must come after the process of generation, since the latter process does not providejustification in the traditional sense. Thus, unintentional generation (rather than discovery) and justification areseparated. This point will be further elaborated in section 7.5.

3.2.2 Justification is Not Aprioristic

The attempts to construct a logic of justification, such as inductive logic or probabilistic theories of confirmation,have failed. Induction and confirmation cannot be justified by, or reduced to, deductive inference. We mayconclude, therefore, that there is no valid algorithm of justification. Indeed, confirmation is not a matter of logic; idoes not have the status of a logical proof. Rather it depends on the scientist's system of beliefs and onpsychological and sociological factors. Hence, both contexts are not guided by logically valid principles and,therefore, there is no epistemic priority to justification over discovery; both have the same epistemic status. HilaryPutnam argues that if any of the two contexts are guided by rules, these have the status of maxims (Putnam 1973,268). The above argument can be raised against thesis (b) of the D-J distinction. It is not only the process of discovery which is not amenable to logical analysis; also justification is not.

However, even if we could show that justification is a matter of logic, we might still question the justification forthe rules of logical inference. If we do not treat the principles of deductive logic as a priori justified, then howwould we justify these very logical principles which confer justification upon our







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ideas? In the next chapter, I will propose a view which maintains that the rules of logical inference are bythemselves justified in virtue of their being a good explication and explanation of our intuitive inferential practicHence, those logical principles, which supposedly eliminate descriptive psychology from epistemology, are bythemselves justified by reference to actual thinking processes. Which discipline then, if not empirical psychologycan determine what are the rules behind our inferential practice? Thus, both contexts are not amenable to logical

analysis and even if they were, this is not an aprioristic logic but a logic which is susceptible to empiricalinvestigation. This argument can be raised against theses (b) and (c).

Harvey Siegel (1980, 301) raises the following objection to Putnam's claim: "the point of Reichenbach's distinctiois that information relevant to the generation of a scientific idea is irrelevant to the evaluation of that idea; and thdistinction between generation and evaluation (or discovery and justification) can be instructively maintaineddespite the fact that both contexts are guided by maxims."

Before I will propose my objection to Siegel's objection, I will offer an example which seems to be favorable tohis claim. Suppose the construction of a theory is guided by maxims of adherence to a certain world picture or tosome general established theoretical principles. If, on the other hand, the maxims of evaluation depend only on thformal syntactic relations which hold between the theory and certain observational sentences, and not on thecontent of the theory, then justification, indeed, does not depend on the maxims of generation, which refer to the

content of the theory. A simple example for such a situation would be the case when the maxims of generationdemand that an explanatory theory of gas behavior be corpuscularian and adhere to the mechanistic world picturewhereas the maxims of justification demand only that the logical implications of a theory match the observationalresults according to some formal confirmation theory. Here validation is indeed independent of the context of discovery or generation. However, if validation by logical (syntactic) standards is not aprioristic, there is no reasoto treat these standards as giving an absolute warrant for the truth of the theory.

Thus, by claiming that "the point" of the D-J distinction is that the context of discovery is irrelevant to the contexof justification, Siegel ignores the epistemological import of the distinction. According to Reichenbach and hisfollowers, the two contexts differ in their epistemic status; the context of discovery does not confer an epistemicwarrant to the discovered idea, whereas the context of justification, because of its logical force, does. Hence, if both contexts are maxim-guided, the epistemological spirit of the thesis will be absent. The context of justificatio

will have no normative import, i.e. it will not have any epistemic superiority over the context of discovery as thethesis requires. Putnam's objection refers, therefore, to the absence of epistemic superiority for the context of justification when it is maxim-guided.







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3.2.3 Information about Generation is Necessary for Evaluation: Predictability and Novelty

If the scientist knows what are the content-dependent criteria of plausibility of hypotheses, he will construct thetheory, taking into account these criteria. This is the subject matter of the logic of pursuit discussed in section 2.2If the hypothesis complies with these criteria, its plausibility, or prior probability, contributes to the final degree oconfirmation, as can be seen through Bayes's formula. Thus, in this case, an information about the generation of the hypothesis is relevant to the evaluation of the hypothesis. But then, the maxims of hypothesis-generation arederived from the maxims of evaluation.

If the standards of evaluation are taken into account when the theory is generated, information about generationmight be relevant to, but not necessary for, evaluation. When a hypothesis is proposed, we do not have to look fothe criteria which guided the scientist who generated it. We simply inspect the hypothesis itself and find outwhether it complies with the world picture, for example. Indeed, the D-J thesis implies that although informationabout generation might be relevant to evaluation, it is not necessary for evaluation. However, as I will show inwhat follows, there are important cases where such information is necessary.

A very important question which bears on the confirmation of a scientific theory is whether or not a certain eventor phenomenon which is predicted by the theory was known at the time the theory was proposed. In scientific

practice it is well known that when the predicted event is observed, or becomes known, only after the theory wasproposed, then the theory's degree of credibility rises considerably, provided that the event has not been expectedon other grounds. Typical examples are the discovery of a new planet (e.g. Neptune) or a new particle (e.g. theomega minus), which were predicted by physical theories. This intuitively accepted methodological principlecannot be explicated in a confirmation theory which depends only on syntactical or formal relations between thetheory and observation statements, since such relations are timeless, i.e. are insensitive to time priorities. I shallilllustrate this point by the following example. Let us consider Nicod's rule of confirmation which states roughlythat statements of the form ($x)(Ax & Bx), i.e. "there exists an object of the kind A with a property B," confirmsthe law-like statement (x)(Ax É Bx), i.e. "every A is B." This rule is insensitive to the question of when eachstatement became known to the scientist who proposes the hypothetical law. If our maxims of justification or confirmation are of the formal kind, like this one, then information as to how a hypothesis has been arrived at isirrelevant to its confirmation. Typically, a formal rule of confirmation takes into account the final products of

scientific discovery, i.e. the statements which describe laws and theories, without taking into account the historywhich led to their discovery. Thus, the D-J distinction thesis fits in well







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with the ahistoric epistemological view, which maintains that all that is relevant to the validation of a claim is itsformal structure and relations to other claims.

If we wish to stay close to actual inferential practice in science, however, we have to devise confirmation ruleswhich will do justice to the above historical or generational consideration. With such rules, the question of whethor not a theory has been constructed with the knowledge of certain facts or phenomena will be relevant to theevaluation of the theory. The higher the percentage of facts previously unknown to the discoverer which aresuccessfully predicted by the theory, the higher will be the epistemic status conferred upon the theory by theserules. In such a case we can say that we have gained something from the theory.

The fact, or the methodological requirement, that a theory gets strong support from its novel predictions is put intquestion by several authors (Donovan, Laudan, and Laudan 1988). According to these authors, the case studiesthey present show that theories can be accepted without meeting the above requirement. Finocchiaro finds noevidence that Galileo demanded that the Copernican worldview should yield novel predictions (Finocchiaro 19884967). Hofmann claims that Ampere did not make this demand as a touchstone to his electrodynamics (Hofmann1988, 201217). And Zandvoort finds that surprising or novel predictions played no role in the acceptance of nuclemagnetic resonance (Zandvoort 1988, 337358).

These cases indicate that in the absence of novel predictions, scientists may accept a theory if it successfullyexplains known facts. But there are degrees of acceptance. The following generalization is supported by examplesif, in addition to the explanation of known facts, the theory also predicts a novel fact and this fact is later discovered, the effect of this event on the credibility of the theory is much more dramatic, and the acceptance of the theory is much stronger. For example, the unitary symmetry theory had been accepted for pursuit by particlephysicists before the discovery of the W- particle, since it had successfully explained a variety of known facts anrelations much better than its competitors, such as the Sakata model or the G2 symmetry group. Yet, the discoverof the W- (Barnes et al. 1964), which had been predicted by the theory, led to the final acceptance of that theory,with a dramatic impact.

The requirement that a theory should be judged by its ability to solve problems it was not invented to solve, or toexplain phenomena it was not invented to explain, is supported by many similar examples. According to this

requirement, the credibility of a theory may rise when it explains things already known, provided they were nottaken into account when the theory was constructed. But from the vantage point of the discoverer there is nodifference between the case in which the predicted fact was not known at the time of discovery and the case knowbut not taken into account. The question is whether the discoverer generated his theory without taking into







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account a certain fact. If the fact was not taken into account and it is afterwards explained by the theory, it makesno epistemic difference whether the fact has been already known or not. Yet, there may be a difference if analready known fact subconsciously effected the process of generating the theory. Since we have already entertainethe possibility that part of the process of discovery is subconscious, we should take this possibility into account.This issue will be further discussed in Chapter 6.

Now, I would like to introduce the dynamic view of confirmation which is intimately related to the notion of dynamic theory. The proponent of the D-J distinction would claim that it does not matter how the theory wasconstructed. The act of justification is the logical act of comparing the theory's predictions to the data. However,since the theory can always be modified so that it would fit the data, there is no sense to this notion of staticconfirmation or justification, since the theory may be always be kept "justified" in this sense. Justification shouldtherefore be a dynamic notion. According to the dynamic approach which I propose (1978, 1979) a theory isconfirmed only if in our efforts to adjust it to the data we make what I call epistemic profit . Namely, if we gainfrom the dynamic theory more empirical knowledge than we have invested in it. By our investment and gain Imean the following. In the dynamic process we adjust the theory to already known data which constitute our investment. The new versions of the theory may yield successful predictions of empirical data, which constitute ogain. Thus, it makes the whole difference in the world if all, or most, of data explained by the theory was knownand taken into account before the theory was constructed and the theory was adjusted to it, or if the theorypredicted all or most of this data. So it is not the final result which counts, but the way it was obtained. In additiothe function of unification should be taken into account. Known data or phenomena which have been epistemicalisolated are unified under the theory's explanatory umbrella. This may still be regarded as an epistemic profit in awider sense. The dynamicist view may be expressed by the following words of Frederick Suppe: "Full epistemicunderstanding of scientific theories could only be had by seeing the dynamics of theory development" (Suppe1974, 126).

The above approach may be called dynamicism. It can be contrasted with generationism and consequentialism,which seek a warrant for the claims our hypotheses make. Dynamicism seeks criteria for judging the potentialitieand fruitfulness of our hypotheses, rather than a warrant for truth. A false theory may be very fruitful in providinnovel and successful predictions.

3.2.4 The Context of Generation Has an Epistemic Dimension

If we believe that the search for truth is not totally blind (as we will see, even evolutionary epistemologists believso), i.e. that among the infinite number of the logically possible hypotheses humans frequently arrive, in particulain







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science, at hypotheses which prove successful, it is unreasonable to exclude this fact from our epistemologicaldiscourse. We may require, therefore, that epistemology and philosophy of science account for this fact. Accordinto this view, science is not only an evaluator of ideaswhatever these may bebut more importantly, a generator of successful ideas. Hence, the ways by which humans, and in particular scientists, come to new ideas areepistemologically important. There must exist a rational way to generate good ideas in a reasonable frequency. W

would otherwise be engaged in testing all kinds of hypotheses with no preferred direction, the chances for progrebeing accordingly diminished.

It may be instructive to draw an analogy with training and judging in sport. The sport of running, for example, hatwo "contexts," the context of training and the context of judging. According to the training-judging (T-J)distinction thesis there are no exact criteria as to how to produce a good athlete and to improve results. Only themeasurement of the results achieved in a particular competition and the decision as to who is the winner are guidby exact criteria. Thus, the process of scientific discovery is analogous to the process of training. The product of tfirst process is a theory (or a law). The product of the second process is a trained athlete. The evaluation of atheory, relative to the competing theories, is analogous to the evaluation of the achievements of the athlete, relativto his competitors. The quality of a theory is judged with respect to its success in explaining and predictingobservational data and phenomena, relative to other theories. The quality of an athlete is judged with respect to hiscores in competitions. Furthermore, in the case of a sport such as running, we cannot object to the claim that themethods of training and producing good athletes are irrelevant to the way of choosing the winner in a competitionHence, this is a perfect analogy to the case where the D-J distinction is valid. Here, the method of measuring theresults is analogous to the logic of justification, whereas physiology and psychology of sport, for example, areanalogous to the psychology of discovery. Thus, the following theses are true: (a') there is a sharp line separatingthe context of training and the context of judging, (b') only the context of judging can benefit from the the methoof measuring results, (c') physiology and psychology of sport is irrelevant to the context of judging and (d') thecontext of training is irrelevant to the context of judging.

However, the T-J distincion thesis does not imply that a theory or a methodology of running should concentrateonly on the methods of judging. This thesis would surely seem to offer too narrow a view of athletics, since itignores the major goal of athletics, i.e. the goal of generating good athletes and breaking records. Moreover, if theaim of athletics is ever-improving achievement, it would be irrational for someone who wishes to understand this

human activity to be solely engaged with judging, and not at all with the methods of improving achievement. It isof course entirely rational to be interested







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in methods of judging, but why call this a ''methodology of athletics"; a better name would be "methodology of judging athletics." Thus, if the aim of the theory of athletics is to understand this human activity and to improve ithe analogue of the conclusion adopted by logical empiriciststhat the theory of athletics should conentrate only onthe context of judgingwould sound absurd here.

The moral in this for the philosophy of science is that it will miss the essence of science if it concentrates solelyupon evaluation. Rationality in science resides not only in the activity of testing theories, but also, and perhapsmainly, in the activity of generating theories which are good candidates for testing. If the aim of science isprogress, it would be irrational to be engaged in testing ideas with no regard to their content or origin. If sciencehad been engaged only in testing theories, with no regard to which theories it was testing, it is very doubtful that would have arrived at its spectacular achievements in understanding and mastering natural phenomena.

Traditional rationality is categorical rationality. It is concerned with truth. Nothing is wrong with truth. However,according to this conception of rationality, we would be perfectly rational if we had been only engaged withtautologies or with very shallow truths which can be proved beyond any doubt. We also would be perfectlyrational if we aim at arriving at absolute truth, without any chance of success. In both cases we would knownothing about the world, but we would be perfectly rational. A philosophy of science which is only interested intruth and in evaluation would adopt the categorical conception of rationality and would secure the truth of

scientific claims. However, if we want to know something about the world, it would be irrational to adopt thisconception of rationality.

Karl Popper goes to the other extreme. He requires that scientists will make bold conjectures. Thus, they would nbe engaged in tautologies or in shallow truths. He says (1969, 215) that "continued growth is essential to therational and empirical character of scientific knowledge." He stresses that the way of growth as he conceives iti.eby conjectures and refutationsis responsible for the rational and empirical character of science. However, hemaintains that it is not the business of epistemology to study the process of arriving at a new conjecture. His onlyrequirement on hypothesis generation is that a new hypothesis will be bold, i.e. that it will significanly depart fromwhat is already known or expected. But if the generation of conjectures were not guided by a mechanism of someepistemic merit, scientists would be engaged in criticizing slack hypotheses which lead nowhere. Bold hypothesemay lead in unfruitful as well fruitful directions. Since the fruitful directions constitute a very small percentage o

all possible directions, scientific knowledge would have very little chance to grow in this way. A rational gamblewho gambles with truth, would not be satisfied with the advice to bet "boldly," since under this advice he wouldhave more chances to lose than to gain a for-







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tune. Hence, one of the tasks of epistemology should be to investigate this mechanism for generating conjectures,which facilitates the growth of scientific knowledge and which therefore, according to Popper himself, guarranteethe rational character of scientific knowledge.

We may conclude that understanding the process of discovery is not only a legitimate occupation for thephilosopher of science, but is essential for understanding the phenomenon of science.

We are facing a seemingly paradoxical situation. On the one hand, the logician would tell us that there are toomany (infinitely many) possible hypotheses for explaining anything. On the other hand, every scientist would tellus that it is sometimes impossible to find even one explanation. We can always invent a theory from which wecould derive any given explanandum, may it be an event, a phenomenon or a regularity. And when we adopt onetheory, we can protect it from refutation as long as we wish, by making modifications in other portions of the bodof knowledge. This is what the "Duhem-Quine thesis" says (see Lakatos 1970). Some philosophers conclude fromthis that science is and should be pluralistic (see, for example, Feyerabend 1978). However, at least in naturalscience, pluralism and explanation do not come together; if we are left with more than one possible explanation, wdo not have any!

Thus, the difficulty of the logician is to dispose of all his candidate theories but one, whereas the difficulty of the

scientist is to discover one possible explanation for a given phenomenon or anomaly. The reason for this "paradoxis that scientific explanation is not a logical notion. The logician is "blind" to the content of the theories. Not everstatement from which we can derive the explanandum is a possible explanation. An explanation should obeycertain requirements. Some of the requirements are logical, formal or methodological, such as predictablity or simplicity. The more important requirements are the context-specific ones, which cannot be captured by thelogician's tools. The progress of science is signified by narrowing the range of possible hypotheses. This means, fexample, that the explanans should comply with the established knowledge which has been formed in this procesAnd this is a question of content, rather than of form. This is exactly where the method or the theory of discovermight help us. As we will see in the next chapter, in a naturalistic approach to the philosophy of science, the theoof discovery may yield a method of discovery. A method of discovery would tell us how to generate, or how toarrive at, hypotheses of the kind which have more chances to succeed under the extra-logical requirements. Atheory of discovery would provide us with an explanation of the fact that we arrive in a finite time at a single

successful hypothesis among the infinite possible ones.







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We would understand this phenomenon if we had a method for generating successful hypotheses at a relativelyhigh rate and if we can show that science, in fact, adopts this method. Alternatively, we could view scientificdiscovery as an involuntary, or natural, phenomenon and look for a scientific explanation for the success of science. If we adopt, for example, a view such as Poincaré's, we would have to explain the mechanism whichweeds out the large number of ideas created in our minds before the better ones rise above the threshold of

awareness. In Part II, I will try to view the philosophy of science as an explanatory discipline. As such, it will becapable of providing an explanation for the phenomenon of discovery.







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PART IIDISCOVERY NATURALIZED







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The Prepared Mind: Cultivating the Unintentional

Both conceptions of discovery by exposure and discovery by generation imply that the process of discovery iscarried out intentionally by the discoverer and that it remains at all stages under his control. However, this is anidealized, and even a distorted, picture. The following are the most obvious kinds of discovery processes which aunintentional or involuntary. The first kind is the intrapsychic process of creation, such as the process of incubation, where the discovery is a product of a subconscious activity. Furthermore, according to the theory whiwill be expounded in Chapter 6, every discovery includes subconscious stages. Second, the process may be acooperative-historical enterprise, where individual scientists do not intentionally generate the product of discoveryAccording to the social oriented view of discovery that will be developed in Chapter 7, unexpected discoveries arliable to occur in a cooperative-historical setting. Third, in the exercise of skill, as we have seen, the discoverer inot fully aware of the process of discovery. All these kinds of phenomena are involuntary or unintentional. Eitherthe discoverer participates in such a process or hosts it. Involuntary discovery may be generational. Many theoriethroughout the history of science have been generated in a cooperative and/or historical process. An incubationprocess may yield a novel idea. It may be a process of exposure as well. The discoverer may expose a deepstructure, or a solution to a problem, by a flash of insight. However, a flash of insight, or an eureka event, may ba culmination of a subconscious processan incubation process, for instance. So, although it seems to be a discoveby exposure, the whole process is generational.

It is customary to confront method-governed discoveries with so-called chance discoveries. However, it is not clewhat "chance" means here. Archimedes' discovery of his law, and Fleming's discovery of penicillin are sometimequoted as examples of chance or accidental discovery. However, chance favors the prepared mind , to use thephrase coined by Pasteur. In each of these cases, the discovery required a prepared mind. Thus, a particular observation, experience or thought triggers the process of discovery only if the discoverer is prepared for it. Hencthese cases can be included in the category of "involuntary" processes. The theory of discovery which will bedeveloped in the following chapters will give a specific interpretation to the notion of the "prepared mind."

The involuntary or unintentional discoveries are the most creative; these are the processes which enable science to

generate novelty and to make







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common knowledge. The discoverer should be knowledgeable in the field, seek information about observationalresults, be open to ideas from other fields and be familiar with the specific kind of problems for which a solutionsought. All these may nourish the involuntary process of discovery. Another kind of advice may be given for preparing the optimal conditions for the process. For example: if you have difficulties in solving a problem, leavethe problem aside, do other things, try solving another problem, take a rest. These suggestions aim at paving the

way for involuntary and subconscious activities. We encounter many descriptions by scientists of how they arriveat their discoveries, which are in line with these pieces of advice. Additional recommendations will be given inChapter 6, when we discuss a psychological theory of discovery.

Other suggestions may be derived from the social nature of science. In this case the aim of cultivation is to prepathe so-called collective mind of the scientific community. This notion will be specified in Chapter 7.

The concept of "cultivation" is not a logical or a methodological concept. I have attempted to clarify it by using anaturalistic metaphor. Indeed, the above view may be labeled a "naturalistic" view of scientific discovery. It isdiametrically opposed to a logical approach and to the possibility of mechanizing scientific discovery. In thefollowing, I will develop a naturalistic theory of science and scientific discovery which will bear upon the procesof cultivating discovery. The above recommendations or rules are drawn from psychologically and sociologicallyoriented theories of science, which will be expounded in Chapters 6 and 7.

To conclude, the alternative to method-governed discovery cannot be described as "chance" discovery. Rather, it involuntary discovery. The latter kind of discoveries are those which favor the "prepared mind." Cultivation is theact of "preparing the mind." Although we may expect the highest degree of novelty to be created by involuntaryprocesses, the philosophy of science has been totally ignorant of them, treating them as anecdotes or relegatingthem to the realm of curiosities. In the following chapters I will attempt to show how this deficiency may becorrected. But first, I will develop my conception of a naturalistic or an explanatory philosophy of science.







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Chapter 4Philosophy Of Science: From Justification To Explanation

In recent years, the philosophy of science has undergone radical changes. With the decline of logical empiricism, is not believed as widely as before that the source of scientific rationality can only be found in some system of formal logic or methodology. The philosophy of science, however, has not yet settled on a new widely acceptedpath. Thus, fundamental questions are raised with respect to its scope, tasks and methods. For example, whatshould supplement or replace the logical analysis of science? Should the philosophy of science be closely linkedthe history of science or should it perhaps be converted into a science of science? There is however one prior,more fundamental, question which has engaged traditional philosophers of science, and which is now posed moreforcefully. The question is whether the philosophy of science should adopt the task of appraising scientific claimshould it be content with the more modest aim of describing science, its methods and evolutionary patterns, or should it have both descriptive and prescriptive functions? This is the normative-descriptive (N-D) dichotomywhich together with the D-J dichotomy evoke the cardinal issues related to the nature of the philosophy of scienc

I will start by analyzing the N-D dichotomy. Traditionally, this dichotomy refers to the context of justification, i.e

to the question whether the methodological rules of confirmation or refutation, acceptance or rejection of hypotheses are normative or descriptive. However, since I attempt to develop a philosophy of science which dealwith both "contexts," I will discuss the implications of the N-D dichotomy for discovery as well. We will arrive athe conclusion that neither purely prescriptive nor purely descriptive philosophy of science are possible. Thenonaprioristic scheme which will be expounded in this chapter can be viewed as a scheme of justification or as ascheme of explanation. As a scheme of explanation it will function as a naturalized philosophy of science, or as ascience of science. Explanatory philosophy of science does







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not undertake the task of telling scientist how to do science. I will argue that it still has a normative role in aspecific sense which resembles the role of psychological advice or therapy. This kind of philosophy of science issuitable for treating discovery and in particular involuntary processes of discovery.

4.1 Normative Philosophy of Science: Justification Relativized

4.1.1 Instrumental Rationality: Science as a Goal-Directed Activity

The mainstream of traditional philosophy of science starts off with a normative or prescriptive attitude. It seeksrationality in science, i.e. it looks for the logic or reasoning behind scientific acts. Scientific rationality depends othe goals of science. If the goal is different from the goal of truth, we might call this conception of rationalityinstrumental rationality, i.e. rationality as an effective instrument for achieving the goal. It is therefore the first tasof the philosopher of science to uncover these goals. If the goals are found, the philosopher can try to answer thequestion as to whether or not the proposed means for achieving them are appropriatei.e. rational. Most traditionalphilosophers of science have taken for granted the assumptions that science is goal directed and that the main goaof science is reaching comprehensive truth about the world. Thus, they were commited to categorical rationality.

Truth is a property of beliefs or statements. Therefore, assigning to science the goal of truth means that the task o

science is to generate true beliefs expressed by true statements about the world. Hence, the rules of deductive logare the natural candidates for showing us how to do good science. If we see the task of science as generatingstatements which are highly probable, then some theory of probabilistic inference will guide us in doing sciencerationally. Thus, deductive, inductive or probabilistic inference schemes will be the basis for rational acts inscience. Adopting this approach, which may be called "logicism," the philosopher of science views science as an"inference machine." This view has implications for both discovery and justification.

Logicism has faced insurmountable difficulties. Some of these difficulties are related to the impossibility of reconciling many of the actual acts of and decisions of scientists throughout the history of science with thoserecommended by the logicist methodologies. One could assume that this might lead philosophers of science toreview their fundamental presuppositions. One such presupposition is that science is a truth-seeking system.

If we abandon this presupposition while still believing that science is a goal-directed activity, we can try to suggealternative goals. We may do this by examining the declarations of the scientists themselves throughout the historof science. We will find out, indeed, that there are other declared goals besides the goal of truth. For example, thefollowing goals are very often cited:







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The goal of explaining and predicting natural events and phenomena and the goal of advancing technology andmastering nature.

A more radical approach is to look for psychological or social motives which scientists are not aware of. Scientisdeclare that they seek comprehensive truth, objectivity, etc., but their real, hidden, motives may be different. For example, John Ziman suggests (1968) that the goal of scientific research is to arrive at a consensus, rather thantruth; this goal of consensus is what distinguishes science from other human activities. This kind of approach treascience as a social phenomenon. Scientists are not free to choose their goals; they can only choose to participate the process and obey the rules of the game, without being fully aware of its significance. This being the case, theactivity of the individual scientist cannot be judged by a standard of rationality, as if it were a goal-directedactivity. The individual soldier is not always aware of the goals of the army as a whole; for example, he may get order to retreat while the army advances.

It is not clear, however, what is the origin of these hypothetical hidden goals. If we refer to a hidden, or subconscious, motive which is shared by all scientists, we may treat it as a general phenomena and seek apsychological explanation for it. If we refer to a collective goal of the scientific community, we may seek asociological, or socio-psychological, explanation. However, we should perhaps dispense with the notion of goalaltogether. According to the fundamental conception underlying modern natural science, natural phenomena are n

regulated by goals but governed by laws of nature. Hence, if our conception of rationality is based on a naturalistiview, we would not expect natural science, as a natural phenomenon, to be regulated by goals. In particular,teleologic explanation is absent from modern evolutionary explanation, which will occupy a central role in thenaturalistic theory which will be presented in the following chapters. The kind of rationality which we would seekin science in case it is a natural (e.g. social or psychological) or an unintentional phenomenon is naturalisticrationality. I shall explain the significance of this conception of rationality in section 4.4.

4.1.2 The Dilemma of the Normative Methodologist and Goodman's Solution: Rationality without Goals

The paradigmatic model which guides the normative philosopher of science with the goal of truth in mind, isdeductive logic. Logic yields prescriptive criteria for deductive validity of reasoning. These criteria do not attempto describe how people actually reason but how they should reason. When people violate the rules of logic the

logican would say that they are in error. Similarly, criteria of scientific rationality are not intended to bedescriptions of how scientists actually reason, but rather how they should reason.

There arises the question from where does the normative philosopher of







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science take his rules of rational reasoning, and how does he justify them. If his theory of rationality is derivedfrom a first philosophy or a priori principles, such as the principles of logical reasoning, then the problem of possible violations of his recommendations in actual science will arise. He would face serious difficulty if, in thelight of his first philosophy, he recommended abandoning some of the central ingredients of scientific practice.Such science could turn into philosophically fabricated science; the most celebrated successes of actual science

might not have been achieved had scientists adopted his methodology. Thus, the philosopher who attempts to deawith real science and not with an ideal system of reasoning must keep an eye on the history of science. On theother hand, as a normative philosopher, he should justify the methodological rules he prescribes, in the light of thgoals of science. Thus, the normative philosopher of science faces a dilemma: on the one hand, he wishes tomaintain the notion of justification; and on the other hand, to avoid a situation where justified rules of inference asystematically violated by most scientists most of the time. He has to choose between abandoning his firstphilosophy or rejecting most of the celebrated chapters of science as irrational or ''nonscientific." For example, anempiricist philosopher may adopt the epistemological view that only observation sentences are justifiable. He maydraw from this the methodological rule that only theories which are wholly reducible to observation sentences arescientific. If he then finds out the Newtonian mechanics or quantum mechanics cannot be wholly reduced toobservation sentences, he must either conclude that modern physics, which is erected upon these theories, isnonscientific or nonrational, or abandon his first philosophy as a theory of rationality. The first possibility is bad

since it means killing science altogether. The second is worse since a first philosophy is, by definition, irrefutableby facts.

Nelson Goodman provides us with an escape from this dilemma. With his approach we also avoid the task of finding out what the goals of science are; the justification of methodological rules is not dependent on any possibgoals of science. This approach would be therefore appropriate for describing science in naturalistic terms. Indeedas we shall see, one way to interpret, or to make sense of, his approach is to view the human activity which isgoverned by these rules as a natural, or involuntary, phenomenon. Goodman starts with an analysis of justificationof deductive rules:

Principles of deductive inference are justified by their conformity with accepted deductive practice. Their validity depends on accordance with the particular deductive inferences we actually make and sanction. If arule yields inacceptable inferences, we drop it as invalid. Justification of general rules thus derives from

judgements rejecting or accepting particular inferences. ... A rule is amended if it yields an inference we areunwilling to accept; an







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inference is rejected if it violates a rule we are unwilling to amend. (Goodman 1965, 6364)

In other words, the justification of rules of inference is not based on a priori principles, but on their accord withinferential practice. This scheme contains a prescriptive element since an inference may be rejected "if it violates rule we are unwilling to amend." However, the reason for this unwillingness is not specified; it is treated as a givfact. We may describe this sort of accord by saying that a justified rule is in reflective equilibrium with inferentiapractice (see Stephen Stich and Richard Nisbett 1980, 190). This term is borrowed from John Rawls (1971, 20). Imay add that this should be a dynamic equilibrium, if we wish to entertain the possibility of changing our attitudtowards rules and particular inferences as our reasoning experience evolves.

Goodman generalizes this view of justification to include inductive reasoning: rules of induction are justified bytheir being in reflective equilibrium with inductive practice. We may further generalize this analysis to include almethodological rules in science; for example, rules of confirmation, refutation, acceptance, rejection andgeneration of scientific theories. Methodological rules are rules of inference or rules which guide decisions, e.g.decisions to accept or reject theories, decisions to perform certain observations or experiments, etc.

This approach to methodological rules does not presuppose any particular goals for science, or that science is agoal-directed activity at all. Its validity merely derives from its accord with scientific practice. If, however, we

assume that science is goal-directed, then the line of reasoning with respect to the goals of science is reversed hewhen a stable set of rules is found to be in reflective equilibrium with the inferences and decisions of a givencommunity (e.g. the whole scientific community or a community of scientists engaged in a specific branch of science) we assume that rational behavior in that community means obeying these rules. This means that rationaliis not universal but is community dependent (a notion which reminds us of the notion of community-specificlogic). Given the rules, we can infer or hypothesize what possible goals the community attributes to science. For example, if we find that physicists are guided by a methodological rule which requires conducting activeexperimentation rather than making only passive observations we may come to the conclusion that one of their goals is to reproduce and control natural phenomena, or to advance technology. The goal of attaining truedescriptions and explanations of natural phenomena cannot by itself explain why, for example, particle physicistsproduce more and more new, short-lived particles at higher and higher energies. As we saw in section 1.4, it seemthat by using this method of active research, physicists create artificial phenomena rather than discover natural

phenomena. We can imagine a science which would not intervene in the natural course of events and would onlybe engaged with







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recording natural phenomena. Indeed, such a passive approach was actually adopted before the emergence of modern experimental science. Thus, the goal of controlling natural phenomena and advancing technology can beseen as one of the goals which distinguishes modern natural science from its predecessors. However, as we haveseen, if scientific discovery is a natural or an involuntary phenomenon, we would not treat it as a goal-directedactivity. If, for example, we view science as an evolutionary process, the same pattern of active experimentation

may be explained by an evolutionary mechanism which I call "growth by expansion" (see section 7.3). Thisexplanation does not attribute any goals to science.

We must remember that we are dealing here with a "second order" justification, i.e. with the justification of methodological rules which are employed in the procedures of justifying knowledge claims. If we attribute anormative role to these rules, we have to justify them. However, we are not interested only in rules of justificationor evaluation, we are in particular interested in rules or methods of generating theories or other kinds of knowledclaims. These rules are not normative in the sense of warranting success or acceptance. They may be normative inthe sense that if we follow them, we have a high chance to generate successful, or acceptable, theories. This is thesense in which rules of generative induction, for example, are normative. If these normative rules of generationaldiscovery are not derived from first principles, they may be justified by a procedure such as Goodman's.

In the following I will propose a scheme in which the rules are derived from an established theory of scientific

rationality. This would explain why we sometimes refuse to amend a rule following its clash with inferentialpractice. The theory from which the rule is derived makes it immune to refutation by particular inferences whichclash with the theory, and as a result these inferences would be rejected as "invalid."

4.1.3 From Justification to Explication

Goodman's approach to justifcation is closely related to the notion of explication of intuitive rules. However, theexplication of methodological rules is based not only on the empirical data of intuitions and practice. It constituteone step towards a theoretical support to the rules. Carnap introduced this notion while attempting to explicatevarious concepts of probability and induction (Carnap 1950). By "explication" he meant formalization or axiomatization. Explication transforms vague concepts used in ordinary or scientific discourse into clearer concepts. A good explication should achieve a good agreement between the formal system and the intuitive

concepts. Such a process can expose and remove inconsistencies in the use of the intuitive concepts.

Mary Hesse advocates reducing the problem of justification of induction to the problem of explicating intuitiveinductive rules. According to Hesse the







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process of explication is divided into two tasks: "(i) To formulate a set of rules which capture as far as possible thimplicit rules which govern our inductive behavior. (ii) To formalize these in an economical postulate system"(Hesse 1974, 97). An example for a rule of induction generated at stage (i) is the rule of enumerative induction,which can be formulated as follows: "An empirical generalization should be increasingly confirmed by observatiof an increasing number of its positive instances and no negative instance." Another example for a presystematize

rule is the following rule which Hesse subsumes under the category of induction, but which can just as well beclassified into the hypothetico-deductive method: "A hypothesis should be strongly confirmed by the observationof the truth of one of its logical consequences which was not expected before the hypothesis was proposed." Aformal system most appropriate for explicating such rules of scientific method is probability theory. As wasmentioned in section 2.2.7, in such a system the probability of a theory, for example, explicates its degree of confirmation.

Let us now compare Hesse's two-stage scheme with Goodman's notion of justification. At first sight we might betempted to identify the process of reaching reflective equilibrium with stage (i); that is, the presystematized rules inductive inference are perhaps formulated via an interaction with inductive practice, and thus justified. HoweverHesse seeks justification specifically for the postulates of the formal system generated at stage (ii) and not just fothe inductive rules formulated at stage (i): "a sufficient, and perhaps the only possible, justification of a set of postulates of inductive inference would be that they form a 'good explication' of the intuitive inductive rules.Justification in this sense resides in the interaction of postulates and rules and not in any external support for thepostulates independently of the rules" (ibid., 98). Goodman refers to two methodological levels: (a) particular inferences, or inferential practice, and (b) principles or rules of inference, where the latter need justification. Hessrefers to three levels: (a') implicit inductive rules; (b') an explicit set of rules; and (c') a formalized system, wherethe postulates of the latter need justification. The implicit rules of level (a') govern the inferential practice of leve(a). Furthermore, levels (b) and (b') are identical. We can therefore identify stage (i) of the explication process withe process of reaching reflective equilibrium between rules [level (b)] and practice [level (a)]. This process,according to Goodman, provides justification to the rules. According to Hesse, however, the justification is shifte"upward" to the formal system [level (c')] and it is attained through the interaction of the system with the rules.

4.1.4 From Explication to Explanation: Paradigms of Rationality

I shall now propose a scheme of justification which will generalize Hesse's view and will employ some ingredienfrom Goodman's approach. The cen-







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tral role in this scheme will be played by a notion which I call " paradigm of rationality." This notion willcontribute to the normative dimension of the scheme. As we will see, it is akin to one of the uses Thomas Kuhnmakes of his notion of paradigm. The paradigm of rationality replaces the first principles of rationality of theaprioristic philosophy of science. However, unlike the latter the paradigm of rationality is not eternal, and mayundergo changes with the evolution of science.

The structure of my scheme of justification can be represented by analogy with the structure of theoreticalexplanation peculiar to modern natural science. I can describe such a process of explanation as an interplaybetween the following layers of scientific knowledge: (a) observational data, (b) empirical generalizations, (c) anexplanatory theory and (d) the general world picture prevailing in science, which is the scientist's general viewabout the structure of the world and its fundamental building blocks (e.g. epicycles, particles, forces, fields, etc.).For example, the kinetic theory of gases [layer (c)] explains the empirical laws describing gas behavior, such asBoyle's law, Gay-Lussac's law and the ideal gas law [layer (b)], which are the regularities found in theobservational data [layer (a)]. According to the view of explanation which I will adopt here, not every theorywhich entails the empirical generalizations explains them; a necessary condition for a theory to be explanatory isthat the theory comply with the world picture. For example, an explanatory theory in nineteenth-century physicshad to comply with the mechanistic-corpuscularian world picture [layer (d)]. The kinetic theory not only entailedthe gas laws, but also explained them, since it complied with that world picture. Furthermore, only empiricalgeneralizations which are faithful to the observational data are candidates for explanation. In the context of of scientific explanation this requirement seems trivial; no one would suggest explaining "laws" or "generalizations"which contradict most of the data. By definition, we explain something which we believe to be true, or approximately true. An explanatory theory, however, may somewhat correct the original generalizations. For example, Newtonian theory entailed a corrected version of Kepler's original laws of planetary motion. It thereforeexplains a modified version of the laws. Thus, the process of finding an explanation may change the originalexplanandum. This would have important implications when we carry over the analogy from the process of explanation in science to the process of justification in the philosophy of science. Furthermore, according to thestandard methodological practice, the explanatory theory may, or should, predict new laws. In scientific practice ithe modified generalizations or the predicted laws agree with the data, the theory is strongly confirmed.

Our scheme of justification can likewise be divided into four layers respectively: (a) particular scientific inference

and decisions ("scientific practice"), (b) methodological rules, (c) methodological theory or theory of science,which may be a formal system (such as Hesse's) but not necessarily, and (d) the







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paradigm of rationality (POR), which is our general view about the nature of science and scientific rationality.According to the conception of justification I propose here, a methodological theory, or a theory of science,justifies the methdological rules which it entails only if it complies with the paradigm of rationality. This is the ficondition for justification. Thus, justification is relativized with respect to the POR. There is no absolute or universal justification, as there is no final or eternal explanation.

Before I try to characterize in general the notion of POR, I would like to illustrate its meaning by means of someexamples. First, I will consider logicism. This POR dominated the twentieth-century philosophy of science. Itsproponents did not consider it as one possible POR. They treated it as a priori valid. This POR views science asproceeding by inferences. The goal of science is generating true, or approximately true, statements or to eliminatefalse statements. In order to achieve this goal, scientists should obey prescribed rules of inference. This view of science would require the construction of a formal system analogous to, or an extension of, deductive logic.Possible methodological theories which comply with this paraidgm are inductive logics, probabilistic confirmatiotheories, such as Bayesian theory, or falsificationist methodology. Hesse's scheme may be viewed as such amethodological theory.

Another example of POR is sociologism, which views science as a social phenomenon. This view may have anumber of versions: e.g. science as a tool for the advancement of society, or of technology. If the goal is advanci

technology, a methodological theory should imply rules of preference for research topics or rules for choosingbetween theories according to their technological utility. Sociologism may have a stronger version, referring to thinternal social characteristics of the scientific community as essential to the nature of science.

Finally, I would like to mention evolutionism, i.e science as an evolutionary phenomenon analogous to, or constituting a continuation of, organic evolution. One possible methodological rule which might be advocated bythis POR is the need for proliferation of hypotheses such that there will be great variability, this being the source evolutionary progress. Another possible methodological recommendation derived from this POR pertains to themanner by which hypotheses should be generated, i.e. independently of the phenomena to be explained or theproblems to be solved ("blind" variation). Finally, rules of elimination and falsification (selection) are indispensibto this paradigm. Thus, Popperian falsificationism may be viewed as inspired by a POR which combines logicismand evolutionism. In Chapter 7 I will expound a POR which couples sociologism with evolutionism.

How can we generalize from the above examples in order to characterize a paradigm of rationality? First, it shoube noted that in each of the above cases there is more than one methodological theory, or theory of science, whiccomplies with, or is implied by, a given POR. Hence, a POR cannot be







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equated with a methodological theory. Second, each of the above paradigms says something about the nature of science as a phenomenon. Each sets a general theme for science: "science as an inference machine," "science as asocial phenomenon" or "science as an evolutionary process." Third, since the POR specifies the general nature of science, it implies general requirements to be met by a methodological theory, i.e. it determines which theories ofscience will not be acceptable on first inspection.

The second condition for justification is that the justified methodological rules be faithful to scientific practice, e.that they be in reflective equilibrium with scientific practice. In other words, the notion of justification can beapplied only to rules which more or less accord with scientific practice. This is analogous to the notion of explanation which can be applied only to empirical laws or generalizations which accord with the observationaldata. This condition guarantees that we will not generate justified methodological rules which are not adhered bymost practicing scientists. Philosophers of science who base their methodology on a first philosophy do generatejustified rules which are not obeyed in actual science, hence the above condition is not trivial as is its counterparin the scheme of scientific explanation.

The above scheme, however, is normative, although not in an absolute sense. As in Goodman's approach, we cansometimes refuse to amend a rule which does not accord with a particular scientific inference or decision. Unlikein Goodman's account, our paradigm-guided scheme gives us a definite reason for refusing to amend a rule when

is entailed by an established methodological theory which complies with our POR. Therefore, when a particular inference or decision violates such an entrenched rule, we will reject such an inference or decision. However, aPOR which leads us to rule out some important elements of scientific practice should in the long run be amendedor be replaced by a new one.

Thus, the normativity of this scheme is expressed by the fact that it may lead to the rejection of particular inferences or decisions, and by the fact that it lends justification to particular inferences or decisions which complwith the methodological rules. However, this is not an aprioristic justification, since the methodological rules havthemselves been justified by being in reflective equilibrium with scientific practice and by complying with thePOR. This is not a universal justification; it depends on the POR. Furthermore, the system of methodological ruleis dynamic; it may incorporate new rules or drop old ones, according to the changing practice of science, on theone hand, and the changing image of science and scientific rationality, on the other.

Hence, the standards of rationality are not dictated from outside science by some first philosophy. Rather they aredrawn from both the practice of science and the POR. The POR itself is determined by external and internalsources. The external sources include epistemological and metaphysical views, the general conception of whatscience is and the attitudes of society towards







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science. The internal sources include our knowledge of the history of science and scientific practice. Thus, thePOR interacts with scientific practice through the methodological rules.

The above scheme applies to justificatory or evaluative methodological rules, such as rules of confirmation,falsification, acceptance or rejection of hypotheses. However, we may extend the scheme to apply to all kinds of methodological rules including methods of theory-generation and discovery. As in the case of justification, thescheme will have both normative and explanatory roles.

4.2 From Description to Explanation

In the previous section I described a philosophy of science the starting point of which is normative or prescriptivand the impossibility of this approach. I proposed to replace the traditional notion of justification by a relativizednotion which is analogous to the notion of theoretical explanation. I will now consider the implications when thepoint of departure is descriptive, and I will arrive at the conclusion that a purely descriptive approach is alsoimpossible and should be replaced by an explanatory approach. Thus, from both points of viewthe normative, or prescriptive, and the descriptivewe would be led to the conception of an explanatory philosophy of science whichcontains some elements of both approaches.

In dealing with the descriptive approach, we first have to see how it differs from a history of science. A historianof science cannot be a neutral observer and describe "mere" facts since he has prior expectations and attitudestowards science and he has initial concepts by which he comprehends the phenomena of science. As Lakatos putit: "history of science without philosophy of science is blind" (Lakatos 1971, 91). What is then the differencebetween the two, if any? A minimalist historian of science might be distinguished by his intention to be as"neutral" as possible, i.e. to describe the empirical facts and to avoid using generalizations or theories as far aspossible. On the other hand, the descriptive philosopher of science, being a philosopher or a methodologist, expeto find in science methods and general characteristics. He expects science to be a rule-governed phenomenon. Sua position involves an intention to analyze, to generalize or to theorize and not just to remain on the level of reporting what scientists do. However, since he does not intend to be prescriptive, he would not employ the notioof justification.

The descriptive philosopher of science will not find any list of explicit and clear methodological rules which guidscientists in their work. I do not refer here to specific research methods, such as how to prepare a chemical solutioor to solve an equation, but to universal rules, such as the rules of the hypothetico-deductive method, whichconstitute the so-called scientific







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method. Although some general methods of science are occasionally discussed in scientific literature, there is nogeneral agreement with respect to their clear formulation. Furthermore, scientists do not learn their profession bystudying a methodology. One of the lessons which a graduate student learns when he turns to actual research isthat he has to ignore many of the nice and neat principles and slogans he has learnt during his undergraduatestudies, in particular some of those principles which are supposed to constitute the scientific method.

Even when great scientists mention certain methodological principles, the philosopher of science may find that thscientists do not actually adhere to them. Perhaps the most conspicuous example of this appears at the verybeginning of modern science. Issac Newton, who declared "hypotheses non fingo" or "I feign no hypotheses,"created one of the most celebrated hypotheses in the history of science. Newton's theory of universal gravitationgoes far beyond commonsense experience and intuition, and has far-reaching predictions. Newton's use of the terhypothesis, however, is somewhat different from that of twentieth-century physicists or philosophers of science. Ione case, for example, he uses this term to mean a proposition which refers to "occult qualities" which are notobservable and measurable. This indicates another problem facing the descriptive philosopher of science.Contemporary examples are abundant. A typical example is that of the theoretical physicist who emphaticallydeclares that his theories are nothing but an economical means of organizing observational data. The philosopher science might point out that such a physicist employs the hypothetico-deductive method, where the theory goesbeyond a mere summary of observed data. Another example is that of the scientist who claims that he is makingobservations in order to confirm a theory, but a philosopher (such as Karl Popper) might tell him that hisexperiments are actually attempts to refute the theory.

Thus, philosophers of science who view their task as descriptive, face the problem that they cannot take at facevalue the declarations of scientists about the scientific method in general, and even about the principles which theemploy in their own research. So perhaps a descriptive philosophy of science should not take very seriously whatscientists say, but rather study how scientists actually do science. For example, the descriptive philosopher of science should study how scientists construct theories and check them against experimental results, and then thephilosopher might try to generalize from these findings. However, here arises a problem which faces the historianof science as well: the philosopher of science does not encounter neutral facts when he studies science; alreadywhen he starts his studies he has to choose where to look and how to interpret and categorize what he sees. By thmetascientific terms he employs he tries to capture the data of science. The raw data may include scientific paper

and reports, conference proceedings, letters (scientific products), or perhaps more abstract entities such as theorieand experi-







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ments. Here there is a parallel between a descriptive philosophy of science and science itself. It is a widelyaccepted view that there are no pure observational terms and statements in science; every descriptive statementemploys terms which are loaded with theoretical pressupositions. The same applies to descriptive statements abouscience.

The descriptive philosopher of science will naturally try to first use the metascientific terminology employed by tscientists themselves. As in the case of the scientists' declarations about the scientific method, however, he willvery soon find out that there exists no such unified and consistent terminology. As we have seen from the examplof Newton's use of the term hypothesis, metascientific terms may be interpreted in different ways at different timEven in contermporary scientific writings, we do not find any systematic metascientific terminology. Metascientifterms as used by scientists are frequently ambiguous. The term science itself conveys different meanings todifferent scientists. Terms such as "theory" or "model" are used with a variety of meanings. As was indicated insection 1.2, the term theory, for example, which is central to modern science and which is extensively used byscientists and philosophers, has a number of possible meanings, some of which are interrelated. A theory might b(1) a conjecture, as opposed to a solid factual statement; (2) a system of statements which employs so-calledtheoretical terms, i.e. terms which do not appear in the observational vocabulary; (3) an explanatory system, asopposed to an empirical generalization which does not explain but only describes and summarizes observationaldata; (4) a system of laws of nature; (5) an uninterpreted deductive system which is related to observational datathrough correspondence rules; or (6) a dynamic system in the sense described in section 1.2. Thus, when we referto "Newtonian theory" we might refer to a system of laws or to a system of statements which express a particularversion of the historical entity stretching from the the seventeenth century till the end of the nineteenth century, owe might refer to the whole historical entity. Furthermore, terms such as "theory" and "model'' are sometimes useinterchangeably to refer to the same entity, e.g. the Bohr atomic model or theory. Methodological terms such as"proof" and "refutation" are frequently used misleadingly: scientists often claim that a certain theory was proved refuted by experiment, whereas it is well known that even if theories are universal statements, they cannot belogically proved by any finite quantity of observational data. It is further known that logical refutation can beavoided by making ad hoc modifications of the theory, by reinterpreting or by ignoring the anomalous data, or byintroducing some auxiliary assumptions. Moreover, metascientific terms convey different meanings in differentsciences.

Hence, the descriptive philosopher of science must choose for himself a proper metascientific terminology and aproper categorization of scientific activity and products. He may use in a more refined manner some of the termsemployed by scientists. He may reintepret other terms and add new







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ones; the terms research program and paradigm are examples of the latter. The choice of terminology andcategorization will be made in compliance with criteria which guide the philosopher of science, such as fruitfulneor explanatory power.

In other words, the descriptive philosopher of science is led to play the role of a scientist; he will invent a scientiftheory of scientific method or a scientific theory of science. If the term theory, for example, appears in such ametascientific theory, it will be a theoretical term.

Thus, descriptive philosophy of science becomes a science of science, or rather a theoretical science of science,since the philosopher of science is not engaged in performing experiments or making observations; he just uses thdata supplied to him by the historian of science, who therefore plays the role of the data-collector or the"experimental" scientist of science who makes the observations.

4.3 Explanatory Philosophy of Science

Following the above arguments, we are led from the descriptive view of the philosophy of science to theexplanatory view. However, the explanatory view is inherent also in the scheme of justification I proposed. Indeethe scheme was constructed analogously with a scheme of theoretical explanation which is widely practised in

science, especially in the "hard" sciences such as physics. Now that we have arrived at the explanatory view fromthe descriptive starting point, it would be natural to consider the possibility of treating the scheme of justification a scheme of explanation and thus, converting the structural analogy between justification and theoreticalexplanation into a deeper similarity. As a scheme of justification it suffers from the disadvantage that it isrelativized on the POR, whereas the latter should in turn be justified. However, if we treat it, instead, as anexplanatory scheme we would avoid this problem; we would deal with a science of science and in scientificexplanation there is no problem of relativizing the explanation on our world picture, since we do not expectexplanation to be absolute. Moreover, in the next section I will argue that as an explanatory scheme the philosophof science still has a normative role, although not in the traditional sense of normativity.

Thus, we may employ the same four-layered scheme which was employed for justification to describe the structuof the explanatory philosophy of science. We would treat the layer of scientific practice as the layer of

observational data. The layer of methodological rules, which originally were subject to justification by themethodological theory, will now be treated as the empirical laws to be explained by the theory of science. Theempirical laws, which include the methdological rules, summarize and generalize scientific practice.







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Notice that I am talking here about the justification of the methodological rules rather than of the scientific practiand its products, such as laws and theories; the latter are traditionally justified by applying the rules. Similarly, Iam talking about the explanation of empirical generalizations and laws (by deriving them from an explanatorytheory), rather than about the explanation of the observational data, which is a different matter. Thus, themethodological theory in its new role will become an explanatory theory. Finally, the paradigm of rationality will

turn into the philosopher of science's general outlook on science, i.e. his paradigm of science through which heviews science as phenomenon in the world.

The same four-layered structure can be viewed as a scheme of justification based on a POR or a scheme of explanation, depending on the meaning attached to the paradigm. If the paradigm is a POR, we are in the realm ojustification; if the paradigm is our general view of science as a phenomenon, we are in the realm of explanationThe two views are not necessarily contradictory. In fact, these are the two faces of the same view. The dualstructure is exhibited in the following diagram:

In both schemes, every two adjacent layers are adjusted to each other. The methodological rules are adjusted to thpractice and the latter may be modified in view of the former. The methodological theory is tested through itspredictions regarding methodological rules and practice. The POR may change, or even be replaced, in the longrun in view of the difficulties facing the methodological theories inspired by it. A similar interaction takes place inthe explanatory scheme.

I shall illustrate the duality between justification and explanation with respect to logicism. If we treat logicism asPOR we mean that particular scientific inferences and decisions are justified only if they obey the rules prescribeby the methodological theory, which is derived from, or modeled on, a logical theory. If we change our attitudetowards logicism and treat it as a scientific paradigm, rather than as a scheme of justification, this means that it isused as a guide for constructing explanatory theories for the phenomenon







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called science and for scientific practice. In this capacity, logicism may be a general psychological or psychosociological paradigm on the nature of scientific knowledge, and a general view of how scientists reason ifact, rather than a normative view of how they should reason or act. Thus, explanatory epistemology becomes parof psychology. The task of the epistemologist qua scientist is to propose hypotheses as to exactly what the rules oinference are. A theory which explains and describes the reasoning and action of scientists is an empirical theory

which is testable and refutable. Violations of the empirical rules of inference will be treated as problems to besolved or anomalies to be explained.

Hence, logicism as a POR leads to prescriptions, whereas logicism as a scientific paradigm guides explanations.However, the distinction between the two attitudes in not as sharp as in the case where logicism is an aprioristicscheme. In my approach the methodological rules draw their justification in part from their interaction with actuainferential practice. Moreover, logicism as a POR is fed back indirectly by inferential practice through itsinteraction with the methodological rule.

The switch from one attitude to the other is therefore not so drastic. When we are in the justificatory mode of thesystem and we face a situation where the methodological rules are violated in many cases, we have the option tomodify or replace our methodological theory. For instance, we may replace an inductive theory by a Bayesiantheory of confirmation, or a naive falsificationism by a sophisticated one (Lakatos 1970). If we cannot find a

satisfactory logicist theory, however, we may look for another POR, but this weakens our normative standsignificantly. Indeed, in our search for a new POR we aim at adopting a POR which will not clash too much withscientific practice. In other words, if we are willing to replace our POR in order to avoid the dilemma of thenormative methodologist, we will be dragged by inferential practice of scientists, rather than impose our prescriptions on the latter. By this we switch from the justificatory mode to the explanatory mode. In order to findout that a certain POR leads to a successful theory of sciencei.e. a theory which does not clash too much withscientific practicewe must act as scientists rather than as normative methodologists. When such a POR is highlyestablished through the theories it inspires, we might switch back to the justificatory mode and recommend thatscientists employ the rules which are derived from the theory, knowing the limitations imposed on the normativestrength of such recommendations. In the next section I will attempt to clarify this sense of normativity.

If we treat our theory of science as an explanatory theory, it should explain scientists' inferences, decisions and

acts, concerning the generation and evaluation of hypotheses. It may explain, for example, why scientists generataccept or reject a certain theory in a given situationa situation which might be characterized epistemologically,sociologically or psychologically.







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The intermingling of epistemology with psychology in the last statement is natural, since epistemology is regardehere as naturalized. The explanatory approach treats science as a natural phenomenon to be explained, rather thanjustified in the traditional manner. This is an extension of Quine's naturalized epistemology (Quine 1969).

Quine did not distinguish between epistemology as a theory of ordinary human knowledge and the epistemologyof science. He therefore treated epistemology, including the epistemology of science, as part of psychology.According to my approach, the naturalistic philosophy or epistemology of science is not exclusively a psychologyof science. Depending on our paradigm of rationality, the theory of science might attribute to the phenomenon ofscience social or evolutionary dimensions which have an essential epistemic role. Moreover, not every possiblePOR would view science as a purely epistemic phenomenon. For example, a technologically oriented POR mighview science as a tool for advancing practical human needs etc. Another possible POR might view science as abroadly sociocultural phenomenon, which has non-epistemic sociocultrual dimensions.

What are the criteria for chosing or for evaluating a POR? We start with some initial criteria which we do notattempt to justify, as scientists do. These are intuitive criteria of commonsense rationality, i.e. the minimal criteriawhich we use in everyday reasoning, and which are shared by all people with whom we can communicate. Thesecriteria will be included in the common hard core of all possible PORs. Yet these criteria will not be immune tonon-radical revision, in the light of the developing POR. We set out to investigate scientific rationality, taking for

granted this commonsense rationality. For example, one of these criteria will be empirical adequacy; other thingsbeing equal, we would chose an initial POR which generates theories of science which are more faithful to thefacts than their rivals.

In summary, the above justificatory-explanatory scheme draws its normative strength from the fact that it is notderived exclusively from scientific practice and the intuitions of scientists, rather it is derived from an additionalsource: the POR and the theory of science. The POR is partially independent of our knowledge of scientificpractice. It is fed by our conception of rationality and by our general beliefs on human nature and on the epistemirelations between us and the world. Of course, these beliefs are partially influenced by scientific conceptions andtheories. And these are produced by the very scientific practice which is under evaluation. To this extent, thenormative strength of this scheme is weaker than that of an aprioristic scheme. But the above scheme is non-foundational. It is unavoidably coherentist. Yet, as a coherentist scheme of justification it is stronger than a semi-

descriptive scheme which







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relies on scientific practice only. Thus, justification is not absolute, but it draws it strength from all relevant sourcof human knowledge and beliefs. As James Cushing expresess it: "Scientific knowledge, as well as knowledgeabout science, must be bootstrapped, starting from what may seem a plausible position, but always keeping theopen possibility (often the likelihood) of fundamental revisions" (Cushing 1990, 240).

4.4 Normative Naturalism: Shallow vs. Deep Theories of Scientific Rationality4.4.1 Phenomenological Theories of Rationality

In this section I would like to shed some more light on the difference between a semi-descriptive theory of scientific rationality, which relies on, or is adjusted to, the practice of science, and a theory of the kind discussedthe last section, which seeks a theoretical explanation for the scientific practice. This will help us in understandinthe role of a naturalistic theory of science in explaining the processes or the phenomena of discovery.

Descriptive or intuitionistic meta-theories of scientific rationality do not rise above the phenomenological level ofmethodological practice or normative intuitions about particular instances of reasoning. According to thedescriptive or empirically oriented approaches the task of the philosopher of science is restricted to recording,describing, and at best systematizing the inferential or methodological practice of scientists. The intuitionistic

approaches derive their theories from scientists' or philosophers' intuitions about scientific reasoning. If on thisbasis alone one attempts to draw normative or prescriptive conclusions, it seems that the is-ought fallacy iscommited. However, even if such a theory does not attempt to be normative, it does not add much to our deepunderstanding of scientific rationality and the nature of science in general. In this section I will show that myexplanatory approach avoids the is-ought fallacy and attempts to add a deeper level to our understanding of scientific rationality, although it retains the empirical or naturalistic character of the theory of rationality. It is thedeeper level which makes the theory normative, to the extent that a non-foundationist theory may be normative.

I find it instructive to present my approach here as an alternative to the intuitionistic approach which was proposeby Laudan (1986), although it has been already abandoned by its author. I also find it very illuminating to comparmy scheme with L. Jonathan Cohen's account (1981) of normative theories of reasoning which are based on thedata of human intuition.

"Meta-methodological intuitionism," according to Laudan (1986), is the view that "we or scientists usually makereliable and trustworthy judg-







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ments about methodological matters (such judgments make our shared 'intuitions'), but that our explicit theoriesabout such matters are not usually so reliable, presumably because we have yet to develop a methodological theowhich does justice to our presumably sound intuitions. If one is an intuitionist, one believes that one should choobetween rival theories of methodology by asking how well they square with (at list some of) our shared intuitions(Laudan 1986, 120). A methodological theory, according to this view, is normative, since it is based only on

exemplary cases; the methodology that explicates the norms behind these cases is applied prescriptively to casesabout which we do not have shared pre-analytic intuitions. The "bedrock" or the "database" on which theintuitionist bases his judgments consists of paradigmatic cases taken from the history of science. The paradigmaticases are distinguished by the fact that we possess shared intuitions about their rationality or irrationality.

Laudan places under the intuitionist roof Reichenbach's method of rational reconstruction and Carnap's theory of explication. As we saw, the later conception has been utilized in constructing inductive logic or probabilistictheories that explicate our pre-analytic notions of probability, evidential support or confirmation. Goodman'sapproach can also be subsumed under this category. All these approaches deal with the context of justification.However, since in the naturalistic approach there is no clear distinction between theories of justification andtheories of discovery and generation, we may include the latter in the intuitionist approach to methodology. Anintuitionist theory of discovery will rely on the scientists' or the philosophers' intuitions about methods andprocedures of arriving at theories. It will seek, for example, to describe, explicate or reconstruct the implicit ruleswhich guide scientists in arriving at reasonable theories which have chances to be successful.

The question which immediately arises is whose intuitions are we talking about? Laudan addresses this questionand his answer is that we should rely on our current intuitions, rather than on the intuitions or judgments of thescientists involved in the exemplary historical cases, e.g. the judgments of the scientific elite. He refers to "our intuitive and implicit modes of ampliative reasoning," i.e. to the intuitions of philosophers or methodologists or contemporary scientists; actually to the intuitions of all "sensitive readers of the historical record." Thus, accordinto this view, anyone can have intuitions about scientific reasoning, just as one has intuitions about ordinaryinductive reasoning, provided he is familiar with the subject matter (i.e., in the case of scientific reasoningwith thhistory of science). As Laudan himself concedes, this metamethodological theory, as it stands, cannot assign tomethodology any significant critical role. The criterion for choosing those people on whose intuitions we wouldbase our theory is not justified, and cannot be justified in a non-circular manner.







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However, the requirement of familiarity with the subject matter may lead us to some useful insights. Familiaritywith the subject matter is required for every ampliative reasoning or judgment which cannot be reduced to theapplication of a content-neutral method, in contradistinction with intuitions about deductive reasoning which donot require familiarity with any particular subject matter. Indeed, in some cases of inductive reasoning, one has tobe familiar with the subject matter in order to be able to identify the "natural kinds" in the field in question, on

which inductive projections can be made. In ordinary experience the ability of identifying the natural kinds is inmost cases genetically and culturally based. However, in science the "natural kinds" or the theoretical categoriesare frequently remote from those of ordinary experience so that scientific inferential practice, in particular, requirfamiliarity with the subject matter. Actually, only active scientists in the field may have the intuitive grasp of themodes of inference and the ways of learning from experience in the field. We are therefore led to the view thatdiscerning power is essential for scientific reasoning. This is another feature which is common to the generationand the evaluation of hypotheses.

Indeed, if we entertain the view that scientific inferential practice exceeds ordinary ampliative reasoning and thatthere are methodological and inferential rules and norms which are peculiar to science or to a particular field of science, we must refer to the shared intuitions of the active scientists, or the leading scientists, in the relevantscientific community. Such a view of science may follow from the evolutionary view of science which is presentin the following chapters. One of the main conclusions which will be reached there is that our inborn and culturaldetermined intuitions are not appropriate for comprehending the phenomena investigated by modern science, sincthese phenomena are radically different from those prevailing in our natural habitat. We cannot therefore expectnon-scientists to have reliable intuitions about the rationality of genuine scientific practice; at most some of theseintuitions might infiltrate society at large. Thus, scientific practice is guided by extra-logical methodological rulesand heuristics, some of which belong to the tacit knowledge shared only by the members of the scientificcommunity. This is a community-specific world view and logic. The proper way to gain the shared intuitions aboscientific inferential or methodological practice is to undergo the lengthy process of scientific training. For example, we cannot expect that the sense of mathematical elegance or simplicity which leads physicists to acceptcertain theories and to reject others would be shared by all philosophers or historians of science.

Stich and Nisbett (1980) recommend to amend the intuitionist method of reflective equilibrium, such that theintuitions of experts in logic should be consulted, rather than the intuitions of laymen, since non-experts sometim

make logical errors. In the case of deductive inference this means consulting the intuitions of professionallogicians. However, the logician does not have a







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privileged access to ordinary human reasoning in the manner an active scientist has to the inferential practice of science. The logician studies human reasoning but does not have prefered intuitions about human reasoning. Withrespect to science, it is the philosopher of science who plays the analogous role to that of the logician. Theprofessional scientist is not a professional with respect to scientific inference or method. He carries out his"inferences" quite intuitively, being in many cases unaware of any underlying rules of inference, or that he is

making an inference at all. As I have noted, training in scientific method or inference (as opposed to specificmethods of scientific research) is only optional for scientists and in general it does not help them much in their scientific practice; an explicit knowledge of scientific method is neither a necessary nor a sufficient condition for being a good scientist. Furthermore, intuitions on which we should rely in the process of arriving at a reflectiveequilibrium, as L. Jonathan Cohen rightly claims (Cohen, L. J. 1981), are "immediate and untutored inclination[sto make some judgments (my emphasis). And "in order to avoid an obvious risk of bias, these must always be theintuitions of those who are not theorists themselves.'' When we refer to science, we can learn about the "immediaand untutored" inclinations of scientists by watching them at work, when they do things naturally withoutnecessarilly being fully aware of the methods they follow.

If the intuitions and the discerning power which guide scientists in evaluating hypotheses are field-dependent andcommunity-dependent then, a fortiori, the intuitions and the discerning power which guide scientists is discoverinand generating hypotheses and theories that are so dependent. If we do not believe in a universal recipe for generating and discovering theories, the philosopher cannot rely on his own intuitions; he should consult theintuitions of the scientists in seeking the rules or the methods of discovery and generation.

Thus, the task of the intuitionist philosopher or methodologist of science is to try and find and explicate theintuitive rules and heuristics which guide scientists, rather than to rely on his own judgment. The fact that all or most contemporary philosophers and methodologists share judgments such as the one which maintains that "it warational to accept Newtonian mechanics and to reject Aristotelian mechanics by, say, 1800," or that "it wasirrational after 1920 to believe that the chemical atom had no parts" (Laudan 1977, 160) does not reflect an"innate" intuition about scientific rationality. Rather it reflects a view which is entrenched in our society. Certainljudgments of this origin cannot be treated as a "bedrock" of any sound meta-methodology. Hence, an intuitionistwho believes that the intuitions about scientific rationality are not inborn or shared by all humans brought up in ougeneral cultural settingin the sense that our pre-analytic logical intuitions aremust attend to the intuitions shared b

active scientists. But then it seems that we accept scientific rationality as a matter of fact in science and we







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license all scientists' intuitions and acts as rational. A theory of rationality such as this will be vacuous, devoid ofany critical or normative force. In fact, any naturalistic-descriptive theory seems to suffer from this sort of vacuityHowever, as I will argue, the explanatory scheme of scientific rationality that I proposed in the last section is aprescriptive, non-vacuous naturalistic theory of rationality.

4.4.2 Explanatory Theories of Rationality: How the Is-Ought Fallacy is Avoided

The main difference between the explanatory approach and the intuitionistic approaches is that the latter give anaccount of scientific rationality and scientific method only on the phenomenological level of intuitions andpractice, whereas my approach seeks a deeper theory which will explain the intuitive rules. Only when we abandthe attitude of relying on our own intuitions and go to the field and look for the intuitions and practice of scientisas our empirical data, is the way open for us to "switch" to theoretical explanation of science and its method. Wemay arrive at the conclusion that the theory of science or the theory of scientific rationality does not necessarilyconsist only of a systematized list of rules. Such a theory may refer to deeper ontology, whereas thephenomenological level of methodological rules is derived from the theory as the empirical laws of gas behavior are derived from and explained by the kinetic or molecular theory of gases. I would like to shed some more light the question of normativity of the explanatory scheme, i.e. in what sense it can be viewed as a normative or justificatory scheme. As a first step we will see that the scheme satisfies a necessary condition for a normative

scheme, i.e. that the is-ought fallacy is not commited.

When we view the theory of science as an explanatory scientific theory, we can give four reasons for why we donot commit the is-ought fallacy in our approach.

(a) Already when we describe the facts of scientific practice, we do not give an unbiased or objective descriptionof facts, since we describe the facts within our conceptual and presuppositional systems. Indeed, one may observescientists dealing with theories or research programs or just recording and organizing observational data, whilereferring to the same activity. One may observe scientists trying to confirm their theories, whereas another observmay see the same scientists trying only to refute their theories. All depends on the fundamental concepts weemploy and on our initial point of view and presuppositions. Our point of view will determine the kind of rules wwill find in the methodological practice of science. It will not help us attend to what the scientists themselves say

they may say they are doing one thing but we may interpret their actions as doing something else. Consequently,some of our norma-







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tive intuitions are already woven into our description of the "is"; we do not infer them from the "is."

(b) Even when we have one uncontestable and stable "observational vocabulary" for describing the facts of scientific practice, our explanatory theories about science employ theoretical concepts not appearing in thedescription of the facts. For example, if we adopt a logicist theory, it may employ concepts such as "inference," o"prior probability," which does not necessarily appear in the observational vocabulary. If we follow anevolutionary theory of science, we might employ concepts such as "adaptation,'' "selection," "environment" and"variation" and so on. Hence, the "ought" is cauched in entirely different vocabulary than the "is."

(c) The way we arrive at our theory of science is not necessarily "from the facts," whatever this might mean. Wemay guess the theory, we may construct it by making an analogy with another theory from another field, we maybe guided in constructing the theory by our general world picture or we may arrive at it unintentionally.

(d) Even if we construct the theory of science "from" certain observed facts, the process of confirming the theory(provided our methodology entertains the notion of confirmation) may require independent confirming facts; wemay require that the theory will successfully predict new (perhaps unexpected) facts and phenomena or previouslunknown methodological patterns or rules.

These four points, and in particular the last three which are not available to the shallow intuitionist approach,would guarantee that in constructing the theory of science and the methodological rules, we will not possiblycommit the is-ought fallacy. This is a necessary condition for a prescriptive theory; we do not prescribe toscientists what we observe them doing anyway.

4.4.3 Ideal Theories of Rationality and the Competence-Performance Distinction

If the task of our theory of rationality is to explain the intuitions and acts of scientists, it means that we do notimpose norms of rationality from outside science, rather we accept scientific rationality as a matter of fact. Thisdoes not mean that we license as rational all that scientists do. When we introduce the deeper level of theoreticalexplanation based on our POR and theory of science, not everything every scientist is doing is licensed. Scientificpractice supplies us with disconfirming or confirming instances for our theory of science. However, whenever thetheory becomes highly confirmed or established, it is the theory rather than scientific practice which serves as our

(provisional) court of appeal for judging whether or not a decision or act of a scientist can







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be licensed or not. The criterion is whether or not what the scientist is doing complies with what the theory woulentail. Hence, although we accept scientific rationality as a matter of fact, our theory becomes a prescriptive theor

In order to comprehend the sort of "normativity" implied by such a view, it would be very illuminating to compathis view with L. Jonathan Cohen's account of normative theories of reasoning. Cohen treats a normative theory orationality analogously to an ideal theory in physics, such as the kinetic theory of gases, which applies only toperfect gases in isolated systems. Real gases may be treated by such a theory only when additional factors are takinto account. Another example is the law of free fall in classical mechanics, which applies only to the ideal,frictionless case. This is the price paid for having a theory with a high degree of generality and comprehensivenesSo is the case with normative hypotheses. Logical theories are abstract or ideal theories since they ignore spatial,temporal and causal effects. Actual human reasonings can be accounted for by such a theory only if the extra-logical factors are taken into account. Thus, the normative theory is an ideal theory which serves as an essentialpremise for explaining and predicting actual human judgments and reasonings. But it is by no means the soledeterminant factor in human reasoning.

According to our dual scheme of scientific rationality, the theory of science serves both as a prescriptive theory orationality and as an explanatory or empirical theory. Cohen, too, ascribes a similar dual role to the ideal theory ohuman reasoning. As an empirical theory, it describes a cognitive competence of human beings to form intuitive

judgments about deductive or probabilistic inferences. This cognitive competence is a "culturally or geneticallyinherent ability which, under ideal conditions, every member of the community would exercise in appropriatecircumstances. It states what people can do, rather than what they will do..." (Cohen 1981, 321). This allows for people to make inferential errors, but these will be performance errors. Thus, the explanatory approach tojustification of human reasoning can be comprehended in terms of the competence-performance distinction. Thetheory of rationality postulates the existence of a genetically and culturally based cognitive capacity in humanbeings which in ideal cases will guarantee rational inferential behavior. In real situations, which are not isolatedfrom the causal influence of other factors, this cognitive capacity will contribute, together with the other factors, tthe inferential behavior. If we can satisfactorily explain the data of inferential practice by the (ideal) theory of rationality together with theories about the other factors, the theory of rationality will be confirmed. A similar argument was proposed by Jerry Fodor (1981, 1201).

Analogously, in my scheme of justification the theory of science describes something like a "competence" of scientists for generating successful ideas and for making rational judgments. This competence is not inborn or innate, rather it is acquired. In the following chapters I will propose a theory of science







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according to which judgments in science are not related only to a competence of an individual. Judgments arerelated also to the collective wisdom of the scientific community which has evolved with science. This theoryattributes an essential epistemic significance to this collective wisdom. Another possible theory of science, such aa psychologically oriented theory, might look for the competence in the individual scientist. In any case, the task the philosopher of science is to put forward hypotheses about this ideal rationality and about the "external" factor

which motivate scientists' behavior and judgments and which may cause performance "errors." If the philosopher of science finds a theory of science which together with the external factors successfully explains and predicts thintuitions and behavior of scientists, his theory is confirmed and he is in a position to criticize improper judgmentor behavior. He may further identify in specific cases disturbing factors which, when removed or avoided, willclear the way to rational behavior. The disturbing factors may be, for example of psychological, social, economicor political origin.

4.4.4 The Therapist Model of Rationality and Its Implications for Involuntary Processes of Discovery

The best way to clarify the prescriptive function of the philosopher of science according to the above approach isto compare it with the function of a therapist in guiding people in overcoming mental or physical problems. Let utake the example of breathing. A normal human being has the inborn "competence" for breathing correctly.Breathing is a physiological function regulated by the parasympathetic nervous system. Thus, correct breathing is

an involuntary activity. When there are no breathing problems, a person is in general not at all aware of thisactivity. Only when problems arise, might one be helped by the guidance of a therapist. The physiologist or themedical researcher does not learn the chracteristics of correct breathing only by watching how people breathe. Hiknowledge of the functions of breathing derives from his theory of human physiology. In constructing the theoryactual breathing practice will be only part of the data at his disposal. He will not prescribe to us how to breathecorrectly merely on the basis of his observations of how people breathe. Thus, he does not commit the is-oughtfallacy. If he would stay only on the phenomenological level and draw his knowledge about breathing only fromobserving how humans breathe in fact, he would not be able to distinguish between "correct" and "incorrect''breathing. The medical researcher who is equipped with a physiological theory will be able to characterize correcbreathing and to identify factors which cause people to breathe incorrectly. He may recommend them, for examplto improve their posture, to perform proper exercises, to change their life style and so on. He may also teach themhow to breathe correctly. The correctness of breathing is thus a functional attribute, related to the function of

breathing in the organism.







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The above metaphor refers to involuntary processes. The competence to reason correctly is treated as aninvoluntary faculty. The competence to make discoveries, a fortiori, can be treated so. As I have indicated, some the major kinds of discovery processes are involuntary: e.g., the process of incubation and the process of generating a discovery by cooperation. So, the above conception of rationality is naturally applied to these kinds oprocesses.

Thus, the philosopher of science who bases his theory of rationality only on the data of intuitions and themethodological practice of scientists can be likened to the therapist who bases his knowledge andrecommendations only on the data of actual breathing. The moral of the above story is that the competence for making proper judgments in science is unintentional or "innate" in the sense that the scientist is unaware of it.

The exact manner by which scientists acquire this competence and how it is expressed in them depends on our theory of science or scientific rationality. For example, if our POR is "sociologism," our theory of science mightclaim that the individual scientist is compelled to make the right judgments whenever he is integrated with thescientific community and obeys its norms of behavior. The institutions and modes of behavior of the scientificcommunity, such as education, imitation, criticism, cooperation, communication and publication systems, wouldkeep the individual scientist on the right track. The competence for making right judgments is a collectivecompetence, built in the social system of science. The social structure and dynamics of the scientific community

regulates processes such as theory generation, acceptance or rejection, analogously to the manner by which theparasympathetic nervous system regulates breathing in the human organism. If our POR is "evolutionism," wemight hypothesize, for example, that scientists are (unknowingly) engaged in the selection of "blindly'' generatedideas and theories.

The above kinds of theories of scientific rationality do not yield a method of discovery. Instead, the discoverer mderive from them suggestions and recommedations for "preparing" his mind. The notion of rationality refers here involuntary and unintentional acts. Alternatively, we may dispense with the notion of scientific rationalityaltogether . In this case, we would maintain that the notion of rationality is not applicable to involuntary or naturalprocesses, including science.

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To conclude our general discussion of the naturalistic approach, we may confront the two movements: naturalismand mechanism. They seem to be diametrically opposed. Mechanical lung is no real replacement for natural lung.The former would always be inferior in performing the physiological function of breathing. By the same token, thnaturalistic and involuntary aspects of discovery are not likely to be fully mechanized. There is a shortcom-







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ing inherent in mechanized discovery in virtue of its technological character. Mechanized discovery is atechnology which purports to solve problems, to discover regularities and perhaps also to generate theories. If aprocess of discovery is an involuntary phenomenon, or, in a very broad sense, a natural phenomenon, atechnological device might, at most, imitate or simulate it. However, the replacement of natural phenomena bytechnology would produce discoveries which will suffer from all the shortcomings of synthetic products. It is very

doubtful whether synthetic science would have produced Newtonian and quantum mechanics and the theories of evolution and relativity, as it is very doubtful that technology would produce great symphonies. If science hadgoals and if we knew what these goals were, we could replace it by technology. And technology might do a bettejob than human scientists. However, in treating science and scientific discovery as an involuntary or a naturalphenomenon, we rule out the possibility of the existence of any such goals. To pursue the analogy with art,technology plays an essential role, in paintings or in sculpture and in particular in music. But technology onlysupplies the tools and the materials. It might open new possibilities for creativity. But it cannot replace the creativartist. In the same fashion, the computer cannot replace the creative scientist or creative processes of discovery,although it might serve as a very useful tool in the hands of the discoverer and might open new directions for theprogress of science.






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Chapter 5An Evolutionary Theory Of Discovery: In Search For The Unexpected

5.1 Evolutionary Epistemology: Taking Natural Selection Seriously

Evolutionary epistemology (EE) is perhaps the best known example of a naturalistic philosophy of science, wherthe theory of evolution is brought to bear upon the philosophy of science. Originally, EE started as a theory abouthe nature of our cognitive apparatus. Konrad Lorenz (1941) was one of the pioneers in this approach. Only laternew approaches by Stephen Toulmin (1972), Karl Popper (1972), Donald Campbell (1974b) and others referredalso to the evolution of scientific knowledge.

The basic idea behind this approach is that all biological evolution is an evolution of knowledge. Here knowledgeis not construed as "justified true belief," as traditional justificationist epistemologies would have it. Rather, it isconjectural knowledge in a Popperian sense, according to which knowledge is always conjectural. Informationabout the environment is reflected in the anatomy, physiology and behavior of organisms which have to adapt tothat environment. This is an endosomatic knowledge which is encoded in the form of genetic information andwhich is a product of the phylogenetic history of the species. An evolutionary change which brings about a betteradaptation to a given environment means, therefore, growth of endosomatic knowledge about that environment.

The basic assumption behind this view is that the growth of endosomatic and exosomatic (non-organic) forms of knowledge is governed by the same basic rules. A stronger claim is that the two processes are different phases of the same phenomenon. This view is summarized by Kai Hahlweg and C. A. Hooker (1989, 23) as follows:"Knowledge development is a direct extension of evolutionary development, and the dynamics of the twoprocesses are identical." If the rules of natural selection apply to organic evolution, i.e. to the







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growth of endosomatic knowledge, they should, therefore, apply also to exosomatic knowledge, such as scienceand technology. New mutant organisms, which are to be selected by the environment, fulfill the same function asnew hypotheses or new conjectures to be tested and selected as providing the best explanations for theobservational data. The model of natural selection requires that the new variations (mutations and recombinationswill be quasi-random, i.e. that they will occur independently of their eventual contribution to the needs of the

organism and their survival value, or without any correlation to environmental pressures. Hence, the growth of exosomatic knowledge should take place via so-called blind conjectures. This means that the generation of newconjectures or hypotheses will not be influenced by the "pressure" of the problems they ought to solve or the datathey are supposed to explain. This is an epistemological claim.

Thus, here we draw epistemological conclusions from a scientific theory. This intermingling of epistemology,traditionally a "pure" philosophical discipline, and science is characteristic of the naturalistic movement in thephilosophy of science, which allows epistemology and the philosophy of science to benefit from the results of science, or be treated as part of natural science.

Popper reached the same epistemological conclusion, about the "blindness" of scientific conjectures, from thevantage point of his theory of knowledge. According to his theory, scientific knowledge grows by chains of conjectures and refutations. Scientists put forward conjectures to tests. Those conjectures which withstand severe

tests temporarily survive, whereas the others are rejected. Scientists do not arrive at their hypotheses by collectingfacts and generalizing from them, or by inferring their hypotheses from the data in some other ways. There is nologically valid way to do this. For example, any number of observed white swans would not give us logical prooffor the conjecture "all swans are white." The only thing we can infer from observational data, with logical validityis that our conjecture is false. This happens when we observe a counterexample, such as a black swan, whichwould refute the above generalization. Thus, in science and in everyday life, we arrive at our conjectures blindlysince we have no other choice; no conjecture can be validly inferred from the data.

I would like to add a hypothetical remark. The line of reasoning presented before can be reversed. We have startby drawing epistemological conclusions from a scientific theory. Now an epistemological theory may haveimplications for science. Starting with the Popperian theory of knowledge and assuming that biological evolution an evolution of knowledge, we may conclude that the method of learning from experience through blind

conjectures and refutations, which applies to exosomatic knowledge, should apply also to endosomatic knowledgeIn other words, as it turns out, an epistemological theory has an implication for empirical science, biology: organievolution "should" obey the rules of natural selection. If the first approach is labeled







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"naturalizing epistemology," the second, hypothetical, argument could be termed "epistemologizing biology."

Evolutionary epistemology deals with both the evolution of our inborn cognitive capacitiesthe "hardwired" basis ohuman knowledgeand with the evolution of human knowledgethe "software." When dealing with the geneticallybased ''hardwired" capacities, the evolutionary model is taken seriously, since we assume that the genetically basecapacities are functions of the genetic "hardware," which is an evolutionary product. When we deal with theimplications of EE for the evolution of human knowledge, and if we treat EE as a descriptive or as an explanatorscheme, it becomes a scientific theory of sociocultural evolution. However, there are approaches which treat thenatural selection model just as a metaphor, or as an analogy, for the growth of knowledge. If we remain on thislevel, there is neither a prescriptive nor an explanatory value to the model; we would hardly gain any new insightwhen we state, for example, that ideas or theories compete just as organisms struggle for survival or as differentspecies compete for the resources of some niche. However, if we treat the evolutionary theory of knowledge as ascientific theory, the metaphor will eventually become a realistic scientific model, transcending its literary value.

When we take evolution more seriously and treat EE as an explanatory theory, we may adopt either of thefollowing two views. We may treat the growth of scientific knowledge as literally a continuation of theevolutionary process of which organic and cultural evolution are parts. Or we may treat science as a vicariousevolutionary process which serves as a tool for the survival of humankind. Of course, the two views need not be

totally exclusive; they may partially overlap. Thus, taking the natural selection model seriously means that we areontologically committed to this model, namely we do not treat the natural selection model just as a useful tool fordescribing the growth of knowledge; rather we consider natural selection to be a true feature of the phenomenon human knowledge.

In adopting the evolutionary, or the natural-selection paradigm of rationality, and an evolutionary theory of science, we do not "accept" evolutionary theory, or appraise it as better than its rivals. Our general beliefs andbackground knowledge, including scientific knowledge, gives the evolutionist POR some initial plausibility. But merits as a POR will also be judged according to its success in explaining science. The criteria of explanatorysuccess are those hard-core criteria for theory appraisal mentioned in the last chapter. It is a combination of boththe initial plausibility and the consequentialist criteria of confirmation, fruitfulness, etc., which will determine itsfate.

Natural selection can be viewed as a universal explanatory paradigm referring to a general pattern of changeprevailing in complex systems. It applies to processes in which a higher order is created, new forms emerge andnew information is gained. The growth of knowledge and the accompanying







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technological progress and social changes indeed yield increments of information and the emergence of a newconceptual order and new social forms.

A process which proceeds according to the model of natural selection must exhibit three main features: (1) amechanism for generating blind or quasi-random variations, (2) a mechanism for eliminating unfit variations, (3) mechanism for propagating the surviving variations. In science, variations are ideas or hypotheses.

5.2 Blind Variation: The Principle of Serendipity

Point (1), which has direct implications for discovery, has evoked the most serious objections to the naturalselection model for the growth of scientific knowledge (see, for example, Thagard 1980). Although, as Popper argues, scientific theories cannot be logically derived from observations, the generation of theories seems to be byno means blind to the observational data. When scientists generate theories for explaining some phenomena, theyseem to be guided by methods and beliefs, although the latter do not yield logical validity. Yet, as will be argued this chapter, although scientists are guided by methods and established theories, many creative leaps andbreakthroughs in science result from serendipitous processes which represent the blind discoveries in science(Kantorovich and Ne'eman 1989). And, according to the theory which will be discussed in the next chapter, eventhose discoveries which do not seem to be serendipitous include subconscious stages of blind variation and

selection. Thus, Einstein's discovery of special relativity, which seems to be a typical intentional process, probablincluded such stages. Einstein himself, drawing upon his own experience, points at infraconscious stages in thecreative process.

5.2.1 Are Scientific Discoveries Analogous to Blind Mutations?

Karl Popper and Donald Campbell relate the requirement of blind variation to the fact that it is logically impossibto validly infer empirical generalizations or theories from observational data. If, indeed, there is no rational theorygenerating method and no logical way of assessing a theory's validity, there is no justification for the theory in thetraditional sense. This is why Campbell qualifies the generation of new scientific ideas or theories as "unjustifiedvariation" (Campbell 1974a). However, do these "unjustified" variations truely have the same significance as quarandom mutations or recombinations in biology?

At first sight, the answer to this question would seem to be in the negative, considering that in conceiving newtheories, we are already equipped with a guiding apparatus even though this apparatus itself is an evolutionaryproduct. One of the major programs of EE expounds the view that our cogni-







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tive apparatus is itself an evolutionary productboth on the organic and on the cultural levels. Our cognitiveapparatus determines our ways of concept formation and determines what kinds of predicates will appear in our natural languages, and thusour standards of similarity. This is a Kantian-like outlook: we impose our notion of similarity and our categories upon the world. However, our system of natural kinds and our conceptual systems anot eternal and are not immune to revisions. In science, the system of natural kinds is a product of the selection o

ideas and theories. Electrons, which have both particle and wave aspects, are natural kinds in science, althoughnatural languages do not accomodate this kind of predicate. Scientific language is thus the successor of naturallanguage in this respect: it is a product of an extended cognitive apparatus which has evolved with science andwhich consists of the widely accepted world-view of the scientific community.

Our cognitive apparatus, our general expectations and our system of natural kinds are genetically and culturallybased. However, they are not infallible and are not rationally justified. Since they are the results of a naturalselection process, they reflect both the nature of our species (our interests and needs) and the structure of theenvironments in which they have evolved. Thus, we are imprisoned within our conceptual system. But, unlike whis claimed by "pessimistic" Kantianism, we transcend this system in the process of scientific evolution.

The system of natural kinds and the related general world picture thus guide us in the construction of a definitehypothesis (among the many logically possible ones) when explaining a given set of data or when solving a given

problem; i.e. they fulfill the task of narrowing down the range of possible explanations or solutions and in manycases we are left with a unique possibility. Let us look first at an example from everyday life. Suppose we arereading a book and it becomes too dark to read; if there is a lamp in front of us, we do not have to guess blindly iorder to generate the hypothesis which will almost always solve our problem. We simply hypothesize that thesolution is to switch on the lamp. Although there is no logical justification for this hypothesis, we do not discoverblindly or generate it randomly. In arriving at our fallible solution, we are guided by our implicit rules of inductioand by our system of natural kinds (the latter determines what sort of predicates are amenable to inductiveprojection). This sort of solution is fallible, but in most cases successful. Thus, although we go beyond what isstrictly known (we do not really know that will happen when we press the button), and although our hypothesis islogically unjustified, we do not arrive at it blindly; our prior expectations and our general world picture yieldalgorithms or heuristics which guide us in explaining given data or in solving given problems. It is in this sensethat the process of discovery of a solution to a problem would appear to contradict the analogy with a blind

mutation, which is generated independently of its contribution to the survival or the needs of the organism.







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In the development of science, we thus indeed have a very elaborate guiding apparatus. "Normal" science,especially, is based on a relatively stable world picture and conceptual system, on established general theories andon methods of theory-construction and concept-formation. Thus, problem-solving in normal science is guided. Tprevailing tradition or heuristic partially guides scientists in the choice or in the construction of a hypothesis. InChapter 2 I described a variety of methods and guiding tools for exposing and generating discoveries. For examp

in constructing an empirical law scientists are guided either by inductive rules or by statistical methods.Alternatively, there are heuristic principles for constructing explanatory theories which are sometimes derived froa general metaphysical outlook or world picture.

Thus, in normal science, even more than in everyday life, the typical case is that scientists appear to solve problemby intentionally trying to solve them, unlike the case of blind mutations, which do not arise as a response toselective environmental pressures. The fact that problem-solving in normal science is not blind would thereforeseem to contradict the paradigm of natural selection. Campbell, however, gives two arguments showing that naturselection still operates in the evolution of science (Campbell 1974b). The first argument maintains, as I mentioneabove, that the guiding scientific world picture or tradition is itself a product of preadaptation, i.e. it is a product oselection on the scientific, cultural and organic levels. The range of variation on the scientific level is therebyreduced by selective processes at the cultural and organic levels; our cognitive apparatus, which is a product of organic and cultural evolution, reduces the range of possible ideas and theories. The scientific world picture, whicis a product of selection on the scientific level, then further reduces the range of possible variation on the level ofnormal science. We observe, therefore, the following rule in this hierarchy: the range of possible variation at anygiven level is reduced by selective processes at the underlying level (see Amundsen 1989). Thus, normal science preadapted by the process of selection to its domain of investigation.

If we look for the parallel situation on the organic level, we notice that the range of possible variation is limited bthe constitution of the organism's genotype and by the laws of molecular biology. More specifically, the range of mutations which a given gene can undergo is restricted by the gene's structure. Hence the mutational repertoire ogene pool is restricted or determined by the evolutionary history of the species, just as the repertoire of new ideasin science is restricted by tradition or by the world picture. Futhermore, as was argued by Francisco Ayala(Dobzhansky et al. 1977, 6566) when a species is in a state of stability (which is the parallel of normal science),and when the environmental conditions are stable and the species does not move into a new habitat, it is more

probable that new mutations will be detrimental rather than advantageous. The reason for this is that if a certainvariation does not appear with a high percentage in the gene pool, it is most probable that it







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has been tried in the phylogenetic history of the species and has already been repressed. Only radicalenvironmental changes might still expose an advantageous variation. The parallel statement with respect to sciencis that radically new ideas are repressed in a mature, or an established, stage of normal science, when unexpectedexperimental data are not produced, no radically new experimental technology is introduced and no new theoreticresults are imported from other areas. Thus, the presence of a restricting and guiding tradition does not contradict

the model of natural selection.Campbell's second and main argument, in defending natural selection in science, is that even in the presence of atradition and a background knowledge there still must remain an element of blindness in scientific problem-solving, since the tradition or heuristic and the background knowledge do not uniquely determine the solution forgiven scientific problem. Thus, Campbell maintains that in general, there remains a range of possible solutionsamong which the scientist can only choose blindly, i.e. independently of the data or of the problem to be solved.His argument is analytic or logical: "In going beyond what is already known, one cannot but go blindly. If one cago wisely, this indicates already achieved wisdom of some general sort...which limits the range of trials" (ibid.,422). Note that to "go wisely" still means here to go blindly, though within a narrower range of trials.

However, in contrast with the above argument, in many cases scientists do arrive at new pieces of knowledge,including new laws and theories, in a non-blind manner. There are two major ways of doing this: by deductive

inference and mathematical derivation, or through experimentation and observation. In normal science, scientistsaspire to gain new knowledge or to solve problems in a methodical manner through these means. Thus blind searcis by no means typical to normal science; it is the exception rather than the rule.

The first way of generating variations in a guided manner is through deductive inference or mathematicalderivation, whereby the scientist exposes a new theoretical result or prediction hidden in a given theory. For example, Maxwell derived the existence of radio waves from his equations. However, as I have already mentionealthough the results of a deductive inference or a mathematical derivation are logically contained in the premises,is not always true that the results are known to the scientist before he makes the derivation or the inference. Thus,is not true that Maxwell knew about radio waves as soon as he arrived at his equations. Yet, deduction andmathematical derivation are by no means blind activities. Deductive inference is the prototypical way of gaining new knowledge in a non-blind manner.

The most common way of gaining new knowledge by deduction or by mathematical calculation is when scientistsderive a prediction from a law or a theory in conjunction with statements describing observational data or initialconditions. Thus, if the data or the initial conditions are accepted by the scien-







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tific community as true or reliable and if the theory is highly established, then the prediction may constitute a newpiece of knowledge. In any case, the prediction can be tested experimentally and if the results agree with theprediction, we must conclude that we have here a new piece of knowledge which was gained non-blindly, since tprediction guided us in deciding where to look. In this manner scientists predict not only singular events, such asan eclipse, but also empirical laws, such as the laws which govern the behavior of a given configuration of bodie

(e.g. a planetary system) or particles (e.g. an atom of a given element or a nuclear system), which can be derivedfrom Newtonian mechanics or quantum mechanics, respectively, in conjunction with the physical properties of thsystem.

However, there is a wider range of scientific activity which is modeled on deductive inference and which istherefore non-blind. It includes research programs or processes of problem-solving which are guided by somecomprehensive heuristic. In section 2.2, I discussed the approach which converts ampliative inference into adeductive inference. I also discussed heuristic-guided theory-construction. We may view these processes, too, asgeneralized inferences, as if the heuristic fills the gaps in the deductive inference, playing the role of an "inferenclicense" or of a missing premise. The accepted heuristic for problem-solving and for theory-construction in a givfield is derived from the guiding apparatus of the scientific community. As we have seen, the heuristic, whichnarrows the range of possible explanations or solutions, may leave room for creativity. Yet in some cases it mayreduce scientific inference to a deductive inference.

The second way of generating new variations in science in a guided manner is by making observations andexperiments. Empirical generalizations and laws of nature can then be derived from the observational data byapplying inductive rules or statistical inference, without a resort to blind groping. The available conceptual systemand the general world picture narrow down the range of variation such that in a given situation controlledexperiments may lead to a unique generalization. Furthermore, if there is a comprehensive theoretical framework and elaborate methods or heuristics for theory-generation, new models or theories may be deduced fromexperimental results. This might happen when the number of possible solutions of a given problem or the numbeof possible explanatory theories is manageable. In order to obtain a unique solution the scientist will conductcontrolled experiments which may leave him with a unique solution, eliminating all other alternatives.

Thus, the general world picture and the heuristic may narrow down the range of possible variations so that the

arrival at the final discovery is a result of accumulated experimental data and deductive inference or mathematicaderivation. This is the reason why scientists often claim that they deduced or derived a certain theory or modelfrom the data. This deduction or derivation is valid only in view of the accepted wisdom of the scientificcommunity. Also,







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in this light we can understand how scientists who share a general theoretical framework, general beliefs andheuristics do arrive at a consensus with respect to the acceptance of a certain theory, or sometimes independentlyarrive at the same theoretical result, as if it were a result of a straightforward mathematical calculation.

The above description refers to the ideal case of scientific inference which is not always realized in practice. Inmany cases an element of chance infiltrates into the process. But the point is that in principle blindness is not anecessary condition for gaining new knowledge and for generating new solutions to problems or new explanatorytheories. On the contrary, in "normal" science scientists expect to solve problems and to discover explanatorytheories by inference or by heuristic-guided problem-solving. Thus, the model of blind variation would appear tofail when we refer to normal science, which does not break with tradition; if scientists would adhere to this modethey would not waste so much time and energy in trying to solve problems in a methodical or a guided manner. Iis only radical or "revolutionary" changes in science that can clearly be described as typically involving blindvariation. However, even scientific revolutions have their roots in normal research or problem solving, i.e. in aguided activity.

And yet, it will be shown in the next section that the paradigm of natural selection can indeed be retained over avery wide range. I will suggest that science advances via a special class of blind discoveries, even though theseoriginate in the intentional or guided action of problem-solving. Although scientists do employ methods and

heuristics which guide their research in view of the data or the problems, these methods and heuristics frequentlylead them to unexpected discoveries. Furthermore, we will see that the "mechanism" which turns a problem-guideactivity towards an unforeseen direction may also be responsible for the revolutionary discoveries which destroythe prevailing order and open new vistas for science.

5.2.2 The Evolutionary-Epistemic Significance of Serendipitous Discovery

In The Sleepwalkers (1964) Arthur Koestler writes: "...the manner in which some of the most important individuadiscoveries were arrived at reminds one more of a sleepwalker's performance than an electronic brain's." The theswhich will be offered here provides a specific interpretation for these words. It will be suggested that radicalscientific changes are very often triggered unintentionally by an innocent problem-solving activity within normalscience. At times, an activity intended to solve a given problem leads to unintended results. This pattern of

discovery might still keep us within normal science. However, it might initiate a process of scientific revolution. fact, blind discovery is a necessary condition for scientific revolution; since the scientist is in general "imprisonedwithin the prevailing paradigm or world picture, he







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would not intentionally try to go beyond the boundaries of what is considered true or plausible. And even if he isaware of the limitations of the scientific world picture and desires to transcend it, he does not have a clue how todo it; he is blind to any territory which lies outside the one governed by his world picture. As we have seen, therare two major ways of gaining new knowledge in a non-blind manner, and both ways will always keep us withinthe confines of our framework of knowledge. By deductive or inductive inference we cannot construct a radically

new conceptual system or world view. Also, the heuristic which helps us in constructing theories in view of theobservational data is part and parcel of our world picture and thus it cannot guide us in transcending the worldpicture.

Thus, one of the major ways of transcending an established state of knowledge is to do it unintentionally whiletrying to solve some problem within the confines of the prevailing paradigm. Indeed, it is well known to workingscientists that a large percentage of research programs in natural science deviate from the original path planned fothem, as if chance "drags" the research program in a new direction, a direction which sometimes leads to thediscovery of a new phenomenon or a new domain of reality. This is how serendipity is realized in natural science(see Ne'eman 1980).

The term serendipity was coined by Horace Walpole. In a letter written to Horace Mann on the 28th of January1754 he says that he formed this term following his reading of a "silly fairy tale" called "The Three Princes of

Serendip" (Serendip is an ancient name for Ceylon or Sri Lanka). The three heroes of this tale "were alwaysmaking discoveries by accidents and sagacity, of things they were not in quest of" (Lewis 1960). The OxfordEnglish Dictionary defines the term as "the faculty of making happy and unexpected discoveries by accident." ThDictionary adds, however, the following sharper definition: "looking for one thing and finding another.'' The lattedefinition refers to cases where one looks for A and finds B. Thus the scientist may act in a guided manner in ordto solve a problemwhile he discovers that the end result provides a solution for another problem, of which he wanot aware. The notion of serendipity implies that the discoverer is aware of the fact that he found B, or at least ofthe fact that he found something unexpected or significant. Thus, science can benefit from a hint given by natureonly if there are open-minded scientists who grasp the significance of the hint. Sometimes the scientist who madethe discovery is not aware of the full significance of his discovery while other scientists complete the task. So inmany cases serendipity in science is a cooperative enterprise.

One of the best known cases of that nature is Fleming's discovery of penicillin. Taking a Petri dish containing abacterial culture he noticed that the loose cover had not been properly set, and a mold had grown over the exposearea. The bacteria, on the other hand, were dead. This may have occurred to other researchers before him and theiconclusion must have been







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to see that lids should be properly clamped. ... Fleming realized that this implied that some molds could kill thebacteria.

A very similar sequence ushered in the "superstring" hypothesis (see for example Schwarz 1985) in physics, whicwas very popular in the eighties. "Dual Models," later shown to represent the quantum excitations of a string, werdeveloped in order to explain the strong nuclear force. One difficulty that appeared to plague the model was theappearance of a spin-two massless state as the lowest physical state of the string's spectrum of excitations. Stronginteractions involve only massive states, and physicists tried unsuccessfully to give a mass to this spin-two state.Yoneya (1974) and Scherk and Schwarz (1974) suggested that the quantum string be reinterpreted as a theory of quantum gravity (since gravity is mediated by gravitons, massless spin-two ''particles") rather than of the strongnuclear interaction. The string tension, the only free parameter in the theory, thus had to be changed by twentyorders of magnitudes! Thus a theoretical construct invented to explain the strong nuclear force led to a deeper understanding of quantum gravity. What is common to the above two events is that a difficulty was turned into adiscovery in an unexpected direction.

I will argue that serendipity in science in not a casual phenomenon. Understanding the role of serendipitousdiscoveries will contribute to understanding the epistemic role of science and its evolutionary character. Serendipsupplies science with its blind edge: The human mind makes plans which have a chance of yielding successful

results only in familiar territories of nature, while serendipity causes science to deviate from its planned coursetowards unexplored domains of nature. Actually, serendipity enables the human mind to transcend establishedframeworks of knowledge, established world pictures.

The requirement of blind discovery is realized in the phenomenon of serendipity in such a way that it does not contradict the fact that scientists do act intentionally and that they direct their efforts towards solving givenproblems. Indeed, when a scientist makes a serendipitous discovery he does not guess blindly. Rather he isoccupied with directed problem-solving in the framework of a research program, employing algorithms andestablished methods. However, since he tries to solve problem A, being aware of problem A, while accidentallysolving (another) problem B, the solution of problem B is, indeed, generated blindly with respect to B. Thus, thediscoverer does act intentionally, being affected by the problem he intended to solve; and yet he ends up making "blind" discovery. By this we reconcile in a straightforward manner the fact that science appears to be a guided

enterprise with the evolutionary model of blind variation. Thus, variations are generated via the activity of problem-solving and are selected by problems which they were not intended to solve. We might describe thesituation by saying that in his problem-solving activity the scientist generates " solutions in search of problems."







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Now, the more profound question is why does science advance in this manner? Why, for example, shouldn'tscientists who wish to find novel solutions to problems (or to free themselves from the prevailing world picture alook for a new one) adopt the Feyerabendian slogan (1978) "anything goes" and start gambling with nature? Whyshould they necessarily expect to find unexpected clues for the understanding of natural phenomena whileconducting "normal" research? Why shouldn't they instead draw their inspiration, for example, from works of art

fairy-tales or wizards? The answer to this question may rest on the stepwise pattern of the growth of science.When one plays with existing building blocks one may discover a new combination or a new configuration whichconstitutes a solution to a problem. Perhaps every new tool is discovered in this way; the chimpanzee, for exampmay discover by innocent playing with sticks that two sticks can be combined to form a new tool which can beused to knock down a banana from a tree. The scientist playing with theoretical concepts while trying to solve aproblem may find a new theoretical construct with which he can solve another problem. A novel form may appeaas an emergent property out of familiar constituents.

What is characteristic of the above pattern of discovery is that the discovered entity is constructed out of existingbuilding blocks. There can be no shortcuts in this process. A building cannot be constructed directly out of protonneutrons and electrons or even out of chemical compounds. First the bricks must be prepared. However, in our context the most appropriate analogue can be drawn from organic evolution: mutations and recombinations aresuperimposed on given genes and on given genetic structures. Following a process of natural selection, the systemmay stabilize with a new genetic structure or a new gene pool. Thus, the new state of stability emerges out of theold one. For example, Homo sapiens arose from some hominid ancestor. It could not have evolved directly from unicellular species, for example. Similarly, a new stratum of knowledge can be constructed out of the prevailingstratum. The new conceptual system or the new world picture is constructed on the basis of some central conceptsand ideas of the old world picture. Quantum mechanics, for example, employs "mutated" concepts of classicalmechanics such as energy, momentum and the Hamiltonian formalism. It is improbable that quantum mechanicswould have been created on the basis of Aristotelian physics or even on the basis of the early version of Newtoniphysics, before classical mechanics was fully developed by Euler, d'Alembert, Lagrange and Hamilton into ageneral dynamical theory. Thus, before a new layer of reality is exposed, and a new stage of knowledge is made temerge, the prevailing layer should be thoroughly explored and the prevailing stage should be fully developed.This principle of "gradualism" or stratification in the growth of knowledge can be accounted for by the evolutinarmodel of stratified stability which will be described in section 7.4.

Hence, discovery by serendipity is essential for the continuity of the advance of science. Variations at the organicand at the scientific levels are not







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generated in vacuo, out of nothing; they are imposed on existing formsexisting genes or existing ideasrespectivelyThus, serendipitous discovery guarantees both independence of problem-solving pressures ("blindness"), andcontinuity.

It should be stressed that serendipity is needed for the advance of science because we conduct our scientificinvestigations from within a given framework: a given conceptual system or a given world picture. Had weadopted the naive empiricist view that we can acquire objective knowledge about the world just by makingunbiased observations, then serendipity would be unnecessary. Serendipity is needed in order to transcend anestablished framework of knowledge.

5.3 Some Implications of the Principle of Serendipity

The theory of science which I propose is a naturalistic theory based on the evolutionist POR. It is evident from thabove discussion that the principle of discovery by serendipity is both descriptive and normative. It is descriptivesince I claim that science in fact advances by serendipitous steps. To be more precise, my approach is explanatoryrather than merely descriptive; we start with an evolutionary theory of science which, on the one hand, is checkedagainst historical evidence and which, on the other hand, attempts to explain scientists' decisions and acts. Myapproach is normative, in the sense explained in the last chapter, since it maintains that in view of the basic

assumptions of our theory, science can make significant progress only by serendipity. Moreover, recommendationfor preparing the mind for serendipitous discovery may be derived from the theory. The theory explains, for example, the fact that scientists prefer theories which yield unexpected predictions. It also may give us some morinsight on two phenomena which characterize modern sciencemathematization and cooperation.

5.3.1 Predictability and Epistemic Profit

The principle of discovery by serendipity sheds light on one of the most important methodological rules for evaluating a scientific theory, i.e. that a theory, besides explaining known phenomena, should generate successfulpredictions of unexpected events or phenomena. Thus, for example, Maxwell's electromagnetic theoryunexpectedly explained the phenomenon of light, and in addition predicted the existence of radio waves,establishing relations between optical and electromagnetic phenomena. This requirement cannot be accounted for

by logic alone. We could perhaps be satisfied by "relegating" it to the psychological arena; yielding an unexpecteprediction has a dramatic effect, like telling the future or performing magic, thus persuading scientists to







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accept the theory. However, in view of our principle of serendipity we can avoid this sort of psychologism. If atheory which was constructed in order to explain A also predicts B, it means that we explain B unintentionally, i.eby serendipity. Namely, in constructing the theory, the scientist could not be influenced by B, i.e. he was blind toB. Thus, Maxwell did not set out to explain light; he calculated the velocity of propagation of electromagneticwaves and was surprised to find that it fitted the known value of the velocity of light. When Dirac constructed his

electron theory, he intended to describe and explain properties of the electron as a quantum-mechanical particleunder relativistic conditions. The prediction of the existence of the positron came as an unexpected by-product. Anew "world," the world of antiparticles, was thus discovered, with the relevant particle-antiparticle symmetry. Ofcourse, after the positron was detected, its existence and its properties became parts of the theory's explanandum.Thus, when we require high predictive power, it means that we require that the process of discovery of the theorywill be as blind as possible to the phenomena the theory eventually explains. The methodological statement that atheory is confirmed by its successful predictions of novel facts can be translated into our evolutionary language bsaying that the theory is selected by facts and phenomena which were not taken into account in constructing thetheory.

In section 3.2, I cited some empirical studies which claim that the requirement of novelty is not always met inscientific practice. However, in view of the principle of serendipity, novel prediction, including prediction of known facts which were not taken into account in generating the theory, becomes a normative requirement (relatito our evolutionist POR).

The ideal case would be when the discoverer generates the theory independently of any factual knowledge. Theprocess of discovery would then be totally blind to any data and if the theory yields successful predictions than th"epistemic profit" will be maximized. Thus, the profit is maximal in a revolutionary change, following a blindtheoretical leap. The epistemic profit can be defined as the ratio of the amount of factual knowledge (or information) predicted and explained by the theory to the amount of factual knowledge invested in constructing ththeory (in practice, of course, there is no simple measure for these "quantities" but in many cases scientists canestimate the ratio). In Dirac's case, the input was just Lorentz-invariance, the output a doubling of the entireparticle world.

In view of our principle, we can explain the negative methodological attitude towards ad hoc modifications

imposed on a theory in order to explain some empirical data if they do not yield new predictions. Ptolemaicastronomy, for example, which explained away every discrepancy between the theory and the facts by employingepicycles, yielded no epistemic profit. Such ad hoc modifications are totally guided by the data, whereas our principle demands that the generation of new variations be blind to some of the data they explain.







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Classifications, such as Linneus' tabulation of the living kingdom, Mendeleev's chart of chemical elements, or theSU(3) symmetry of nuclear particles, are interesting when they predict new speciesso as to be falsifiable. Howevethey then also take on a characteristic of "classifying A and finding B," with B's emergence representing abroadening of the known universe.

A straightforward case of serendipity occurs when the theory yields an unexpected explanation for a knownphenomenon or an unexpected solution for a known problem. For example, as was mentioned above, Maxwell'stheory explained light, Newton's theory of gravitation explained the phenomenon of tides and Einstein's generaltheory of relativity solved the problem of the abnormal behavior of Mercury. Thus, one of the major cases of advance occurs when a new scientific theory solves a known problem which it was not intended to solve. Thediscoverer in this situation solves the problem by using a theory which was constructed or discovered by scientistwho were not aware of the problem.

Thus, serendipitous events can be divided into two main classes:

1. intending to solve (explain) A, but solving (explaining) B instead;2. intending to solve (explain) A, and solving (explaining) B in addition to A.

The case of an unexpected prediction belongs to class (2). Class (2) also includes cases where a research programwhich solved the original problem A continues to evolve and solves problems, explains phenomena or leads toideas which were not dreamt of at the start. Ernest Rutherford, for example, was not satisfied with the idea of ligquanta, since he thought it lacked a physical basis, yet the Bohr-Rutherford model, which developed from hisinitial model of the atom, contributed decisively to the acceptance of this very idea and lended it a high degree ofconfirmation. In general, a research program starts with an initial version of a theory and ends up with a differenversion due to ad hoc corrections and modifications made in the course of the development of the researchprogram. Thus, the later version can be seen as an outcome of the initial version, the initial discovery. The initialversion is intended to solve a given problem, whereas the subsequent versions of a progressive research programsolve additional problems. Hence, when we demand high predictive power we refer not only to a given theory as

stands, but to its potentialities which can become actualized in a dynamic process of modifications andimprovements.

Lakatos treated the research program as the basic methodological entity in science which replaces the static theoras the unit for appraisal. It is clear now that due to its plasticity, the research program or the dynamic theory canalso be characterized as the basic unit which may be subject to serendipitous developments; indeed, as we will sebelow, the dynamic theory is developed in a social setting which provides the conditions for serendipitousdevelopments.







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5.3.2 The Mathematical and the Social Media

There are two characteristics of modern science which make it liable to serendipitous developments: the complexdeductive or mathematical structure of scientific theories and the highly cooperative nature of scientific research.Although these two phenomena seem to take place on totally different levelscognitive and socialthey can be viewas serving a common purpose. Complex mathematical theory may yield far-reaching predictions of which thescientist proposing the theory cannot be aware at the outset. Similarly, a scientist proposing a theory cannot knowin advance how the theory will be interpreted or exploited by other scientists and in what direction the theory wilbe developed and modified by his collaborators or by his successors; after a theory or an idea appears in the publiarena it has a life of its own and does not remain any more under the control of its originator (see againRutherford's case). Thus, the discoverer of a new idea or theory is blind to some of its far-reaching consequenceswhich are obtained either by mathematical development or as a result of its processing by the scientificcommunity. He may, therefore, unintentionally trigger a process which leads to a solution of a problem of whichhe was not aware. The principle of serendipity, therefore, also sheds some light on the epistemic function of themathematical nature of modern science and of the cooperative nature of modern scientific research.

From the viewpoint of the socio-evolutionary POR, the important point regarding serendipity and unintentionalityin science is that it is mainly generated by the social dynamics of science. We encounter here a first example

where the evolutionary model is coupled with the social dimension of science.

5.4 Two Landmarks of Serendipity in Physics

Two of the greatest revolutions in physics can be viewed in the light of the principle of serendipity.

5.4.1 Kepler: The Conscious Sleepwalker

Johann Kepler is one of the heroes of Koestler's Sleepwalkers (1964). 6 Kepler's original problem was to explainwhy there are exactly six planets and why the distances between their orbits are as they are. He was impressed bythe Pythagorean view that the world is governed by mathematical relations and hoped at first to find the solution his problem in the realm of arithmetics. He then looked for the solution in plane geometry. After he failed there

too, he turned to solid geometry. The erroneous number of planets, six, gave him the clue for his model of fivePlatonic solids (the five regular convex polyhe-







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dra) on which he erected the universe. He associated the five perfect solids with the five interplanetary regions antried to find out how the proportions between the five solids are related to the distances between the orbits. After many unsuccessful attempts to explain away the discrepancies between his model and the observational data, heturned to another Pythagorean model: he tried to construct the heavenly motions as "a continuous song for severavoices (perceived by the intellect, not by the ear)." His model of the universe was thus constructed out of the five

Platonic solids and the musical harmonies of the Pythagorean scale. In his attempts to improve his model heneeded exact figures of the eccentricities and mean distances. These were supplied by Tycho Brahe. However,Kepler encountered new problems in Tycho's data and found other parameters to investigate, instead of the relativdistances of the planets. The attempts to solve the new problems eventually led him to the discovery of his threeLaws.

The processes by which he arrived at his Laws involved many sequences of trials and errors. His Pythagoreanmodels stayed in the background and set the framework for his investigations. However, when he struggled withthe data, he arrived at his successful solutions mostly by error or by chance, not always recognizing their value orsignificance. His struggle with the Martian orbit led to the First Law. His first assumption was naturally that Marsorbit is circular. Then he hypothesized an egg-shape orbit. After abandoning the egg-hypothesis, he constructed tMartian orbit by very precise calculations and obtained a circle flattened at two opposite sides. He then found bychance that a simple relation holds between two quantities related to the geometrical from of the orbit. As a resulthe obtained a simple formula expressing the functional relation between the planet's distance from the sun and itsposition (Koestler, 33638). Since analytical geometry was not available in his time, he did not realize that theformula characterizes an ellipse. And yet in his next step, he conjectured that the orbit is an ellipse. He thusdiscovered his First Law twice: once by chance and once by making a hypothesis and testing it. This hypothesiswas almost the only one left for him after he had eliminated all other alternatives. The belief in circular orbits waso deeply entrenched that Kepler could depart from it only by chance or by a lengthy process of trial and error.

The process by which Kepler arrived at the Second Law was hazardous in a different way. He discovered that theradius vector of the earth's orbit sweeps out equal areas in equal times, after making three erroneous assumptionswhich somehow led to the correct result. The assumptions were the following: "(a) that the planet's velocity variein reverse ratio with its distance from the sun; (b) the circular orbit; (c) that the sum of eccentric radii vectorsequals the area" (ibid., 591). With respect to assumption (b), note that he discovered the Second Law first. This

process of "error begetting truth" (to use Koestler's expression), which is characteristic of Kepler's investigations,amounts again to blind discovery. Indeed, if we start a deductive inference







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from false assumptions there are equal chances to get a true and a false conclusion and the inference is thusreduced to gambling.

The discovery of the Third Law came about after many years of search for a correlation between a planet's periodand its distance. Kepler arrived at the Law after innumerable trials. Hence chance did not play a significant role ithe final discovery.

In general, Kepler did not realize the importance of his Laws. Without Newton's theory the Laws looked arbitraryThe belief in circular orbits of heavenly bodies was deeply rooted in the Ptolemaic and the Copernican worldpicture and Kepler could see no reason why the planets would move in ellipses. He treated therefore the First Lawas a necessary evil. The Second Law was treated by him as a computational device. The Third Law was treated juas one more step in the construction of Celestial Harmonies. Kepler thus thought that he was constructing hisPythagorean models, the three Laws being just building blocks in this process. He was partially imprisoned withinthe old traditions of Neoplatonism and Pythagoreanism. He could not therefore realize that he had made a decisivstep in transcending this "paradigm."

In summary, Kepler started with a problem in the old "paradigm," trying to give mathematical sense to the numbof planets and to their spatial distribution. He ended up identifying the mathematical regularities of planetary

motion, a discovery which led eventually to Newtonian Mechanics and to a new paradigm. The framework of Kepler's grand research program was set while Kepler was totally blind to the final data and to the final problemwhich he eventually solved. Although Kepler's original model of the Solar System has left no remnant in physics,the mathematical element of his Pythagorean outlook did become part of the world picture of physics, establishedby the Newtonian paradigm.

We can trace Kepler's train of reasoning from his writings. Other great scientists, such as Copernicus, Galileo andNewton, mainly give us the final results of their investigations, hence we cannot trace serendipitous elements intheir work. Moreover, Kepler is partly aware of the serendipitous nature of his discoveries. He writes in the Prefato his Astronomia Nova:

What matters to me is not merely to impart to the reader what I have to say, but above all to convey to himthe reasons, subterfuges, and lucky hazards which led me to my discoveries. When Christopher Colombus,Magelhaen, and the Portuguese relate how they went astray on their journeys, we not only forgive them, but would regret to miss their narration because without it the whole, grand entertainment would be lost.Hence, I shall not be blamed if, prompted by the same affection for the reader, I follow the same methods.(Cited in Koestler, 318)







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Indeed, if the notion of "serendipity" were available to Kepler he would have used it, since Columbus' story is onof the most prominent examples of serendipity in human history. It seems, therefore, that Kepler felt that the zigzpath of his investigations is significant enough to deserve a description in his scientific writings.

5.4.2 Planck: The Reluctant Revolutionist

Of the two revolutions which shook human thought at the beginning of the twentieth century the quantumrevolution seems to be the more radical. Relativity theory was based on classical theories, whereas the idea of energy quantization and the subsequent principles of quantum mechanics sharply depart from classical physics.(Indeed, nowadays relativity theory is included in textbooks as part of classical physics.) It is suggestive, thereforthat the quantum revolution arose as a result of a serendipitous discovery, whereas the special theory of relativityemerged out of a systematic analysis of known concepts and theories. And yet even in the latter case, a new theoof space and time arose out of measurements that were meant to measure the velocity of the earth through theaether.

Planck attempted to solve a problem concerning the Second Law of Thermodynamics and ended up solving theproblem of black-body radiation. The implications of the discovery had a radical impact on the whole worldpicture of science. Planck treated the Second Law as an absolutely valid principle. Hence he did not accept

Boltzmann's statistical approach, which treated the increase in entropy, asserted by the Second Law, as "highlyprobable" rather than absolutely valid. Planck spent many years trying to clarify and understand deeply the SeconLaw. Before the turn of the nineteenth century he consequently became interested in the problem of black-bodyradiation.

The problem of electromagnetic radiation emitted from a very small cavity in a hot furnace had occupied physicifor half a century. The discrepancy between the observed distribution of intensity of the emitted light for differenwavelengths and the predictions of classical physics was termed "the ultra-violet catastrophe." The curve based othe experimental data showed a very weak intensity for short wavelengths, in the ultra-violet region. The intensityincreased with wavelength until it reached a maximum at a certain wavelength (which corresponded to thedominant color of the light emitted from the furnace) and then decreased and again became very weak in the infrred region.

The theory of black-body radiation was developed by Rayleigh, Jeans, Kirchhoff and Wien on the basis of classictheories: the electromagnetic theory for treating light radiation and Newtonian mechanics for treating the oscillatielectrons within the walls of the furnace, which absorb or emit the light. Since the electrons in the walls must be equilibrium, they have to emit







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and absorb on the whole the same amount of radiation energy. Hence, a third theoryBoltzmann's statisticalmechanicswas incorporated in order to calculate the energy distribution in a state of equilibrium. Only in the infrared region was the curve of the energy distribution (or the intensity of the emitted light at equilibrium) predicted bthese theories indeed similar to the experimental curve. In the ultra-violet region, the intensity increasedindefinitely with decreasing wavelengths. Thus, at least one of the three theories employed for the calculation mu

have been wrong.As mentioned above, Planck's motivation in attacking this problem stemmed from his interest in the Second LawHe had studied problems related to the scattering of electromagnetic waves by an oscillating dipole, which haddirect implications for the scattering of light by the furnace's electrons. His aim was to understand how theradiation within the furnace is kept in a state of equilibrium at constant temperature. He was thus engaged in thethermodynamics of radiation. In the course of his investigations he planned to derive the Second Law for a systemconsisting of radiation and charged oscillators, in an enclosure with reflecting walls. I will not describe here thedetails of these investigations with all their technicalities. I would rather refer the interested reader to MartinKlein's detailed historical article on this subject (Klein 1966). I will only cite a few statements describing the aimof Planck's research program. Klein writes: "The ultimate goal of this program would be the explanation of irreversibility for conservative systems and, as a valuable by-product, the determination of the spectral distributioof black-body radiation." In doing this, Planck hoped to "put an end, once and for all, to claims that the SecondLaw was merely a matter of probability. How was Planck to know that he was headed in a very different directiothat he had started on what he would later call 'the long and multiply twisted path to the quantum theory?'" It isinteresting to note that, in describing Kepler's thought, Koestler speaks about the "zigazag course of his reasoningThis seems a paraphrase on the above-cited words of Planck, taken from his Nobel address. Needless to say,Planck did not succeed in attaining his original goal (just as Kepler did not) and the by-product turned out to be tmajor result of his enterprise.

In the last stage of his long serendipitous path he found that the problem of black-body radiation would be solvedif the energy of an oscillator could take only values 0, E0, 2E0, 3E0..., where E0 = hf, f being the frequency of thoscillations and h a constant to be determined by experiment. Boltzmann had already used this idea as acomputational device, going to the limit E0Þ0. After six years of unsuccessful attempts to solve the problem,Planck decided to employ E0 without going to the limit. Planck explains this move as "an act of desparation" and

he treats it, as he says, as "a purely formal assumption, and I did not give it much thought except for this: that I hto obtain a positive result, under any circumstances and at whatever cost."

Thus, Planck's discovery was doubly serendipitous. First, his original







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goal was related to the Second Law of Thermodynamics but he ended up solving the ''ultra-violet catastrophe."Second, when he arrived at the solution of the latter problem, he employed it reluctantly, without realizing at firstits far-reaching implications. He treated the energy quantization as a computational device rather than as a law onature. He did not commit himself to the existence of quanta as real physical entities. This may remind us of theinstrumentalist spirit of Osiander's preface to Copernicus' Revolutionibus, in which Osiander explains that

Copernicus meant his heliocentric hypothesis to be just a computational device, or Kepler's treatment of his seconLaw. When Planck used his computational subterfuge, he did not dream that it would have immediate implicationin explaining phenomena such as the photoelectric effect and atomic spectra, not to mention the subsequentdevelopments and successes of quantum physics. Einstein was the first to treat quanta seriously, in explaining thephotoelectric effect in 1905.

5.5 Serendipitous Discovery of Natural Phenomena

The discovery of penicillin belongs to a different kind of serendipitous discovery which also contributes as anevolutionary process to the advancement of science, but does not seem to be analogous to blind variation. I amreferring to the discovery of an unexpected phenomenon such as that of X-rays and radioactivity. As we shall seein the following examples, the original aim of the investigation and the final result in these cases were entirelydifferentresearching A and discovering B. The final result, however, was not a solution of a problem but theemergence of a new problem awaiting a solution. The discovery of an unexpected phenomenon in the course of normal-science research is similar to a new environmental pressure exposed by the species' activity (such as amigration or an activity which undermines the ecological balance in the natural habitat). The new environmentalconditions pose a challenge to the species, which has to overcome new dangers and difficulties or exploit newopportunities. There are two possible sources of variation which might enable the species to meet the challenge:

(a) Preexisting genes which are responsible for other functions. For example, in certain insects genes which areresponsible for metabolic functions also confer resistance to insecticides (in this example, the new environmentalpressure came about as an indirect result of the species' activity).

(b) Genes which have been kept in a dormant state, or genes with low frequency in the population, which areactivated by the new environmental conditions and spread through the population, since they endow high survival

value. This is typical of the evolution of resistant strains of bacteria.







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Similarly, novel phenomena may be explained by an existing idea or theory which was generated in order toexplain other phenomena, by a modified version of such a theory, or by an idea or theory that was latent in theexisting paradigm. In the following I will describe three examples of this kind of discovery.

Hertz, Roentgen and Bequerel A series of serendipitous discoveries at the end of the nineteenth century heraldedthe approaching upheaval. The photoelectric effect, X-rays and radioactivity were discovered by serendipity andwere later explained by theories which stemmed from the quantum idea, itself the product of serendipity.

The photoelectric effect was discovered in 1887 by Heinrich Hertz while he was conducting experiments related tthe radio waves which he had discovered in 1886. He used a spark generator to produce the waves. In the course these experiments he discovered by chance that the behavior of the spark gap was affected by the illumination of the electrodes. Other experiments following Hertz's observation showed that a piece of zinc illuminated by ultra-violet light became electrically charged. It was found that the effect is obtained for other metals and other wavelengths of light, provided the wavelength is below some threshold, irrespective of the intensity of the light.The metal became charged because negatively charged electrons were ejected from it by the incidentelectromagnetic energy. It was further found that the speed of the ejected electrons was greater, the higher thefrequency of the incident light. Increasing the intensity of the light beam only affected the number of electronsleaving the metal, which increased proportionally to the intensity. Below the threshold, however, no electron wou

be ejected at any light intensity.

After Planck's discovery of energy quantization, Einstein was very quick to explain the photoelectric effect byconjecturing that light waves of frequency f consist of light-particles, photons, each of which carries an amount oenergy E=hf. The intensity of the beam is proportional to the number of photons. Indeed, if the frequency of a ligbeam is less then some threshold f0, no electron will be ejected, no matter how many photons there are in the beasince none of them has enough energy to knock out an electron.

Roentgen's discovery in 1895 came as a by-product of a long research program triggered by Faraday. Faraday anhis followers had investigated the phenomena which occur when an electric discharge is set up in partly evacuateglass tubes containing two electrodes. Advances in vacuum pump technology led to the accumulation of newexperimental data and to the conjecture that the luminescence which appears near the anode is produced by what

was called "cathode rays." The research program culminated in 1897 with the results of J. J. Thomson'sexperiments showing that the cathode rays were negatively charged particleselectrons. The aim of the researchprogram was







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to understand the nature of the cathode rays. However, before this aim was attained, X-rays were discovered bychance, as a by-product.

Roentgen inserted into the cathode-rays tube a metal plate which formed an angle with the path of the cathoderays. At each discharge within the tube, Roentgen observed a bright illumination of a screen covered with afluorescent salt situated outside the tube. It was evident that the cathode rays could not cause this glow since it habeen previously proved that they cannot penetrate the glass walls. It turned out that the higher the vacuum in thetube, the more penetrating the new rays were.

The explanation of the X-rays phenomenon came later, with quantum theory and the atomic model. These rays arproduced when high speed electrons (such as cathode rays) bombard a target atom and as a result one of theelectrons in an inner shell of the atom is removed. The rearrangement of the electrons in the shells is accompanieby a decrease in energy and an emission of an X-ray photon.

The discovery of radioactivity in 1896 was even more accidental than the above two discoveries. Henri Bequerelknew about Roentgen's discovery and his aim was to find, as he says, "whether the property of emitting rays wasnot intimately bound up with phosphorescence" (cited in Hurd and Kipling 1964, 363). As phosphorescentsubstances he used uranium salts. He used a photographic plate wrapped with two sheets of thick black paper to

protect the plate from sunlight. He placed a plate of the phosphorescent substance on the paper and exposed thewhole thing to the sun. After developing the photographic plate, he saw the silhouette of the phosphorescent platin black on the negative. One day, Bequerel tells us, when "the sun only showed itself intermittently, I kept myarrangements all prepared and put back the holders in the dark in the drawer of the case, and left in place the cruof uranium salt. Since the sun did not show itself again for several days, I developed the photographicplates...expecting to find the images very feeble. The silhouettes appeared on the contrary with great intensity"(ibid., 365). After conducting further experiments he came to the conclusion that the phenomenon was not causedby radiation emitted by phosphorescence, and that the uranium salt itself emits radiation.

It was only after the famous experiments of the Curies that it was understood that radioactive elements such asuranium and radium disintegrate and change their chemical identity. Bequerel's discovery led, therefore, to theconclusion that chemical elements are not immutable and opened the way to the nuclear domain.

Let us now try to compare the theoretical explanations in these three cases to the above mentioned two possiblesources of variation enabling a species to meet new environmental conditions. The understanding of thephotoelectric effect is analogous to case (a), since it employed the idea of the quantum, which was invented for adifferent purpose and was not treated seriously until 1905. The understanding of X-rays is also analogous to case(a), since the phenome-







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non was explained by atomic physics, which had evolved from Planck's and Einstein's ideas and which wasintended to explain other phenomena. Radioactivity was explained by employing ideas borrowed from chemistry,by using a heuristic of the Meyersonian kind for constructing matter- theories (case (b)).

Thus, a discovery of a novel phenomenon may foster theoretical advance, just as changing environmentalconditions may foster evolutionary progress. In each of the above examples the resulting theoretical advance wasserendipitous, since the new phenomenon was exposed following an experimental activity guided by an establishetheory or by an entrenched conception, whereas the end result was the adoption of another theory or conceptionwhich superseded the original one. In other words, the original research employed a guiding theory or conceptionto solve a given problem, whereas the end result was its rejection or a radical change imposed on it. Hence theepistemological significance of such a discovery is in triggering the process of replacing an entrenched conceptioor theory. This sort of serendipitous discovery, just as the blind discovery of new explanatory ideas and solutionsof problems, serves, therefore, as a means of transcending an entrenched framework of knowledge. The discoveryof an anomalous phenomenon which is unexpected in view of the entrenched background knowledge must, indeebe serendipitous. In addition, as the example of the discovery of penicillin indicates, such a process sometimes cabe viewed as a serendipitous discovery of a solution of a practical problem. The discovery of penicillin solved anacute medical problem. The discovery of X-rays and radioactivity solved experimental problems within physicsitself by providing new methods for probing the structure of matter.

We would expect that discovery of new phenomena by serendipity will be more frequent in sciences which do noyet have a fully developed theoretical system to guide research. Indeed, this is very common in certain areas of thmedical sciences, such as drug research; the example of the discovery of penicillin by Fleming is repeated againand again in this field. It has also typically occurred, as we saw above, in fluid stages in the evolution of physics.Other classical examples are: Galvani's discovery leading to the electric battery, Brown's discovery of molecular motion (two cases of interdisciplinary serendipity), and Oersted's discovery of the nature of the connection betweelectricity and magnetism. Other examples are described in Cannon (1961), Shapiro (1986), Roberts (1989) andKohn (1989).

5.6 Cultivating Serendipity

There can be no method for generating serendipitous discovery, since a discovery generated by employing amethod which is directed towards the particular product of discovery cannot be unintentional. However, althoughis an







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unintentional phenomenon, we can enhance the chances for its occurrence by preparing appropriate conditions forit; we can cultivate it. Below I will propose some "rules," or recommendations, for the cultivation of serendipity.Most of them are practised intuitively. However, the principle of serendipity sheds new light on them. We caninterpret the role of these rules as helping to "prepare the mind" for serendipitous discoveries.

(a) The first rule or recommendation would be to adopt the policy of setting the target by encircling the spot after the arrow has hit it. This recommendation is well known in its negative connotation. The principle of serendipitysheds a positive light on it. Fleming adopted this policy when his bacterial culture was contaminated by mold andthus spoiled his original experimental setting. What could be regarded as difficulty, was converted by Fleming inta great discovery. Kepler also acted in this manner. He started by constructing a model of the universe out of thefive Platonic solids and the musical harmonies of the Pythagorean scale. His original goal was to give mathematicsense to the number of planets and to their spatial distribution. As we have seen, his unsuccessful attempts led himto solve other problems. He ended up identifying the mathematical regularities of planetary motion. The discoverof the superstring came about as an opportunistic exploitation of the difficulty which arose by the appearance of the undesirable spin-two massless state which was inappropriate for strong interactions, i.e. by reinterpreting thequantum string as a theory of quantum gravity. Thus, sometimes the scientist is engaged in unsuccessful attemptsto solve a problem. He stubbornly tries again and again to proceed with Sisyphean efforts. If he were alert to thepossibility of solving other problems along the way, he might find out that his efforts are not in vain and thatanother problem could be solved by the results already achieved. In this way an obstacle may turn into a victory.

George Polya describes a typical situation which the problem-solver encounters when he is working on a problemA which is connected to another problem B. The study of problem B may bring him near his goal of solving A.Dealing with B "may stir his memory and bring into the surface elements that he can use in solving his originalproblem A" (Polya 1965, 90). Polya is employing here concepts which fit Simonton's account of the incubationprocess to be discussed in the next chapter. The dilemma which, according to Polya, faces the problem-solver iswhether or not to invest time on B. This dilemma would not arise if we believe in the principle of serendipity. Wcannot know in advance which problem is related to A in the sense that dealing with it may help solving A. Thiscan be discovered only in hindsight. Serendipitous discovery happens when one does not expect in advance that Bis related to A. Hence, the answer to the above dilemma is that if one wishes to benefit from serendipity, oneshould not deal with B only because it seems to him related to A. The serendipitous situation is an opposite one:

when one's







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goal is solving A, one might serendipitously solve a different problem B, which he did not intend to solve.

(b) The second recommendation is derived from the first: we have to be engaged in solving more than one probleat a time, to be engaged with problems which do not seem to be related to each other, and to be aware of as manproblems as possible. And in general, one should not restrict his domain of interest to his current narrow area of research. We have here a definite reason for being broad-minded.

(c) The next advice, which is directed to the scientific community, is to encourage freedom of research. Thisdemand does not stem from a sheer liberal-idealistic attitude. It can be justified, or rather explained, from theviewpoint of the principle of serendipity. According to this principle, good science should not be controlled bypreconceived goals. A government agency might support research for solving a given problem. However, thescientist should not be possessed by the initial goal. He should be alert to different problems which might besolved by his research program. Hence, we arrive at the seemingly paradoxical conclusion that in order for societyto benefit from science, science should not be forced to solve the problems of society or to be controlled bysociety.

Thus, the principle of serendipity has direct implications for science policy. First, basic research should not andcannot be directed from outside the realm of science. According to Yuval Ne'eman:

We can only direct towards targets we know, but the more important ones are the unknown. A society or a statethat decides to concentrate on 'relevant' aims is in fact stopping progress. This happened in the USSR in theThirties to Fifties, in China during the 'cultural revolution' (which actually almost destroyed a culture) and even inthe West around 196570 in a milder fashion. (Ne'eman 1988)

The same advice should be directed towards the scientific community's policy for the granting of funds accordingto submitted proposals:

In preparing such a proposal the researcher can only use extrapolation as an input. The really important advancesthat will result from his proposal are those of which he has no inkling. The grantor should not take the proposalseriously. He can only judge by past performance whether or not this researcher will detect something unexpectedin the course of his research. (Ibid.)

In the research report which the supporting agency asks the researcher to submit at the culmination of the researcthe following question should be







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avoided: "to what extent have you achieved the goal set up in your research proposal?" There is an essentialdifference between an engineering project and scientific research: an engineer is supposed to achieve a pre-determined goal. For example, if an aircraft is designed for certain purposes, then the project will not be considersuccessful if the aircraft will not fulfill the predesigned task, even if the engineer discovers that it can performanother task.

In general, the above recommendation is not followed in the scientific community. Indeed, in a reaction to our principle of serendipity, James Baggot writes: "today's patterns of science funding are reducing the opportunitiesfor making...serendipitous discovery." What would encourage this kind of discovery is "the freedom to deviatefrom a proposed research programme when such a discovery is made or appears possible" (Baggott 1990).

(d) It should be stressed that the principle of serendipity does not imply anarchy of the "anything goes" kind. Inorder to enhance the chance for serendipity, scientists should be engaged in problems which appear on the currenlevel of scientific research, employing the most advanced knowledge and methods. Indeed, in arriving at the ideaof the quantum, Planck employed the latest ideas and mathematical tools of the time and had been engaged insolving problems in the current paradigm. This is directly implied by the conceptions of stratified stability andgradualism in scientific progress, which will be discussed in Chapter 7.







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Chapter 6Intrapsychic Processes Of Creation

Even sleepers are workers and collaborators in what goes on in the universe.Heraclitus, Fragment 124 (ibid. 79 )

No doubt that some major scientific discoveries are generated by individuals who set out to solve a problem or toconstruct a theory. In these cases, the process of discovery seems to be both intentional and creative. Newton'sdiscovery of universal gravitation, Fresnel's discovery of the wave nature of light and Einstein's discovery of special relativity, are examples of revolutionary discoveries which are apparently intentional. (Although theanecdote about Newton's arriving at his theory after observing a falling apple suggests that chance may have beeninvolved in his discovery). This seems to undermine the evolutionary picture of science. However, even processelike these may be accounted for by the natural-selection model. But this time the natural selection is below thethreshold of awareness.

There are some indications that the brain brings order to information and creates an inner thought model of the

world during rapid-eye-movement (REM) phase of sleep (Winson 1992). As Karel Pstruzina puts it:

During REM-sleep...our brain slips into natural process in which the present day information becomesinvolved with our endoceptive structure of thinking. Thinking that arises during REM-sleep is inarticulate.It is not eas[y] or convenient to become aware of it. ... Behind the shut eyes there run products of our imagination, thinking is diverted to remote association, and free imagination enters in. ... This sort of knowledge touches the limit of our mental faculties. (Pstruzina 1992)

This is the kind of process I am referring to when I am talking about involuntary natural processes of creation.Dean Keith Simonton's theory of creativity






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(Simonton 1988) 7 may acount for this phenomenon. Simonton provides us with a theory about the creativeprocess which takes place in the mind of the scientific genius. But we can treat the theory as describing theintrapsychic process of creation in generalnot only in the genius' mind. Simonton's theory postulates the deepmechanism which is responsible for the creative process of incubation. The theory explains some typical cases of serendipitous events which occur when the scientist's mind hosts the incubation process.

The creative process is modeled on Donald Campbell's paradigm of blind variation and selective retention and it idivided into the following personal and social components.

a)An intrapsychic process (taking place within the individual), which is comprised of two stages:

a1: The chance permutation of mental elements.a2: The formation of stable configurations (internal selection).

b)Interpsychic (interpersonal) processes: the communication, social acceptance and socioculturalretention of selected configurations (social selection). Let's look at each of these in more detail.

6.1 A Psychological Theory of the Creative Process

6.1.1 The Chance-Configuration Model

a. The Mechanism of Chance Permutation The fundamental creative process postulated by Simonton is a naturalselection process taking place in the scientist's mind. The raw material for the process are "mental elements,"including cognitive entities, such as facts, principles, relations, rules, laws, formulas and images.

These mental elements can be deliberately evoked by retrieving them from memory. They can also be evokedinvoluntarily, e.g. via an association. They need not be consciously entertained; they may be processed at theperiphery of consciousness. In fact, there are grades of consciousness. In this connection, Simonton quotes Einstesaying that what we "call full consciousness is a limit case which can never be fully accomplished."

New combinations of mental elements are formed by chance in the scientist's mind. This is the basis of the creativprocess. Simonton calls these combinations "chance permutations." He borrows this term from probability theorysince the order of mental elements in the set is important. Indeed, in permutations the elements' order is importantwhereas in combinations it is not. For example, one kind of creative product is a mathematical proof, whichconsists of an ordered set of logical steps.







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The chance permutation theory leads Simonton to conclude that "in a loose sense, genius and chance becomesynonymous" (33). With this, the heroic image of the discoverer gets another decisive blow. The discoverer isequipped with merely an efficient gambling machine. However, later we will see that, according to this theory, it not chance alone which generates discoveries.

b. The Formation of Configurations The selection process takes place on both the intrapsychic and social levels. Ithe intrapsychic process, the most stable permutations, called configurations, are selected among the mentalaggregates formed in the chance-permutation process. The discoverer cannot become aware of the non-stablepermutations; only the stable permutations are processed consciously. Since a configuration is relatively stable, itmay be viewed as a new mental element which can serve as a unit in forming new combinations. Here Simontonemploys atomistic and chemical metaphors: the process of forming a stable configuration is analogous to thechemical process of forming molecules from atoms. Mental elements tend to form stable units when they haveintrinsic affinities for each other. And "large clusters of elements also can spontaneously form highly orderedarrangements out of chaos." In order to illustrate this process, he cites Campbell's example of crystal formation ouof a dissolved chemical. We can also resort to a geometrical metaphor, where a simple geometrial figure is formeout of juxtaposing several geometrical figures which match each other.

What is the principle of selection? A permutation is stable if it is sufficiently coherent. The notion of coherency

here is too broad to be specified in more detail. It is context-dependent. Only if there is a shared sense of coherenin a community of scientists, may a configuration generated by one of its members be widely accepted. Theprinciple of selection cannot be a priori specified. The sense of coherence would depend on the prevailing worldpicture, standards of scientific explanation which have been internalized by the discoverer, as well as on hispersonal preferences. Hence, Simonton's talk about "natural" or "intrinsic" affinity between two mental elements inappropriate, since these notions have an objectivist or absolutist flavor.

Stable permutations may be inventive as well as imaginative. When the stable permutation arises by chance, it isrestricted neither by logic nor by experience. It is thus fully imaginative. If on the other hand the configuration isformed by applying logical or mathematical procedures, it is inventive, since it is generated intentionally, with theguidance of rules (yet, as we have seen, there are inventions which are generated unintentionally). A genuinecreative process generates new configurations by chance. Simonton calls configurations formed in a rule-governe

manner, via mathematical or logical procedures, "a priori configurations," whereas "a posteriori configurations" athose arrived at via experience. Both a priori and a posteriori configurations are not genuinely creative.







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The conjecture about the wave nature of light is given as an example of a creative configuration. Here theassociation was formed by making an analogy between the two a posteriori configurations corresponding to theempirical character of light and the wave phenomenon. Another example is the isomorphism between the a prioriconfiguration represented by the Balmer formula and the a posteriori configuration representing the spectral linesof hydrogen. In both examples, there was an element of chance in the creative process. The conjectures about the

wave structure of light or the Balmer formula for the hydrogen spectrum could not be straightforwardly derivedfrom the data. Both new configurations resulted in a greater self-organization of the available information. Thenew configurations were stable since they united diverse pieces of information in a coherent scheme. Such aunified scheme occupies less memory space and increases information-processing efficiency. Thus, Simontonsuggests that ''the human intellect is programmed to self-organize its contents into hierarchical structures in whichknowledge is most efficaciously distributed" (14). Self-organization, rather than the goal of truth, drives thecreative process in science. Simonton subsumes under the title of self-organization, notions such as regularity,structure, order, harmony and beauty.

c. Interpsychic Processes Not every configuration formed in the above manner in the mind of an individual will baccepted as a scientific discovery. Two conditions are necessary for this. First, the configuration should beexpressed linguistically or mathematically in order to be suitable for communication. Second, the configurationshould bring about self-organization in the minds of the other members of the scientific community.

Hence, if the configuration is not yet expressed linguistically or mathematically, for example if the configuration a visual image or a vague metaphor, the discoverer should verbalize or explicate it. It should be presented in thelanguage which is acceptable in the particular discipline. The configuration is thus converted into communicationconfiguration. In some cases this process of articulation is by itself creative. For example, the discoverer maycreate a new mathematical language in order to convey his ideas, as did Newton when he created Calculus in ordto express his physical ideas.

The acceptance of the proposed configuration depends on various factors. For example, other members of thecommunity should recognize the problem for which the new configuration is supposed to provide a solution as agenuine problem. Other members should also share a common repertoire of mental elements, such as facts,theoretical principles and methods. Rhetorical and stylistic elements are also important.

6.1.2 Phenomena Explained by the Theory and Evidence for Its Support

Simonton seeks support for his theory from introspective reports of some eminent scientists which provide us withevidence about the three compo-







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nents of the personal process of discovery: the nature of the mental elements, the operation of the permutationmechanism and the unexpected act of illumination or the eureka event, when a configuration emerges and floatsabove the threshold of awareness.

For instance, in describing the early stages of thought, Einstein employs notions which correspond to Simonton'smental elements and to the act of combination: "The psychical entities which seem to serve as elements in thoughare certain signs and more or less clear images which can be 'voluntarily' reproduced and combined. ... Thiscombinatory play seems to be the essential feature in productive thought" (quoted on page 25). Einstein claims thonly prelinguistic elements participate in the permutation mechanism: "the words of the language, as they arewritten or spoken, do not seem to play any role in my mechanism of thought." The transition to a communicationconfiguration is made in the second stage of the process, after a stable configuration has been reached:''conventional words or other signs have to be sought for laboriously only in a secondary stage, when thementioned associative play is sufficiently established and can be reproduced at will" (2526). Simonton suggeststhat the more original the chance configuration, the more difficult the task of communicating it to other scientists.The early phases of a genuinely creative process emerge from prelinguistic imagery.

Support for the theory is provided also by Poincaré who draws from his experience of discovering the Fuchsianfunctions. He describes the process of forming a configuration via a vivid mechanistic metaphor. "Ideas rose in

crowds; I felt them collide until pairs interlocked, so to speak, making a stable combination" (quoted on page 29)He makes the analogy between these colliding ideas and the colliding molecules in the kinetic theory of gases. Indescribing the mechanism of producing stable combinations between mental elements or ideas, Poincaré resorts tothe mechanism by which the hooked atoms of Epicurus are combined; the hooks presumably represent the affinitithat certain mental elements have for each other.

From the above descriptions we see that the notion of a mental element is too vague and the mechanism of formicombinations is very metaphorical. But this should be expected, since the experience from which this notion isderived barely passes the threshold of awareness. Nevertheless, since several eminent discoverers have provided uwith similar vague descriptions, we cannot dismiss the phenomenon. In any case, if we adopt the view thatinferring a theory from the data (such as that provided by the above descriptions) only gives it initial plausibilty (oprior probability in the Bayesian approach), we would treat the chance-permutation theory as a plausible

hypothesis which has to be confirmed by further indirect evidence. This is exactly what Simonton is trying to dothroughout his book.

Descriptions of scientists and problem-solvers suggest that in many cases the initial efforts to solve a problem setup a subconscious process of







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conscious associations, and the analytical type, whose mental elements are linked by a smaller set of stronger,predominantly conscious, associations. The two styles of thought are sometimes called divergent and convergentthinking, respectively. The analytical type has mental elements clustered into compact configurations arranged in hierarchical order, where there are strong links between elements within a configuration and weak links withelements in other configurations. The intuitive type has many interconnections between mental elements, a higher

percentage of them being infraconscious. In ordinary discourse we would say that the intuitive type is moreimaginative, whereas the analytical type in more restricted to passing from one element to another by logical andexplicit connections. The "richness of associative interconnections provides the psychological vehicle for chancepermutations." In the intuitive type's mind each mental element is linked with many other elements via direct andindirect routes so that a larger amount of permutations may be generated. Since there are many nearly equiprobabpossibilities of linking each element to other elements in the network, the permutations thus generated can beregarded as random, or at least quasi-random. The intuitive type is more alert than the analytical type to "novel ounusual stimuli on the fringe of focused attention." This what makes the intuitive type more "susceptible toserendipity"namely, this type of scientist is alert to problems which are beyond his focal awareness. Consequentlyin the course of looking for a solution to a given problem, this scientist might notice that he arrived at a solution a problem different from the one originally under investigation. Or in attempting to solve a given problem, hemight hit upon a solution which was generated in response to another problem. Since many of the chance

permutations are based on infraconscious associations, the intuitive discoverer is not always fully aware of the wthe discovery was arrived at, and may be unable to reconstruct it correctly. In fact, as we have seen, in manytypical cases, he reconstructs it as if he had arrived at the discovery by reason or inference.

The following "law" is implied by the above model: "the stronger are the associations that tie the elements of aconfiguration, the fewer will be the active bonds among the configurations." This means that the intuitive typegenerates a set of configurations which are more diffuse in the sense that the interconnections between the elemenwithin a configuration are weak, and the configurations are not sharply distinct from each other. However, intuiticonfigurations may be systematized or explicated to become progressively more clear and distinct. The moreadvanced the process of explication, the more consolidated the configurations become and the less they areinterconnected. The result is that there is less room for creativity through chance permutation. This phenomenonhas implications for both the individual scientist and for science. The individual scientist becomes less creative ingiven field, the more clear and distinct elements of knowledge he has acquired in the







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field. And it is well known that the more advanced a science, the less room left in it for creativity.

6.2 Implications of the Theory

6.2.1 Explaining Serendipity

The theory of chance permutation provides us with a possible mechanism which explains serendipitous discoveryWhen the process of incubation for solving a problem has already been evoked, some external stimulus might theintroduce new mental elements or associations which provide the missing pieces in the "jig saw" puzzle leading ta stable permutation. Thus, the process of incubation may require the injection of some additional elements into thblend in order to generate a novel configuration.

The prototypical serendipitious discovery occurs when one tries to solve problem A but unintentionally solvesproblem B. Here the external stimulus for generating the new configuration which solves B is provided as a by-product of the attempts to solve A. According to Simonton's picture, any external experience may provide theexternal stimulus. Yet, in science the more specific kind of serendipity, that is, when one finds the solution whiletrying to solve another problem, is very common. Indeed, in the last chapter I argued that the discoverer is morelikely to solve problem B while being engaged with another scientific problem A, preferably in the same field,

rather than when drawing his inspiration from extra-scientific sources. The reason I gave for this was related to thgradual manner in which scientific knowledge grows, each new layer of knowledge being constructed fromelements belonging to the present layer. The theory of chance permutation provides us with a sharper reason for this: in being engaged with current scientific research, the discoverer is more likely to hit upon mental elementswhich have "intrinsic" affinities for the elements participating in the process of forming the solution of B. As Polydescribes it: when the problem-solver is working on a problem which is connected to his original problem, he ismore likely to "bring into surface elements that can be used in solving his original problem" (ibid.). This isespecially true in modern science since it employs very specialized and abstract concepts and principles whichdiffer significantly from those used in everyday life.

When Archimedes noticed the overflow of water in the bathtub, he hit upon the missing element of the solution toa problem which had already occupied his mindthe problem which had been posed to him by King Hieron of

Syracuse. Almost everyone who had ever had this sort of experience, including Archimedes himself, had noticedthis phenomenon before, but only after the process of solving the problem had been evoked in Archimedes' mindcould he benefit from this experience in solving the prob-







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lem. Since he was engaged with a problem which was not far removed from everyday experience, he could hitupon the clue for solving it while being engaged in everyday activity. However, the particle physicist, for exampleis not likely to encounter in everyday experience a missing piece for solving a puzzle which is couched in terms quantum fields, quarks, etc. In order to have a chance to find a clue for solving such a problem today's physicisthas to be engaged with research in particle physics or in any field which employs physical or mathematical

elements which might have "intrinsic" affinities to the elements used in particle physics.In view of the above picture, we can interpret Pasteur's claim that chance favors the "prepared mind." We can giva weaker and a stronger interpretation. According to the weaker interpretation, the discoverer's mind is prepared fsolving problems of a certain kind if it is equipped with the appropriate mental elements and the appropriateassociations which enable the process of chance permutation to generate solutions of this kind of problem.According to the stronger interpretation, the discoverer's mind is prepared for solving a specific problem if he hasalready entered an incubation process for solving the problem so that he can benefit from appropriate hintsas if thincubation process opportunistically "attracts" the missing element which was generated for another purpose.Poincaré provides us with a tangible description which may be interpreted as referring to the process of preparingthe mind in the strong sense. Employing his metaphor of hooked atoms, he says: "the role of the preliminaryconscious work...is evidently to mobilize certain of these atoms, to unhook them from the wall and put them inswing." (quoted on page 31). The discoverer thus prepares his mind by starting this process of "free-associativeprocedure'' which then goes on autonomously, ready to pick up the first clue for completing the task.

Thus, although, as Simonton says, "the permutation process is 'blind' in the sense of being devoid of any a prioriknowledge of the most profitable direction to search for combinations" (32), the process does not take place invacuo; the raw material for the creative process consists of the "atoms hooked in the wall." The mental elementsand associations with which the prepared mind is equipped constitute the "a priori" component of the process of discovery. They constitute the raw material for the chance-permutation process.

Darwin's case illustrates the notion of the prepared mind. Darwin arrived at his theory of natural selection via along process. He tells us in his Autobiography that after reading Malthus' Principles of Population in September,1838, "being well prepared to appreciate the struggle for existence...it at once struck me that...favourable variationwould tend to be preserved, and unfavourable ones to be destroyed. The result of this would be the formation of

new species. Here, then I had at last got a theory by which to work" (Darwin 1958, 120). Lamb and Eastoncomment on this: "The influence of Malthus was unlikely to have occurred as an instantaneous event but was







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rather a contribution to a lengthy process of thought." Darwin came to Malthus not for the first time. But this tim"by September 1838 his researches were at a stage when he could assimilate Malthus's insights" (Lamb & Easton1984, 65).

Thus, when we say that the time was ripe for the discovery, we mean two things: First, that at the time of thediscovery the appropriate background knowledge had been accumulated, i.e. the "collective mind" of the scientificommunity was prepared for the discoveryfor its generation and acceptance. The ideas of selective breeding,Malthus ideas and various evolutionary models were all in the foreground at the time Darwin had his eurekaexperience. Second, that the mind of the discoverer was prepared, in the strong sense, for the discovery. So, in asense, both the collective and the individual mind were prepared.

Yet, the range of creativity of the chance-permutation process is restricted by the structure of the network of mental elements. The initial conscious efforts to solve the problem trigger the process by evoking a train of associations which lead to the mental elements which participate in the process of chance permutation. Thesemental elements are not picked up totally at random since they are interconnected through a network of associations. The initial mental elements and associations determine, through the structure of the network, thesubset of elements which will participate in the process of chance permutation. Thus, if the system is closed, therewill be no opportunity to arrive at a novel element or association.

However, an incubation process which ends up following an external stimulus may lead to a radical novelty. Aftethe incubation process has reached a "pending state," where it is awaiting an external stimulus, or a new piece ofinformation, which will bring about a transition into a stable state, the missing element, generated through anactivity which has not been aimed at solving the original problem, may be caught up "opportunistically." The finastep, which is the decisive step in the process, is not affected by the problem-solving pressures. Thus, due to theopenness of the system, serendipitous discovery can take place, leading to radical novelty.

6.2.2 Individual vs. Collective Creativity

When Simonton introduces the social component of creativity, he does not take into account the full implicationsof the social dynamics responsible for the formation of configurations. He still refers to personal factors and treat"creativity as a form of personal influence over others and therein as a special variety of leadershipsocioculturalrather than political, military, or economic" (22). The question is what about a great discoverer that is recognizedas such only posthumously? For instance, in the case of Mendel, the discovery was eventually accepted despite thunsuccessful attempts by the discoverer to







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convince his contemporaries. Thus, the above description is not appropriate for cases where a great discovery isaccepted for reason other than efforts made by the discoverer. It also does not account for cases when the discoveris a cooperative-historical process. Planck, for example, did not believe in the reality of quanta; only after thediscoveries made by his successors was the idea of the quantum widely accepted.

Simonton maintains that "collaboration per se may not necessarily contribute to creative productivity...collaboratimay contribute to the elaboration and verification of an initial creative idea, but the original concept normallyarises from an entirely intrapsychic chance-permutation procedure" (5455). The following objection may be raiseagainst this claim. The individual scientist does not employ only mental elements and associations stored in hismemory. Interpersonal interaction provides important external stimuli, such as new ideas, clues and missingelements, to the intrapsychic process of chance permutation. The basic process in this case may still be viewed asan intrapsychic process of chance permutation or incubation, nurtured by communication with other scientistsbutthe ideas channeled from external sources are sometimes essential to the process. The discovery may depend uponthe integration of these external ideas with the intrapsychic associations network.

Furthermore, a configuration proposed by an individual scientist may not only be subject to "elaboration andverification"; it may also undergo substantial changes via a cooperative and/or historical process. The final creativproduct in this process might have only the slightest resemblance to the original idea proposed by the individual

who initiated the process. The social process might also be viewed as a chance-permutation process on theinterpsychic level, where many individuals in a given community of investigators propose their ideas which arequasi-randomly combined with other ideas to produce new ideas, most of which are rejected at first sight and onla few of which survive for further scrutiny. This process may eventually yield a final configuration which isaccepted as a discovery. Thus, the act of acceptance is not applied to a finished product. Acceptance is built in thdynamic process of creating the product of discovery. Hence, in the process of discovery, elaboration andverification cannot be sharply distinguished from the process of creation, as we have already observed.

Another related claim (5355) is that there is an "intrinsic motive to engage in scientific research for its own sake"which "ensues from the more fundamental drive toward self-organization" and ''the successive discovery of chanconfigurations is accompanied by personal satisfaction, or subjective pleasure." Or: "The quest for self-organization...provides a powerful incentive that shoves aside other motives." Against this view about "the inhere

superiority of intrinsic over extrinsic motivation," we may state the motive of obtaining recognition by thescientific community. According to the former







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view, self-organization, rather than truth, drives the creative process in science. According to the latter view,acceptance and recognition by the scientific community, rather than the quest for truth, is the main goal whichdrives the creative individual in modern science. This is the basis of social epistemology. An idea may be accepteby the scientific community (by the leading figures or by the establishment) and yet it does not necessarily bringabout self-organization in the mind of every individual in that community. Thus, both intrapsychic processes and

epistemic cooperation may contribute to the process of discovery.Simonton does consider the view that science is a more democratic enterprise than seems to be implied by histheory of chance permutation (94). If "the scientific edifice is built piece by piece using small bricks mostly laid bundistinguished craftspersons" and if "anyone with the appropriate training in the trade of science may participatein the construction of even the most impressive monuments," then ''the term scientific genius may provemeaningless." But this is exactly what is implied by the chance-permutation mechanism operating on the sociallevel. Ideas proposed by numerous scientists are continuously combined and recombined in this cooperativeenterprise.

Thus, Simonton seems to reject the idea that there is a chance-permutation process on the social level. Yet, hesupplies the most decisive argument for not ignoring the contribution of the mediocre to the process of scientificadvance: "Just as we cannot have winners of a race without having losers too, so we cannot really have successes

in the absence of failures. What is required, according to the current theory, are many variations that are open tosociocultural selection" (97). We can understand the above statement as saying that a successful idea is notobjectively or absolutely a true idea, but an idea which has been accepted according to current standards or as aresult of the social dynamics. Hence, the unsuccessful individuals are as important for the selection process as thesuccessful ones. Moreover, if we treat sociocultural selection according to the model of (quasi-) random variationwe would say that the configuration which is accepted, or which proves successful, is not necessarily generatedwith a guidance of method or logic; otherwise it would not be random. If the winning configuration is a product ochance, then we cannot attribute it to the wisdom of the discoverer. Yet, method or logic are required for theselection of variations. We may say therefore that the mediocre contributes to the generation of variations, wherethe analytical genius plays an important role in the process of selection.

6.2.3 Cultivating the Creative Potential

Innovation can be cultivated when the discoverer is isolated from the community so that he is not committed to ttradition, or when his mind is fertilized by ideas from other fields. The tension between tradition and innovationcan







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be accounted for by the chance-configuration theory in the following way (115). There are two conflictingrequirements for cultivating the creative potential. On the one hand, the scientist's mind must be equipped with threpertoire of mental elements shared by the community of investigators. This body of mental elements must be incomparable condition of disorganization so that the scientist would share the same problems with his collegaues.On the other hand, he must be ready to depart from this shared body of knowledge and problems. The creative

potential of a scientist who is not ready to depart from tradition would be diminished for two reasons. First, thenumber of mental elements would be limited by the tradition. Second, the chance-permutation process would beconstrained by the strong ties already existing between the prevailing mental elements so that there would not bemuch room left for generating chance associations. Thus, an essential tension exists between tradition andinnovation (Kuhn 1963) i.e. between the conformism required for social acceptance and the non-conformismnecessary for generating novel chance permutations.

One way of bypassing tradition and nurturing the creative potential is through sociocultural or professionalmarginality. A scientist who is isolated from the scientific community is less constrained by tradition. Sometimes"ignorance...allows the chance permutations to proceed afresh" (127). But ignorance is not always an asset sincescience cannot advance if it always starts afresh. This would not allow the combinations to become cumulative. Amajor way through which scientific knowledge grows is when configurations become themselves elements whichparticipate in the combinatorial play. The discoverer should therefore be equipped with the repertoire of configurations that have already been generated in the field.

As we will see, another social means of nurturing the creative potential is through what M. J. Mulkay calls"intellectual magration" (Mulkay 1972). A scientist who switches fields brings along ideas and methods from hisoriginal field to the new one, thus widening the range of associations. Simonton mentions two examples. Kekulé'sinterest in architecture was perhaps the motive behind his developing the structural approach to organic chemistryHelmholtz, who became engaged in medicine, was also interested in physics and this led him to the invention of the ophthalmoscope. Thus, intellectual migration and, more generally, cross-fertilization between differentdisciplines nurtures creativity.

6.2.4 Multiple Discovery

The traditional explanation of the multiple discovery phenomenon is based on the assumption that the process of discovery is predominantly affected by the prevailing world picture or the zeitgeist, rather than by intrapsychicfactors. If there is a common world picture shared by the members of the scien-







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tific community, certain discoveries are inevitable since these discoveries are "in the air." Consequently, severalscientists who share the common repertoire of ideas and try to solve the same problem may arrive at similar solutions. Simonton thinks that the zeitgeist interpretation seems to contradict the chance-permutation theory, sincthe zeitgeist view amounts to sociocultural determinism which does not allow random variation. However, thezeitgeist view does not necessarily entail generation of predetermined ideas or permutations. The zeitgeist may

entail only common standards of selection, while generation might still be quasi-random. Quasi-randomness meahere that the mental elements out of which permutations are randomly formed belong to the common repertoire oideas. The zeitgeist or the tradition limits only the range of variationsit does not predetermine them.

The "multiples" phenomenon seems peculiar to science, and does not appear in artistic creativity. This leadsSimonton to think that his view which treats artistic and scientific creativity on a par may be undermined. But thehe "rescues" his theory by claiming that the multiples phenomenon does appear in artistic creativity. But thissounds implausible. The Fifth Symphony, Hamlet and the Sistine Chapel ceiling are unique, although their stylesreflect their zeitgeist. Of course, there are imitations, but these would not be considered to be genuine artisticproducts or counterparts of scientific discoveries.

Nevertheless, we can hold that both kinds of creativity are governed by the chance-permutation mechanism and yscientific creativity is characterized by the multiples phenomenon, whereas artistic creativity is not. There are two

substantial differences between artistic and scientific creativity. First, unlike artistic creation, scientific discovery intended to describe the world. No wonder that several scientists investigating the same domain of nature mightarrive at the same results, or at similar results. Scientific discovery is thus constrained by experimental results aswell as by zeitgeist. In contrast, artistic creativity is constrained only by the zeitgeist. Thus both kinds of creativitymay be based on the process of chance permutation, but the selection procedures are different. The configurationsselected in scientific discovery must accord with observational data, as well as with the world picture. Even if observational data partially depend on the zeitgeist, they depend also on nature.

The second difference is that much of the practice of science consists of inferences and argumentations. As wehave seen, much of the theoretical argumentation in science, in particular in the natural sciences, is modeled onlogical deduction. In logical and mathematical inference people are supposed to arrive at the same conclusion,starting with the same premises. This kind of inference takes place in normal science, where the theoretical

framework is given and typical discoveries are made by performing logical deductions or mathematicalcalculations, as well as by conducting experiments and making observations. We would expect, therefore, that innormal science scientists who start from the same transparent presuppositions and employ the same







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theory and observational data would arrive at the same result. No wonder that several scientists may independentlarrive at the same discovery. This may be an ideal case, but it shows that multiple discovery is not an exceptionacase; on the contrary, it is the regulating ideal of empirical and mathematically oriented science. In artisticcreativity, logic does not play such a role.

Scientific revolutions are not restricted by the prevailing paradigm, i.e. by the zeitgeist, but they should conform tsome transparadigmatic standards which characterize science and which are responsible for some minimalcontinuity in its evolution. A revolutionary configuration should conform with some general principles andentrenched beliefs and with some observational data which were inherited from the old paradigm. We thus wouldexpect the multiples phenomenon to occur less frequently in revolutionary science than in normal science. In thisrespect, revolutionary science comes closer to artistic creativity than does normal science.

As a consequence of the above discussion it would be highly objectionable to maintain that "scientific contributioare no more inevitable than artistic creations," even were it true that "one theory of creativity may account for significant contributions in both the arts and the sciences" (148). The discovery of Neptune was inevitable becausthe planet is there. Of course, we can say it now in retrospect because the fact that Neptune is a planet in the SolaSystem is now established beyond any doubt. Only if we are extreme antirealists, might we treat the existence of Neptune just as a convenient instrument for organizing our observations. When we come to a full-fledged theory

such as quantum mechanics or the theory of evolution, the influence of the zeitgeist on discovering the theory ismore significant than on an observational discovery, but still, the theory can be strongly confirmed by observationa factor which does not have a counterpart in the case of a piece of art such as the Mona Lisa.

In the domain of sense experience, we have more or less a definite set of natural kinds and phenomena and we sethe causes of these phenomena. The causes may be independently discovered by many people. Yet, when sciencesignificantly departs from the domain of ordinary experience, it can proceed along different paths. Many differenttheories can explain a given set of data. We choose a theory according to the zeitgeist, but this does not guarantethat we will be left with only one inevitable theory. There is an element of chance in the process. The physicaltheories which prevail are not inevitable. Had modern physics not started from the Galileo-Newtonian tradition, iis entirely possible that it may have proceeded in a completely different direction. We already have another example: the Aristotelian tradition. Yet scientists, in particular physicists, have the feeling that there are some

inevitable discoveries. The reason for this is the fact that they are imprisoned in their paradigms which limit their horizons. They do not believe that their paradigm may be eventually replaced. This is true in particular if they feethat their cur-







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rent theories are in general successful. Indeed, within a given paradigm certain discoveries are inevitable and as aresult we encounter the multiples phenomenon. This is also true of biological evolution. Along a given evolutionaline certain evolutionary developments are inevitable.

So although there is only one world, there are many possible evolutionary paths in it. There are different ways toadapt to a given niche. And the same is true of science. Hence, although the products of scientific creation are moinevitable than those of artistic creation, still they are not inevitable in any absolute sense, unless we believe thatscience aims at absolute truth, a belief that would not conform to the evolutionary picture. Multiple discovery andthe independent appearance of similar species in geographically isolated places are two manifestations of the samevolutionary phenomenon. The reason why the products of scientific discovery are more inevitable than those of the arts is that the environment in which the arts operate is determined by human culture, whereas the environmenof science is determined by nature as well. And the latter imposes severe restrictions on the ideas which wouldsurvive since nature is less flexible than human culture; there is a hard core in nature which cannot be changed byhuman action. The cultural environment, on the other hand, is a human product and therefore can be more easilychanged by humans.






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Chapter 7A Socio-Evolutionary Theory Of Science

7.1 Epistemic Cooperation and the Social Dimension of Discovery

Scientific knowledge is a socially produced knowledge and scientific epistemology is to a large extent a socialepistemology. Hence, scientific discovery is a social product. Individual scientists do not, in fact, cannot, make ascientific discovery. In order that a hypothesis, an observation or an experimental result will count as a scientificdiscovery, it has to be approved by the scientific community. Furthermore, the product of discovery is producedcollectively, synchronically (by cooperation) and diachronically (by relying on predecessors). Even Einstein'stheory of relativity cannot be seen as an isolated discovery made by a lone discoverer, since it relies on pastscientific results. If an Einstein or a Darwin would be raised up in a different cultural setting, they might not haveproduced their discoveries. They synthesize the scientific results of their predecessors and their contemporaries.Thus, they can be viewed as crucial links in a historical-cooperative process. One cannot envisage Einstein's theoof relativity without Maxwell, Poincaré and Lorentz. According to this view, the great discoverer supplies the

missing link in the cooperative process by which the discovery is generated. Discoveries are not made in a socialvacuum. The discovery is "in the air," or "the time is ripe" for it. This means that (a) the state of knowledge in thescientific community is ready for generating the discovery and/or (b) the time is ripe for the acceptance of the neidea or theory.

The idea that inventions are the products of their time is an Hegelian idea. It is related to the cooperative nature oscientific discovery. The soil for the invention is prepared by many predecessors. According to Hegel, the invento"is like the man who finds himself among workers who are building a stone arch whose general structure isinvisibly present as an idea. He so happens to be the last in line; when he puts his stone into place the archsupports itself. As he places his stone he sees that the whole edifice is an arch, says so






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and passes for the inventor" (Quoted in Lukacs 1975, 356). The discoverer, likewise, appears on stage at the rightmoment and puts his stone into place. I will cite three examples described by Lamb and Easton (1984). The firsttwo examples are those of Newton and Darwin. Newton's theory of universal gravitation developed between 1679and 1685 on soil prepared by Galileo, Kepler, Huygens, Descartes, Fermat and Hooke. Newton started to developthe theory when Hooke showed him the analysis of motion along a curved trajectory. It was developed through

communication with his contemporaries. The theory gradually emerged by logical deductions and transformationsof existing ideas "out of the repeated construction of mathematical models of the universe whose consequences hecompared with known observations and laws of the physical world, such as Kepler's laws of areas and of ellipticorbits" (ibid., 117). 8 The soil prepared for Darwin was fertilized by the ideas of selective breeding, Malthus's woon population and various evolutionary theories; the discovery was "in the air" (ibid., 120).

The third example of a revolutionary idea which emerged and gradually accepted in a historical process until thetime was ripe for it is the idea of extinct species (ibid., 105). The idea of species becoming extinct without leavinany descendants was revolutionary since it was against entrenched metaphysical beliefs going back to Aristotle.Several investigators entertained this idea in the late seventeenth century, but eventually yielded to theconventional view. By the beginning of the nineteenth century Georges Cuvier had become convinced of this ideaHis evidence in support of the mammoth's extinction undermined traditional views. In 1822, Gideon AlgernonMantell discovered iguanodon teeth in Sussex. He compared them with the teeth of the South American iguanalizard and calculated with reference to their respective sizes, that the teeth he found must have come from acreature over sixty feet long. As a result, the hypothesis of extinct species was gradually accepted. Mantell'squantitative evidence supported it strongly. This encouraged the search for further fossils. After similar fossils hadbeen found throughout the South England, as a result of the intellectual shift, the idea became established.9

The example of electroweak unification in particle physics, which will be described in Chapter 8, also demonstratthe cooperative nature of theory-construction. In this case it wasn't Hooft who put his stone into place and madethe arch supporting itself, although he was not last in line.

A discovery may be produced by an intentional cooperative work of a group of scientists who work on the sameproblems, not necessarily in the same place. The group, sometimes called "invisible college," may spread over several continents, having a strong communication network connecting them. This is predominantly a synchronic

cooperation, where the scientists conducting investigations on the same issues are aware of each other's work andreact quickly to each other's suggestions or results, as if they were participating in an ongoing dialogue.







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The cases where cooperation is not a preplanned process are the most innovative. It may happen that a scientist oa group of scientists propose an idea or a theory and other scientists who become acquainted with the proposalthrough the communication network and publication channels of the scientific community may suggest somemodifications or improvements, or contribute their own ideas, and as a result a successful theory is produced whiis a collective product. The process of discovery may stretch over a long period of time. In this case it can be

viewed as a diachronic process where the scientists do not cooperate intentionally; only with hindsight, may we sthat the final result is a collective product. The diachronic process may not even be continuous in the sense that aneglected theory or idea may be revived and modified after many years. The diachronic process in which onegeneration of scientists relies on the achievements and results of previous generations, is reflected in Newton'sfamous statement that he could make his discoveries since he was standing on the shoulders of giants. The finalresult is again a collective product.

We have here, therefore, another kind of unintentional discovery processes, where the process of discovery is, in sense, autonomous and has a "vitality of its own." When we view the intrapsychic process of creation and thesocial process of cooperative creation as involuntary processes, we can explain the tendency of scientists to exprethemselves in a modest fashion. The discoverer knows that he owes much of his achievments to his collegues andpredecessors, or to subconscious processes. This may explain why the use of first person singular is avoided inscientific literature. This mode of behavior is accounted for by the Mertonian norms of disinterestedness or communism (communality). The first norm forbids the scientist to profit personally in any way from his researchIn conclusion, the scientist should not make the search for professional recognition his explicit goal (Merton 1973276). The second requires that the scientist should share his findings, as a common property, with his collegues(ibid., 273) and thus it encourages epistemic cooperation.

Both diachronic and synchronic manners of interaction between scientists are social patterns of behavior; the firsexpresses reliance on the works of predecessors and the acceptance of tradition and the second reflectscooperation. The synchronic process has become more and more dominant in modern science. This kind of cooperation is encouraged by the norms of the scientific community and is channeled through a communicationnetwork, including journals, conferences and, nowadays, computer networking, all of which make the scientificcommunity highly liable to synchronic cooperation. Thus, the scientific community is a social system in whichcooperation in acquiring and producing knowledge is institutionalized.

An important stage in the discovery process is the evaluation of the product in order to decide whether it is indeeda discovery. This stage also has a social dimension. In science, the individual's belief is not recognized as a legiti







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mate knowledge claim before it is processed by the organs of the scientific community. Via this processing the idis assessed, improved or modified and integrated with other ideas. True, at any given period, there may be highauthorities whose opinions or beliefs are almost instantly accepted. However, it is the scientific community whichdetermines who are these authorities and when their opinions are accepted. There are cases where one or twoauthoritative figure dominates in a given field. For example, in the 1830s40s Berzelius was "the arbiter of the

chemical world" (Mulkay, 12). Murray Gell-Mann and Geoffrey Chew where the "gurus" of particle physics in thSixties. On the other hand, in some cases the opinion of a very prominent authority is not accepted. For example,Einstein's objection to the indeterministic nature of physical phenomena according to the newly created quantummechanics, and Rutherford's rejection of the idea of the quantum as a physical idea were ignored.

In order to clarify the epistemic situation in science, the following question is imminent: What is the evaluativecriterion which guides a scientist when he proposes a solution to a scientific problem or a new theory? Is it thecriterion of truth? Does he ask himself whether he has discovered some objective truth about nature or, perhaps,whether his proposal will be accepted by the scientific community? As is very well known to active scientists or tpeople who are acquainted with the patterns of behavior in the contemporary scientific community, the criterion oacceptance is the first one which comes to the scientist's mind. This is by no means opportunistic behavior. Indeedfor a scientist who has internalized the norms of the scientific community, the criterion of truth is acceptance bythe scientific community; this criterion is institutionalized. By "acceptance" I do not mean here simply acceptanceby all or most scientists in a democratic manner, but a kind of institutional acceptance which is expressed, for example, by acceptance for publication in respectable journals, endorsements by leading scientists and inclusion itextbooks. However, acceptance admits of degrees.

The social theory of science which will be expounded in this chapter will provide us with an explanation for thesocial or collective nature of scientific knowledge. The main conclusion of this social epistemology of science isthat in the environment exposed by modern science, the individual scientist cannot rely on his cognitive capabilitiin arriving at an explanatory theory or in judging whether a theory is good or bad. My main epistemological thesiis that in this case the scientist relies for good reasons on the collective wisdom of the scientific community.

Thus, in science we encounter an epistemic situation which seems to be diametrically opposed to traditionalepistemological conceptions. One of the main issues, if not the prime one, of the traditional theory of knowledge

the criterion of truth, i.e. the method or the way of determining whether a claim is true. Cardinal Mercier, as citedby Roderick Chisholm (1982, 63), says in his Criteriologie Generale Ou Theorie Generale de la Certitude that ifthere is a cri-







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terion of truth, then this criterion should be, among other things, "internal." This implies that the criterion of truthshould not be provided by external authorities. For example, in our quest for truth, we would not rely on criteriaprovided by our teachers or leaders or by the holy scriptures. Of course, we might be influenced by externalsources but in each case we are the final judges as to what to accept as true. The reason for accepting what theexternal authority says must be our own reason. According to this epistemological principle, the criterion of truth

or plausibility cannot be an acceptance by the scientific community. However, for a scientist who has internalizedthe norms of the scientific community through the process of scientific education and socialization, the criterion oacceptance by the community becomes an internal criterion for him; he really believes that what is accepted is truor plausible. Thus, just as according to the empiricist view, a belief is true only if it can be derived from, or baseon, sense experience, so in science a belief is true or plausible only if it is accepted by the scientific community. Athey stand, both truth criteria have no a priori justification.

What, then, is the difference between the tribesman who internalizes the truth criterion of believing whatever thewitch doctor or the chief says and the scientist who believes whatever is accepted by the scientific community?Modern Western society would treat the tribesman's "criterion" as irrational, whereas science would be regarded athe most rational human enterprise. The difference between the two attitudes may be found by employing thenotion of adaptability. The tribesman kind of behavior is appropriate for meeting the environmental conditionsprevailing within the boundaries of his restricted living spacethe tribal habitat. However, his truth criterion may bdetrimental under different environmental conditions. From the vantage point of the evolutionary POR, as we wilsee, rationality requires adaptability to changing environmental conditions. If we equate rationality withadaptability, we may explain why the tribesman truth criterion is irrational. Science is rational since it is adaptablto a variety of environmental conditions. Science adapts to the artificial technology-intensive environment createdby science itself. The adaptation is achieved by employing highly abstract theories and by using elaborateexperimental and observational techniques which help scientists in testing and improving their theories.Furthermore, the process of testing and improving the theories brings about further extension of the environment.Hence, adaptability is built into the ongoing process of the growth of scientific knowledge.

Now, what is the role of epistemic cooperation in the process which makes science adaptable to extendedenvironments? An answer to this question will provide us also with an answer to the question: why is it rational treplace individual judgments in science with epistemic cooperation. Cooperation brings about efficiency in the

acquisition of knowledge. However, efficiency is not epistemically essential. Cooperation would be epistemically







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essential only if it leads to discoveries that would not have been possible without it. Cooperation would beepistemically essential, for example, in a hypothetical community where none of the members possesses all thenatural sensory or cognitive capabilities, which are possessed by all the members taken together. In science, itseems the situation is not like this. In principle, a single gifted scientist can conduct all experiments and develop possible theories which are conducted and developed by the whole scientific community. Practically it is

impossible. However, traditional epistemology is not interested in pragmatic contingencies, such as the time takenfor making a discovery, or the availability of a human general-purpose supercomputer.

One possible reason why the social dimension might be essential is that the selection should not be made by thescientist who proposed the idea. Thus, perhaps there should be a division of labor in this respect. However, eventhis is not epistemically necessary. Indeed, a single Descartes would attempt to question and undermine any beliehe has; a single scientist may have both creative and critical faculties. Another widely accepted reason for theimportance of the communal acquisition of knowledge is that a community may eliminate personal bias. Howevethere is no way to be totally objective; who will eliminate communal, cultural or, in general, human bias?

Yet, as I will argue in this chapter, the reasons for the epistemic indispensability of the social dimension of scienclie in its indispensability for science as an evolutionary process. Hence, epistemologically, the cooperation and thsocial dimension of science cannot be divorced from the evolutionary view of science.

Now, I would like to list and to summarize some of the implications of epistemic cooperation for the process of scientific discovery.

a) The process of scientific discovery is a collective process and the product of discovery is a collective, or socialproduct. Hence, whenever someone proposes a hypothesis, he loses control of it since it is processed by other members of the scientific community, including future generations of scientists. We can view the process as anautonomous phenomenon. Thus, the process and the product of discovery are independent of the individual scientist's mind . This reminds us of the realist's claim that the object of discovery is independent of the discoveremind. For example, the idea of the quantum developed independently of Planck's intentions, and quantummechanics is a product of the collective efforts of Planck, Bohr, de-Broglie, Schroedinger, Heisenberg, Born, PauDirac, Bohm and their followers. In this sense, collective discovery can be categorized as an involuntary

phenomenon on the social level, similar to the process of chance permutation or incubation which operates on theintrapsychic level.

b) No scientist can know that he made a discovery before he has submitted it to the scientific community. Anessential part of the process of discovery is the







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processing of the proposed hypothesis by the scientific community. Only when this processing is terminated withacceptance, is the process of discovery terminated. Hence, strictly speaking, even in case a proposal is acceptedintact, the discoverer is the whole scientific community, rather than the scientist(s) who proposed the hypothesis.

c) There is an implication of b) for the issue of realism. We might say that scientific discovery is made not merelin nature, but also in the scientific community. This means that the object of discovery is not merely a naturalobject, phenomenon or law; it is also a social product. This leads to a radical epistemological aspect of the''socialization" of scientific discovery. When I say that scientific discovery is made "in the scientific community,"mean that we discover something which happens in the scientific community; we discover what ideas or hypotheses are accepted in the scientific community and how they develop. The totality of the accepted ideas andtheories constitutes the picture of reality formed by science. We may metaphorically describe this sense of discovery by saying that the scientific community is an instrument by which we (human society) investigate theworld. This instrument is our only information channel from the external world. We do not have any alternativeway to observe or investigate the external world, either directly or indirectly. Hence, our only way of obtaininginformation on what is going on out there is by observing the image or picture of the external world which isgenerated or formed in the instrument. We discover, therefore, the image or the picture of reality, rather thanreality itself. According to this view, science is a "mirror of nature" (I employ this expression as it was used longbefore Rorty). As we have already seen, this mirror is not a passive reflecting device. It is rather a mirror whicheffects the color and the shape of the image. Hopefully, it is not a distorting mirror. The major question concerninrealism is whether a discovery in the scientific community reflects something real in the external world, or does ionly reflect the internal dynamics of the scientific community.

However, is there a real difference between this manner of viewing scientific discovery and the way we view anordinary discovery that we make in our ordinary experience? Viewing ordinary observation from an objectivepoint of view, i.e. from a vantage point external to the observer, we may say that the observer becomes directlyaware of the mental picture formed in his mind, not of reality itself. Yet, the observer, from his subjective, or internal, point of view identifies the picture with reality itself. The difference between the mental picture formed ithe individual's mind and the collective picture formed in the scientific community is that with respect to the latteno one has an internal vantage point; the picture is external to every member of the scientific community, althougall of them participate in the process of forming the picture. This is analogous to the following situation: none of

the members of a large group of soldiers or gymnasts in a stadium can directly perceive, or be directly







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aware of, the formation he is helping to create. We can discover the shape of the formation only from a bird eyeview, which is an external point of view.

In the social game of science, a necessary condition for making creative discovery is the exposure of the collectivpicture formed in the game. Indeed, a scientist who participates in the game is imprisoned in the collective picturthus formed and he cannot intentionally change the picture without being aware of it. Hence, a creative or a radicdiscovery, which has been generated in the scienitific community, can be exposed by someone who is capable ofascending above the game of science or by someone who does not participate in the game.

Moreover, when we say that the creative discoverer proposes something that no one has thought about before, werefer to the typical case when everyone is looking for the solution or the explanation in a traditional direction,whereas the creative discoverer is looking in a new direction. This means that creativity is derived from the abilityto break out of the prevailing framework of conceptions and presuppositions. Sometimes the current paradigm is entrenched that most scientists are not aware of it. Indeed, a precondition for breaking out of the framework of tabeliefs, assumptions and conceptions in which the community of problem-solvers is imprisoned is identifying it.This can be done only by someone who is capable of ascending above the framework, taking an external vantagepoint. Since the framework is community-dependent, we may conclude that the creative discoverer should be anon-conformist or someone who tends to be socially an outsider to the scientific community. Social isolation or

social non-conformism characterizes many revolutionary discoverers. The famous example of Einstein at the pateoffice is well known.

Mulkay suggests a possible social mechanism of innovation in science (Mulkay 1972). Innovation is built into thestructure of the scientific community. Deviation from current orthodoxy is usually discouraged in the scientificcommunity. Yet, the very social processes which are responsible for maintaining intellectual conformity in thescientific community generate also the conditions for innovation. One of the main driving forces in science is theneed for professional recognition. Scientists share the results of their research with their collegues. In return, theyreceive recognition which is mainly given to contributions which conform to current "cognitive norms." So whenscientific field matures and provides fewer opportunities for recognition by the scientific community, scientistsworking in the field tend to look for other fields with more rewarding problems. This leads to the phenomenon ofintellectual migration mentioned in the last chapter. Scientists migrate from areas of declining interest into those

with greater opportunities for recognition. In their new area of research they apply the tools or techniques theyacquired in their old field for solving the new problems they face. The tools they carry with them to the new fieldare specific ideas, theories or theoretical methods as







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well as experimental techniques and instruments. The resulting cross fertilization of ideas is a major source of innovations.

Mulkay discusses another source of innovation. "Significant innovations emerge mainly at the top and the bottomof the status hierarchy of science" (ibid., 8). Within a given community, innovation comes from scientists who arnew to the area and who have not acquired a strong commitment to the prevailing norms. They have little to loseAnd scientists at the top of the hierarchy can take risks since their reputation is well established.

However, many great discoveries were made from within the current paradigm. As we saw in Chapter 5, somegreat discoverers started with problems which arose in the current paradigm, not being aware of the fact that theystarted a process that eventually broke out of the framework. Kuhn maintains that "only investigations firmly rootin the contemporary scientific tradition are likely to break the tradition and give rise to a new one" (Kuhn 1963,343). They do it, however, unintentionally.

Planck's example raises the question of whether creativity in scientific discovery can always be attributed to anindividual discoverer. The discovery of quantum mechanics, for example, was a historical process which cannot battributed to a single discoverer. Thus, as I have already indicated, major discoveries are sometimes historical andcollective processes which only in hindsight can be recognized as such. The individual participant in the process

may not be aware of the full significance of the process. In this case, our esteem should be directed to the wholescientific community, rather than to individual scientists.

The social dimension of creativity is, therefore, evident. On the one hand, in some important cases a creativeindividual is socially a non-conformist, a migrant or an outsider. On the other hand, many major creativediscoveries are collective and/or historical products. In other words, they could emerge only unintentionally fromthe activity of conformist scientists. What can be concluded from these two social characteristics of creativity isthat there is a tension between creativity and social conformity in normal science. The two ways to overcome thistension is when the discoverer is a non-conformist individual, or an outsider, and when the process of discovery ia collective-historical process which transcends the intentions of individual scientists participating in it.

7.2 The Social Dimension of Blind Variation, Selection and Dissemination

One source of blind variation in science is the intrapsychic process of chance permutation. A second source is thesocial dynamics of science. As we have







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observed, unintentionality and serendipity, i.e. blind variation, is built into the social dynamics of science. Due tothe the cooperative nature of scientific work, when a scientist proposes an idea to the scientific community, he isnot anymore in control over the idea, which is processed by the community synchronically and diachronically. Thend product may solve a problem the originator of the idea has not dreamt about; in suggesting the idea, theoriginator was "blind" to the problem that is eventually solved in the process he initiated.

The mechanism for eliminating unfit variations which is part of the natural selection scheme also has a socialdimension. The elimination of unfit hypotheses is not a purely logical act as Popper claims. As is well known toscientists, and as has been shown by philosophers (such as Duhem and Quine), a hypothesis can be protected frorefutation by observational data which contradict it by introducing ad hoc assumptions or by modifying some othdomains in the corpus of knowledge. Of course, such ad hoc maneuvers may complicate the theory which will loits original simplicity, without gaining any new information. However, there is no universal standard for decidingwhen the auxiliary assumptions and modifications are unacceptable. It is not a matter of purely logical refutationwhich leads to abandoning an hypothesis. Here again, the social dimension is operative. The mechanisms of eliminating and accepting new hypotheses are regulated by social institutions such as scientific societies, the awasystem and the funding agencies, which promote certain research projects and reject others, and scientific journaland conferences, which accept certain research papers and reject others. The policy of these institutions reflect thenorms and methods prevailing in the scientific discipline. These norms are context-dependent rather than universaHowever, the acceptance or rejection of an idea or a theory may be a result of the social dynamics in the scientifcommunity, having nothing to do with any explicit norms.

If we try to view scientific decisions in a traditional methodological fashion, as an objective matter, then we mayconclude that the major factors contributing to the survival of a hypothesis or a theory which is under evaluationare its problem-solving capability or the extent it fits the observational data. Problems may arise when trying toexplain particular phenomena or events, or when trying to relate the hypothesis to other theories. Hence, we maydefine the environment of a developing theory as consisting of (a) the data which the theory ought to explain, (b)other developing theories which attempt to explain the same data and (c) established theories with which the theoshould conform. This is analogous to the fact that the environment for an organism consists of physicalenvironment and other organisms. However, if we do not ignore the social dimension of science, we must take inaccount the fact that the decision whether the given hypothesis is well adapted to the "environment" is made by th

scientific community, which does not necessarily follow objective norms. Thus, the mechanism of weeding outunfit varia-







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tions is provided by the dynamics of belief-formation in the scientific community. Yet, the individual scientistmakes the first selection; he proposes only selected ideas to the community. Ideas proposed by individual scientistare subsequently selected by the scientific community. Similarly, mechanisms for generating variations operateboth on the individual and the social levels.

The mechanism of dissemination of ideas and theories is clearly a social process, which encompasses the educatioand publication systems. It neither belongs to the context of discovery or generation nor to the context of evaluation. Nevertheless, dissemination, according to the evolutionist POR, is an essential component in theevolution of science.

Thus, in the evolutionary POR the D-J dichotomy is converted into a trichotomy: the D-J-DS (discovery-justification-dissemination) distinction. However, as there is not a sharp line separating discovery and justificatioso there is no sharp line separating justification and dissemination. Dissemination does not always temporallyfollow justification or evaluation. Dissemination may be part of the evaluative process and vice versa. Sinceevaluation has an essential social component, one of the determining factors in evaluation is the effectiveness of the communication channels through which an idea is disseminated. If an idea is disseminated through anestablished and influential publication system, and presented in prestigeous conferences, it would have morechances to be accepted. The publication and communication systems are not regulated by objective norms and

standards of evaluation. Since an essential part of evaluation is persuation, effective dissemination is part of therhetoric which contributes to the process of evaluation and confirmation. An idea is accepted if most influentialscientists are persuaded to accept it. Thus, there are scientists who have more access to these systems than doothers, for various reasons, not the least of which is that they themselves are in control of tools of dissemination.

A logicist or coginitivist POR would not attribute an essential role to dissemination, since according to bothapproaches science can in principle be done by a Robinson Cruso. In an evolutionist POR dissemination isessential and is linked with the social dynamics of science.

7.3 Has Science Liberated Humankind from the Tyranny of the Genes?

7.3.1 Genetically Controlled Human Understanding

Viewing science as an evolutionary process sheds light on its epistemological significance. Evolutionaryepistemology tries to explain why science is so successful and reliable in view of its evolutionary character.However, science







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emerged from our cognitive capacities and from our ordinary experience. Hence, science is restricted by, and relon, prescientific intuitions and commonsense which are guided to a large extent by our "hardwired" cognitiveapparatus or innate capacities which are common to all humans. Hence EE should try to explain first why our genetically based cognitive apparatus is a relatively reliable guide for learning from experience and for our orientation in the world, so that we have relatively high chance to survive.

For example, on the basis of our past experience, we make predictions about events we have never observed, andmiraculously most of these predictions turn out to be trueotherwise we would not survive. Why it is the case, for example, that all (or most) of humankind's expectations that "the sun will rise tomorrow" have turned out to betrue? Induction cannot be logically justified. Furthermore, it cannot be justified by referring to the fact that most oour inductive inferences have succeeded in the past, since this argument relies again on induction. Nevertheless, wdo not have to accept the following claim made by Alfred Ayer (1952, 73): "we shall have to accept it as amysterious inexplicable fact that our thought has this power to reveal to us authoritatively the nature of objectswhich we have never observed." Even if induction cannot be logically justified, we still can treat it as a naturalphenomenon which is by no means inexplicable. Indeed, EE attempts at providing an explanation for this fact. EEdoes not provide us with a justification, in the traditional sense, of beliefs based on induction. For example, it doenot supply us with a warrant for the prediction that the sun will rise tomorrow, or that the chair I am sitting on wisupport me in the following second. However, it may provide us with reasons why these beliefs are rational, or more rational than their negations. In addition to providing the basis for our inductive expectations, our innatecognitive capacities may provide the basis for other kinds of expectations and conceptions which seem to usnecessary for our thought processes and for comprehending the world around us.

Biology can give an explanation for the miracle of the special adaptation of our "hardwired" cognitive apparatus tthe world. In the course of evolution, Homo sapiens and its predecessor species developed tools for acquiring anorientation in the world and for learning from experience. These tools are genetically based and are inherent inevery individual. There is no guarantee that these tools enable us to perceive reality correctly, but they havesurvived during the process of natural selection, hence we can assume that they have some advantages with respeto their adaptability to the world.

When we try to explain the origin of our cognitive apparatus in the light of evolutionary theory, we can say that t

information which is responsible for the modes of perception and learning from experience have developed in theevolutionary process where the DNA has been shaped by natural selection as a model of the environment. Thus,human beings are born with a potential to develop a cognitive apparatus, which is destined to absorb the rawmaterial







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of sense impressions. Our innate capacities are not explicit ideas or beliefs. Rather they are dispositions or potentialities which are actualized in the course of our experience and development. Namely, one becomes awareof some genetically determined expectation or belief when one is exposed to some relevant experience, includingcultural experience, such as learning. For example, one may become aware of a basic logical rule after somereflection or after being taught. The inborn schemes include the basis for the ways we learn from experience, e.g.

by induction, and the basis for our tendency to expect regularities in nature and for our belief in causality. It is alsplausible to assume that some of the basic elements on which classical physics is grounded stem from geneticinformation which is common to all human beings. This is because classical physics was shaped in an environmewhich did not much exceed the environment in which evolution of the hominid line took place. Indeed, Piagetclaims that the child discovers in a certain developmental stage the laws of mechanics, so we may say that thechild, through his activity in his environment, exposes his innate mental capability to comprehend these laws.

By assuming that there is a common genetic information responsible for some of our cognitive capacities whichhas evolved through the evolutionary process, we may answer the question of how we can arrive at successfultheories such as evolutionary theory, Newtonian physics or the classical theory of matter. Such an explanation isneeded if we are not in possession of a method or an algorithm for inferring or constructing true or successfulscientific theories from a firm basis such as facts (if we are empiricists) or first principles (if we are rationalists).

I should add that it would be an exaggeration to assume that the world picture of classical physics is solelygenetically based. The classical world picture certainly draws some of its basic concepts and ideas from thosedeveloped in cultural evolution and which are not genetically based. In any case, it is difficult to disentanglegenetical influence from cultural influences on concept formation and on our basic beliefs. However, the fact thatsimilar concepts and ideas have appeared independently in different cultures and that all natural languages havecommon deep structure (Chomski 1957, 1966) may indicate that there are genetically based ways of learning fromexperience and of comprehending the world. For example, inductive expectations and the concept of object areperhaps universal. In fact, higher animals, too, behave inductively and they seem to behave as if they see objects their surroundings. Maybe also the concepts of space, time and force are transcultural. Also the method of exploring the environment by intervening (e.g., by active experimentation) is characteristic of the whole humanspecies. The mechanistic outlook, on the other hand, seems to be dependent on European culture in the seventeencentury. Some would claim that Aristotelian physics is more intuitive than Newtonian physics. However, nowaday

the world picture of classical physics does not clash with our genetically and culturally based intu-







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ition. And it is plausible to assume that some of the most fundamental concepts and beliefs upon which classicalphysics is erected are inborn in the Piagetian sense; i.e. in the sense that at certain developmental stages we arecapable of comprehending, and even discovering or acquiring, these concepts and beliefs, provided we interact wiour physical and social environment. We do not have to accept the detailed theory of Piaget about a child'sdevelopment. I only endorse here the general principle that the actualization of our innate capacities is a process

which takes place only when we are exposed to experience, when we interact with an environment of the type inwhich these capacities evolved or by interacting with our sociocultural environment, e.g. by learning.

Yet, the assumption that the genes responsible for the development of our cognitive apparatus were shaped in anevolutionary process will not provide us with an explanation for the fact that modern natural science is successfulin those domains of experience which exceed the conditions under which organic evolution took place. It isestimated that human anatomic and physiological constitution has not changed much in the last fifty thousandyears. There is no reason to believe that human genetically based cognitive capacities have changed much either.Thus, "the actors in modern technical society are products of the past, of times and ways of life long gone"(Washburn & Lancaster 1968, 221).

The actors in modern science are no better off; stripped of all cultural influence, they would not differ from thehunters and cave dwellers of tens of thousand years ago. Nevertheless, modern physics, for example, is quite

successful in dealing with objects and phenomena on the microcosmic and cosmic scales. In these domains, thephysicist obtains his data by using high energy technology and high power telescopes, radiotelescopes and other devices which extend his sensorimotor organs, exposing environmental conditions which are radically differentfrom those prevailing in our natural habitat, in which our ancestors, the cave-men hunters, evolved. Even when winclude the culturally shaped environment of industrial society in the environment where our genetically and

culturally based cognitive apparatus evolved, still the boundaries of the environment in which modern scienceevolves are much wider. Hence, our genetically and culturally based cognitive capacities are inappropriate for guiding us in modern scientific inquiry.

Indeed, the concepts and theories of modern physics are much more remote from our intuitive grasp than those ofclassical physics and the commonsense. For example, the concepts and principles of quantum mechanics, such asthe wave function, the wave-particle duality or the uncertainty principle, are not easily comprehensible to our

intuition. In high energy physics, or particle physics, which stands in the frontier of science, the theoreticalconcepts are extremely remote from everyday concepts. The quark, for example, departs from the everyday notionof an object or a classical particle, more than







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does the ordinary quantum-mechanical wavy particle. Other examples are the notion of quantum field, guage fieldor superstring.

The conceptual difficulties arising in the interpretation of quantum mechanics may be related to the fact that our cognitive apparatus was shaped in the mesocosmos, which consists of medium-size objects and everydayvelocities, distances, temperatures, energies and so on. Namely, our cognitive apparatus is capable of comprehending only mesocosmic phenomena which can be explored or exposed by our natural sensorimotor organs aided by prescientific tools and technological devices. Indeed, our cognitive apparatus coevolved with thesorgans and tools, which determine the boundaries of our natural habitatthe mesocosmos. It is therefore capable ofcomprehending this environment only.

7.3.2 Transcending Our Natural Habitat

Serendipity enables science to break through the boundaries of the prevailing paradigm. It is only throughunintentional acts that a prevailing framework of beliefs can be transcended by conformist scientists. One of theway an unintentional development takes place is via a collective or a historical process, in which the final problemwhich is solved is different from the original problem which triggered the process. Serendipitous discoveries canalso be made by an individual scientist. However, as I will argue below, our main hope of freeing ourselves from

the framework of beliefs in which we are imprisoned is through serendipitous processes with socio-historicaldimensions. The process of transcending the Ptolemaic paradigm, initiated by Kepler, and the process of transcending the Newtonian paradigm, initiated by Planck are two of the most salient examples of thisphenomenon. The product of a serendipitous process should be comprehended and accepted by the scientificcommunity before it is recognized as a discovery. My claim is that only the social dynamics of science can yield discovery which transcends an established paradigm. This is in particular true if the resulting discovery leads tocomprehending a new environment which significantly departs from our natural habitatthe mesocosmicenvironment.

The clue for understanding how science progresses in explaining cosmic and microcosmic phenomena, for example, can be found in the social dimension of science and in the manner by which science continues theprocess of organic and cultural evolution. Our cognitive apparatus is mainly a product of organic and early cultur

evolution. Its limitations in comprehending wider environments can, therefore, be overcome by the continuation othe evolutionary process on the socio-cultural level. The latter does not bring about modifications in human brainand cognitive capacities. Our cognitive apparatus is essentially the same as that of our prescientific ancestors; anoffspring of a Planck or an Einstein is born with genetically based potential for developing







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cognitive capacities which are essentially the same as that of an Aristotle or a Ptolemy.

Of course, there is a variability in the gene pool of the human species. Perhaps some people have useful dormantgenetically based, or even culturally based, mental variations which can be activated only when the appropriateenvironmental conditions emerge, e.g. when those people are exposed to an appropriate branch of science, to newdata or to a new mathematical apparatus. However, when such dormant variations become successful, they do notspread biologically in the human population since they do not endow their owners survival value or reproductiveadvantage; they just spread within science. Ideas are eliminated or disseminated by cultural means. Hence themodifications of human cognitive capacities occur on the superorganic, or cultural, level. Culture and sciencedevelop novel conceptual systems and world pictures which are not genetically inherited but can be acquired byevery individual via learning. This is why science is not adaptive for individual human beings. However, it isadaptive for human society and this is what is important, since the evolution of humanity takes place at the presestage on the sociocultural level. I would not accept, therefore, the following claim made recently by Michael Ruse

Note that I am not saying anything so crude as simply that science is adaptive and that which we consider better science is more adaptive than worse science. This is obviously false. Mendel, to the best of one'sknowledge, died childless and yet in respects he had a better grasp of the nature of heredity than any of hisfellows. Darwin, to the contrary, had many children but this had nothing whatsoever to do with his

brilliance as a scientist. (Ruse 1989, 193)

Other things being equal, a society which benefits from Mendelian genetics, or from modern biology, in general,more adaptive than a society which does not. There is no correlation between the adaptiveness of science and thebiological adaptiveness of single scientists. Mendel was childless but he fathered ideas which survived in scienceand which contributed to the fitness of society at large.

Every individual who is brought up in a given culture acquires and assimilates since early childhood and in hisformative years the general world picture prevailing in that culture. Hence, this world picture is deeply entrenchedin his mind; he looks at the world through it. The hard core of the world picture is genetically based, in the sensethat every human being has an inborn potential for developing the expectations, concepts and beliefs constitutingthat hard core. Furthermore, the world picture which was developed in any culture is adapted to the mesocosmic

environment. It is true that, to a certain extent, the scientific world picture penetrates the culturally based worldpicture, but the







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average non-scientist does not look at the world through the updated world picture of science. Hence, we may saythat our genetically and culturally controlled cognitive apparatus limits us to comprehend the mecocosmos only. different view is proposed by Ruse who maintains that it is sensible ''to suppose that our reasoning abilities are, insome very real sense, rooted in our biology" (ibid., 203). Ruse does not distinguish between ordinary reasoning anscientific reasoning. For him the reasoning processes which led to quantum and relativistic physics are based on t

same logic which guides prescientific and everyday reasoning. Science is governed by commonly accepted rulesand criteria which "we humans use because they proved of value to our ancestors in the struggle for existence"(ibid., 193).

However, although ordinary reasoning and scientific reasoning have some common core, it is implausible toassume that the evolution of modern physics, for example, can be explained by this common core alone. ThomasNagel expresses this question in the following illuminating passage:

The question is whether not only the physical but the mental capacity needed to make a stone axeautomatically brings with it the capacity to take each of the steps that have led from there to theconstruction of the hydrogen bomb, or whether an enormous excess mental capacity, not explainable bynatural selection, was responsible for the generation and spread of the sequence of intellectual instrumentsthat has emerged over the last thirty thousand years. (Nagel 1986, 80)

Indeed, something else is needed for comprehending the phenomenon of modern physics. However, Nagel looksfor the "enormous excess [of] mental capacity" needed for creating science in the wrong place. It is not an inborncapacity. Rather, it is generated in a creative socio-evolutionary process. I will explain this cognitive capacity bythe same model of natural selection, operating on the sociocultural level. In looking for the additional factor responsible for the growth of science, I will consider the possibility that in science new dimensions, in addition toreasoning, play an essential role; perhaps natural science is a natural phenomenon in its own right, not just a matof reasoning. I shall look for these dimensions in the sociocultural arena.

However, one may object that to the extent that the capabilities of being a social animal and of developing culturare rooted in humankind's gene pool, then everything humankind is achieving, including science, is "rooted in oubiology," as Ruse claims. But in what sense do we use here the term rooted? If we view science as an evolutiona

process, which is a continuation of human evolution, then we might say that everything developed in thisevolutionary process is rooted in human biology. In this sense of the word, every form or trait which emerges aloan evolutionary line, is rooted in any pre-







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decessor stage along the line. However, in the same fashion, we would be led to say that every new species or trawhich appears along an evolutionary line is rooted in the biological constitution of its predecessors, so that humanbrain and human culture is rooted in the biology of some ape species. But this is a very broad and unilluminatingnotion, which will lead us to the following argument: The capacity to do science is rooted in our biology, which, turn, is rooted in the biology of some hominid ape or even in the biology of some primordial form of life of whic

we are descendants. Therefore, scientific reasoning is rooted in the latter.However, evolution, including cultural evolution, is not deterministic; chance playing a major role in this processincluding the evolution of humankind, in particular in sociocultural evolution. Thus, if we use the word rooted innarrower, and more sensible sense, we would not claim that every quasi-random variation, of any order, imposedon a given form along an evolutionary line, is rooted in this form. Novelty emerges along any evolutionary line,and science is one of the novelties which have emerged in our evolutionary line. The evolution of science has beaffected both by our biology and by chance events or new environmental conditions which were exploitedopportunistically in the processthe same as it happens in organic evolution. Thus, the trait of social cooperation ohumankind, which perhaps was originally selected for the benefit of hunting, was later opportunistically exploitedfor the creation of science. This does not mean that science is deterministically rooted in prehistorical hunting.

7.3.3 Two Patterns of Human Evolution

Yet, it is not only sheer chance which has been regulating novelty-generation along our evolutionary line. I wouldlike to suggest that there are two interlocked evolutionary patterns, or principles, which enable humankind totranscend its natural habitat. These patterns in themselves were probably selected because of their survival value.One principle refers to the strategy by which our species solves its problems and increases its adaptability: this isthe principle of growth by expansion. The second is concerned with the evolution of the capabilities which enablehumankind to carry out this strategy: the coevolution of the sensorimotor organs and the brain, or of human actionand human cognitive capacities.

a. The Principle of Growth by Expansion The preceding discussion raised a crucial question regarding humanevolution: whether and how human knowledge has broken free from, or has transcended, the limits imposed on itby its genetically and culturally controlled cognitive capacities. Since our cognitive apparatus is an evolutionary

product, then by considerations of biological adaptation, we would expect human intelligence to be limited tocomprehend-







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ing only those aspects of reality which are vital to the survival of the human species. However, the question iswhat does biological adaptation mean. Does it mean adaptation to humankind's natural undisturbed environment?Furthermore, is there any biological meaning to such a static concept of environment? We know that theenvironment of a given population of organisms is determined to a large extent by the organism's activity. In othewords, the environment is composed of those domains and aspects of the physical and organic surroundings whic

the species tries to exploit. Thus, the environment is not independent of the species' traits and behavior. As theactivity of the population extends, the environment changes. This applies in particular to the human species and toculturally based activity. Humankind explores its environment by actively disturbing it, e.g. by technologicalintervention. Hence, humankind's environment is rapidly changing as a response to its activity. These culturallyinduced changes are more extensive than the natural changes.

We may say that with the evolution of human extensive motor activity, and with the parallel evolution of thecognitive capacities, the guiding principle of cultural development became the principle of evolution by expansionThis means that the human species extends its activity, exposing new domains in the environment and adapting tothe changing environment. Natural science and technology, which continue this process most extensively, haveevolved, indeed, in a rapidly changing environment. The environment exposed by active scientific observation anexperimentation does not just change but expands; more and more phenomena are exposed and more and morelayers and aspects of reality are unveiled.

Thus, when we are asked whether the human mind is capable of comprehending only its natural habitat, our firstresponse will be that humankind's natural habitat itself is not static and is not limited to the niche in which Homosapiens evolved organically. A major trend in humankind is its adaptation to an expanding environment rather thaimproving its adaptation to a given environment. However, the dichotomy implied by the last statement is onlyapparent. By going beyond given environmental conditions, humanity overcomes problems which have beenunsolvable in the old environment. For example, in order to overcome food shortage, humanity changed its livingspace by agriculture. Another example is from science. In order to solve anomalous phenomena which arose inchemistry and atomic physics, such as the radioactivity phenomenon, science entered into the domain of nuclear physics, by developing new experimental and theoretical methods and techniques. Of course, every new "living-space" raises new problems, some of which cannot be solved and a new "Lebensraum" is sought.

This principle of problem-solving by expansion can be related to C.H. Waddington's view of evolutionary change(Waddington 1975). Waddington maintains that evolutionary progress (not only of humankind) means progress inadaptability, rather than progress in adaptation. A species may be







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well adapted to a static environment. Such an environment does not exert selective pressures that give an advantato organisms which are more adaptable. The species may survive a long period in a stable state, but may becomeextinct after the environment undergoes sudden changes. The human species does not wait passively for environmental changes to occur but creates the changes by its own activity. This evolutionary pattern, which isrelated to the evolution of the sensorimotor organs and the brain, brought about the high degree of adaptability of

humankind. Humankind's high degree of adaptability is not due only to the plasticity of the individual humanphenotype but also to the high plasticity inherent in the structure of human society. This includes the socialdimension of science and technology.

We often encounter an objection to the claim that science serves as a tool for survival, or that it constitutes acontinuation of biological evolution. The objection relies on the assumption that science expands into areas whichhave no survival value for humanity. In other words, it is claimed that science "overdoes" the task of serving as atool for survival. According to this argument there is no survival value in theories developed for explainingphenomena which to a large extent are created by science. Also there is no use in cosmological theories.Furthermore, science aims at understanding rather than at practical usage. However, in view of what was saidabove, a survival value is not attached to the adaptation to a given environment. Science is a method or a tool forincreasing adaptability, and the latter is the trait which has a survival value. Science prepares us for future hazardor future opportunities to which we will more quickly adapt by employing scientific theories and methods. Sincewe cannot anticipate what environmental changes will occur in the future, we cannot know at any given momentwhether a certain theory or an experimental result or technique has a survival value or not.

The phenomenon of serendipity is related to the process of increasing the adaptability of science. Serendipitousdiscovery is a mechanism for expanding knowledge beyond any given framework or paradigm. Indeed, scientistscannot know in advance what new environments will be eventually exposed as a result of their research. In manycases a new environment is exposed serendipitously as an unplanned by-product of research done within theconfines of the old environment. The new environment provides solutions to problems that were unsolvable in theold environment. This is, therefore, another important facet of serendipity. The phenomenon of unintended or serendipitous discoveries, which is built into science, contributes to the adaptability of science .

Our cognitive apparatus which was shaped in the mesocosmic environment gives every human being the basis for

adaptation to this environment, including the basis for comprehending mesocosmic phenomena. Our geneticheritage also gives us the capability of developing technology-based culture which is characterized by the patternof problem solving by expansion. This







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evolutionary pattern enables humankind to transcend the limits of the mesocosmic environment. However, at thepresent evolutionary stage of cultural and scientific evolution the selection pressures exerted by new environmentconditions, e.g. by the data gathered via scientific experiments, affect only our "idea pool" rather than our genepool. This is because ideas compete and "die in our stead" (to use Popper's phrase, 1972, 25). Hence, the resultingincrease in adaptability is not genetically transmitted from generation to generation. It is, therefore, the human

society, or rather the scientific community, which evolves and adapts to the new environmental conditions. Thescientific community with its institutional structure and its collective wisdom is capable of coping with the newenvironments exposed by science. With this conclusion in mind, let us turn to the second pattern of humanevolution.

b. The Coevolution of Human Action and Human Understanding The above evolutionary pattern characterizes theactivity of the human species which results in adaptation to an expanding environment. The second patterncharacterizes the evolution of the human species' constitution: the coevolution of sensorimotor capabilties and bracapacities. This is the very evolutionary pattern which enables humankind to generate the expanding environmentand to adapt to it. Furthermore, I will view sociocultural evolution, including science, as a process which isgoverned by the same principle; technology and science extends both our sensorimotor capabilities and braincapacities. Observational and experimental devices constitute our "extended sensorimotor organs" which generateor expose the environment in which modern science evolves.

Now, if we want to complete the analogy, the question is what is the "extended brain" which coevolves with theobservational and experimental technologies and which developed the intricate mathematical and theoreticalapparatus of modern natural science? Our extended sensorimotor organs are based on technology. If we look for abrain-extending technology we shall find, of course, computer technology. However, the most spectacular achievements of twentieth-century science could not benefit from computer technology; quantum mechanics, thetheory of relativity and molecular biology were invented and developed before the digital computer. Furthermorethe computer only magnifies our computational capabilities and our capabilities for storing, retrieving andmanipulating bits of information. For the time being, it does not help us much in inventing new conceptual systemor scientific theories. Only when the concept-formation capabilities of the AI technology will be significantlyimproved, might it aid science in inventing new concepts and theories.

What is, then, the extended brain which enabled humanity to invent or discover the great ideas and theories of thephysical and biological sciences? It seems that the answer to this question lies not in the realm of technology but







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in the realm of social dynamics. This was the conclusion I arrived at in discussing the first evolutionary pattern. Ipropose to view the network of brains of the scientific community as the extended brain exhibiting cognitivecapacities which transcend those of an individual human being. The cooperative nature of scientific research iswhat makes the progress of modern science possible (Kantorovich 1983, Levinson 1988, Hull 1988). Technologydoes play a role in the formation of this network. Indeed, in the twentieth century, with the advance of

communication technology, science has become increasingly more cooperative and at the same time it haspenetrated environments far removed from the mesocosmos. Indeed, as we have seen, cooperation fostersserendipity and the latter is one of the major driving forces in the evolution of science that enables science to breout a tradition and to create new environments.

However, cooperative social dynamics fulfills an additional epistemic role in exploring foreign environmentscreated by this very social dynamics. This is the role of epistemic support. Cooperation is required in everyday lifwhenever we attempt to solve a complex problem, or a problem which involves many uncertainties. An individuwho encounters a complex problem with uncertain elements needs support and confirmation from others. Anecessary condition for cooperation in problem solving and advancing knowledge is the existence of commonsystems of basic concepts and beliefs. These systems are social products; they evolve as a result of interactionbetween human beings and between them and their environment. In everyday life, a system of concepts andbeliefs, or a world picture, evolves as a result of the experience of human societies in the mesocosmos throughoumany generations. A common world picture enables human discourse and further cooperation in problem solvingand knowledge acquisition.

In technology-intensive science, the problem environment is much less familiar and predictable, much morecomplex and much more rapidly changing than the mesocosmic environment. Our cognitive apparatus which iscapable of guiding us in the mesocosmic environment is not appropriate to do so in the extended environment.Cooperation is what is needed for generating the extended cognitive apparatus for guiding us in this environmentThe extended guiding apparatus is the scientific world picture which is developed in an evolutionary process inwhich ideas and theories are generated and selected by the scientific community. The notion of world picture as Iemploy it here refers to the logic and methods of acquiring new knowledge, as well as to the basic concepts and tentrenched beliefs and theories through which scientists look at the world. According to EE, all these are productof the selection process in science. The world picture which thus evolves extends or replaces the genetically and

culturally based cognitive apparatus which evolved in the mesocosmic environment. It guides scientists inexploring and comprehending the extended environment.







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The scientific community must, therefore, be so structured as to facilitate cooperation in advancing knowledgeinevaluating discoveries as well as in generating them. Thus, instead of relying on his genetically and culturallybased cognitive capabilities, the individual scientist must rely on the world picture generated by the scientificcommunity. The scientific world picture is based on the conceptual system by which the extended environment isdescribed. It includes the system of basic beliefs which guide scientists in constructing and selecting explanatory

theories and general methods of research. This notion is akin to some of the senses given by Kuhn (1962) to hisnotion of the scientific paradigm.

The specific social organization of science aims at arriving in an efficient manner at a common world picture, or a consensus in the scientific community. According to John Ziman (1968), the goal of arriving at a consensus is adistinctive feature of science. However, Ziman does not provide an explanation for why this goal by itself isdistinctive and what is its epistemological significance. According to the view I expound here, science indeedstrives at generating a consensus with respect to the basic world picture. The epistemological significance of thisgoal is to create a collective guiding apparatus for comprehending the extended environment generated andinvestigated by science.

The "collective brain" of the scientific community is not just a collection of brains; it is rather a network of intercommunicating brains which are interlocked via an intricate social infrastructure which channels the social

dynamics of science towards creating a consensus or a widely accepted world picture. The social structure iscomposed of the various institutions of the scientific community which foster cooperation and which support anappropriate division of labor and specializations. This social infrastructure evolves with the advance of science bymodifying the division of labor, by splitting into subspecializations, by integrating separate fields and by creatingnew institutions. The creation of the scientific Academies and Societies signified the emergence of one of thecrucial stages in the evolution of science. Other institutions which have evolved since then are the internationalconferences, research funding, the award system and the publication system.

Twentieth-century physics have witnessed extensive changes in the structure of the scientific community, whichreflect the fast evolution of the world picture of science. In physics, for example, there is a sharp division of labobetween experimentalists and theoreticans. In biology, on the other hand, every scientist acts both as anexperimentalist and as a theoretician; theoretical biology, which has emerged recently as a separate discipline, do

not have yet a major influence on the mainstream of current biological research. Groups of experts which handlenew experimental or computational technologies emerges from time to time. For example, in recent years almostevery branch of science employs computer specialistsa function which did not exist in the fifties. Thus, thecomputer revolution affected the evolution of sci-







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ence. In theoretical physics, there are groups of mathematically oriented physicists who are engaged in developinthe mathematical machinery which is applied by theoretical physicists. There are scientists who concentrate on thfoundations of their discipline. Others are engaged in applied branches of their science. All these functions arecontrolled by the institutions of the scientific community and by its communication network. This network of institutions is the "central nervous system" of the scientific community which controls scientific research. This

description may remind us of the organismic model of society which was employed in sociology and socialanthropology in the nineteenth century. This model described the evolution of society analogously to the evolutioof human organs where specialized groups played the role of organs. I do not mean to adopt this model literally.Rather I employ this model metaphorically in order to make the point that observational and experimentaltechnologies constitute an extension of our sensorimotor organs and that the evolution of these tools isaccompanied by changes in the structure of the scientific community which uses these tools. The principle of coevolution of organs and brain is similarly extended to the structure of the scientific community.

Thus far I have described the evolution of science as a coevolution of experimental technology and the socialinfrastructure of the scientific community. Now I will turn to the evolution of the scientific knowledge, which isgenerated by the "collective brain" and the extended "sensorimotor organs." This will lead us to a social theory oknowledge, or to social epistemology.

7.3.4. The Epistemological Significance of Cooperation in Science: The Evolutionary Perspective

The theory of science which I outline here is a naturalistic philosophy of science. In a traditional logicist approacthe social element does not have any epistemological significance. Only logical facts matter. However, the logicisapproach cannot account for scientific explanation. It is a logical fact that any finite body of observationalstatements can be deduced from an unlimited number of different theories. Namely, for any finite number of observational statements for which we have to provide an explanation, we could construct an unlimited number otheories, in conjunction with initial conditions, from which these statements could be deduced. The problem of generating an explanatory theory is, therefore, formidable. If scientists had a logical method or algorithm for inferring or constructing a theory from observational data, then the problem would not arise, but they do not. Inconstructing a physical theory, for example, physicists since the seventeenth century have had at their disposaltheoretical entities such as epicycles, vortices, media, fluids, powers, forces, poles, fields, waves, particles, string

charges and radiations in any number, combination and configuration, to mention but a few. The theoreti-







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cal system can always be adjusted to yield the requested predictions. In the history of humankind's attempts toexplain natural phenomena we encounter also prescientific or mythical entities such as sympathies, attractions,tendencies, natural loci, ghosts and spirits and the list is only beginning.

As we have seen, although there is an unlimited number of possible hypotheses, in most cases scientist havedifficulties in finding even one explanation. The anarchistic policy recommended by the slogan "anything goes"(Feyerabend 1978) has never been practised in modern natural science. Logic alone cannot tell why the Ptolemaysystem was replaced by the Copernican. Logic alone cannot distinguish between acceptable and unacceptableexplanations. Logic also cannot prevent scientists from inventing any theory they wish, provided it is self-consistent and consistent with the data. When we add methodological requirements such as simplicity and highpredictive power, we may reduce the number of possible theories. However, we face the problem that there is nounique way of measuring these methodological properties (we cannot measure simplicity or count predictions andweigh them). Scientific explanation requires extra-logical criteria and standards for choosing plausible theoriesamong all those which logically account for the data.

Thus, in actual science not every logically possible theory is accepted as an explanation. The logical requirementthat the observational data should be deducible from the theory in conjunction with initial conditions is a necessarbut not a sufficient condition for explanation. The additional requirement for an explanatory theory is that it shou

conform with the established body of knowledge, including the prevailing world picture, and with the generalextralogical criteria. At any given period there is a general conception of what an explanatory theory should looklike, and a repertoire of exemplary models of explanation, which narrow the range of acceptable hypotheses. Forexample, in the nineteenth century, the mechanistic-curpuscularian picture dominated physics; mechanics wasregarded as the paradigmatic theory. Hence, attempts were made to construct explanatory theories in fields such alight, electricity and magnetism in terms of mechanical models. Lord Kelvin, a very respectable physicist,proposed, for example, the following model for the structure of the luminiferous aether, which was supposed to bthe weightless elastic medium carrying the action of the electric and magnetic forces:

...a structure is formed of spheres, each sphere being the center of a tetrahedron formed by its four nearestneighbours. Let each sphere be joined to these four neighbours by rigid bars, which have spherical caps attheir ends so as to slide freely on the spheres. ... Now attach to each bar a pair of gyroscopically mounted

flywheels, rotating with equal and opposite angular velocities... (Whittaker 1951, 145)







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arrangements and theoretical machinery. They are also characterized by the fact that the act of observing them isnot an act of an individual but a cooperative act. And perhaps one of the measures of the degree of theoreticity oan entity is the number of scientists and groups of scientists needed for the act of ''observation."

Contrary to what is going on in many areas of philosophy, a scientist is not engaged most of the time in criticizinhis fellow scientists; he relies on their work. I have already mentioned Newton's words to the effect that he standson the shoulders of giants. They reflects this attitude; scientists rely on other scientists both synchronically anddiachronically. Thus, the scientific world picture summarizes the collective experience of a community of scientists. Since the reliance on other scientists' work is so crucial, the scientific community is engaged not onlywith investigating natural phenomena but also with surveying the capabilities of its members and "grading" themthe scientific community is a complex instrument for probing remote territories of nature, hence all its parts or components should be constantly "calibrated." With the emergence of science as a cooperative enterprise whichrelies on experts operating sophisticated technology and employing sophisticated mathematical machinery, thisactivity of assessing the performance of the community members has become institutionalized in the award systemof the scientific community, in paper- and citation-counting and in many other formal and informal means of ranking.

Thus, the scientific community is a social system in which cooperation in acquiring knowledge is institutionalized

and the individual's opinion is not recognized as a legitimate knowledge claim before it is processed by the organof the community. Via this processing, a proposed idea is assessed, improved, or modified and integrated withother ideas, or it is rejected. As we have seen, for the scientist, the ultimate truth-criterion is the acceptance by thscientific community. According to this view, this is the only possible and recommended criterion, especially innormal science, since there is no way for the individual scientist to know whether he discovered some truth in theextra-mesocosmic domains dealt with by modern natural science. A similar view is expounded by Hull (ibid.) whclaims that the main aim of a scientist is in disseminating his ideas rather than in discovering truth.

Just as our genetically based cognitive capacities do not necessarily reflect absolute truth, so is the scientific worlpicture. Both reflect those aspects of reality which have something to do with the needs, preferences and interestsof humankind, on the organic and cultural levels.

7.4 The Tension between Change and Stability

The tension between innovation and tradition is built into the evolutionary POR. A proliferation of ideas andhypotheses is vital for the progress of sci-







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ence as an evolutionary process, since variability is the source for evolutionary progress; the generation of variantgenes (or ideas) which are usesless at the time of their appearance might be useful for the future adaptation of thespecies (or of science) to its environment. Natural selection favors, therefore, variability and adaptability. Thesocial system of science provides a fertile soil for producing a variety of ideas which constitute the raw materialfor the process of selection in science. The strive for originality is a major driving force in the scientific

community. However, originality is restricted by tradition. Hence, the phenomenon of serendipity is essential for generating ideas which deviate from tradition.

Thus, science is a cultural form which exhibits two seemingly contradictory trends: on the one hand, it narrows thrange of acceptable ideas, and on the other, it fosters variability of ideas. These two complementary trends arenecessary for progress. Conformity with tradition is essential for progress in a given direction; it enables theexploitation of the potentialities hidden in the existing world picture. Whereas variability is necessary for enhancing the chances of hitting upon new ideas in order to modify or replace the present world picture by a bettone. We face here, therefore, a dialectic situation in which change and stability play an equally important role. Inorganic evolution the parallel situation is that a large number of mutations endanger the phylogenesis of thespecies. The mutations should bring about useful changes in the gene pool of the species without undermining thecentral characteristics of the species. In cultural evolution we have a similar situation: the deviation fromtraditional norms is necessary for cultural progress, however cultural changes should not endanger the informationcontained in the cultural tradition, including scientific tradition.

The dialectics between change and stability can be illustrated by J. Bronowski's model of stratified stability(Bronowski 1970), as applied by Ervin Laszlo (1972) to the evolution of science. According to Laszlo, science cabe treated as an open system, analogous to an organismic system, which develops and grows as a result of information input from its environment ("nature") through a series of intermediary states, on its way to equilibriuwith its environment. These intermediary states are far from equilibrium. Some of them are more stable thanothers, i.e. they resist disturbances from the environment for a relatively long period of time. The informationinflow, which consists mainly of empirical data, enables the system to grow, so that the potentials inherent in thesystemthe hidden strata of stabilityare actualized. In a state of stability the system retains its main characteristics the face of disturbances from the environment such as anomalies or experimental data which do not fit thetheoretical system. A stable state of science corresponds to something like normal science with a stable world

picture or paradigm. When the disturbances exceed a certain limit, the system will lose its stability and after aperiod of instability will eventually reach a new state of







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stability. This transition corresponds to a scientific "revolution" or to a radical theoretical change, or to a radicalchange in the world picture. When the system climbs up the strata of stability, it becomes progressively moreresistant to disturbances; the new state of the theoretical system accounts for the phenomena explained in thepreceding state plus the unexplained anomalies and new data. Thus, unlike in a Kuhnian revolution, in which thesuccessive paradigms are incommensurable, a higher stratum of scientific knowledge in the above model can be

compared with the preceding one; the transition to a new state of stability means progress. This agrees, for example, with the physicists' intuition that the transition from classical physics to quantum and relativistic physicconstituted a progress.

This kind of evolutionary model requires, therefore, a variability of ideas which will enable the system toaccomodate the inflow of information and to climb up the evolutionary ladder. However, when the system stays ia stable state it attempts to exploit the potentialities of that state of knowledge and to explain as much data aspossible. It would not be wise to try climbing the ladder prematurely, before the present rung is stabilized and fulexploited, since the next stratum will be erected on the present one. For example, Newtonian physics was notreplaced before its potentialities were maximally exploited. Thus, at a period of stability, i.e. in normal science,mainly ideas which conform with the world picture should be employed and investigated. Novel ideas will be keaside provisionally to be activated at a time of crisis. But the activation of these ideas will not be by intention;rather it will be a result of a serendipitous event.

This model can therefore provide the basis for the concept of "gradualism" underlying the principle of serendipitySerendipitous discoveries are variations generated unintentionally in the course of methodical research taking plain normal science, which represents a stratum of stability in the evolution of science. Eventually they may bringabout a transition to a new state of stability. A serendipitous development is more likely to occur at a time of criswhen the system loses its stability as a result of disturbance caused by some acute problems awaiting a solution.These problems trigger off an interpsychic "chance-permutation" process in the collective mind of the scientificcommunity. If we make the analogy with the intrapsychic process, we may treat this process as an "incubation"process. Thus, when scientists encounter the missing piece in the puzzle, a stable configuration is formed and theincubation process terminates. We may identify the system of "mental elements" which are distributed throughouthe scientific community as the open system referred to by Laszlo. When a major new configuration is formed inthis manner, the system undergoes a transition to a new state of stability. Thus, the system climbs up the strata of

stability via serendipitous discovery.







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7.5 Implications for Discovery

7.5.1 The D-J Distinction Revisited

At first sight, it seems that the D-J distinction is valid in the evolutionist POR since there is a clear distinctionbetween the process of variation-generation and the process of selection. Furthermore, the main import of thenatural selection model is that the way by which a variation was generated is irrelevant to the selection-evaluationprocess, in the sense that the environment "opportunistically" selects quasi-random variations.

Since in organic evolution variations are not produced by agents who are capable of acting intentionally, there is nsense in talking about a mutation which is produced "in order to" overcome an environmental pressure. In sciencehowever, variations can be produced by intentional acts. Hence, if we believe that genuine discoveries must beproduced "blindly," we would treat favorably only ideas and theories which have been produced without knowingin advance the phenomena which will be eventually explained or the problems which will eventually be solved bthese theories or ideas. Only in this respect is generation relevant to evaluation. However, in this case informationconcerning generation is relevant to evaluation in the negative sense. As we have seen, scientists treat unfavouraban ad hoc hypothesis, which was produced with the knowledge of the phenomena and the data which it eventuallexplains.

Thus, we encounter here the antithesis to the D-J distinction thesis. The D-J thesis, which was inspired by theempiricist attitude, can be seen as directed against rationalism. In the Cartesian system, a conclusion which isvalidly derived from first principles is considered to be necessarily true, irrespective of any empirical observationEmpiricism implies an opposing view reflected in the D-J thesis: a hypothesis is refuted or confirmed byobservation, irrespective of its source. However, even without being guided by the evolutionist POR, astraightforward objection would arise: what about the case where the hypothesis was constructed in order to matcalready known data or to explain already known phenomena? If the same observational results which wereemployed in constructing the hypothesis serve also as the ultimate court of appeal for judging it, something iswrong with this kind of "justice." The evolutionist POR and the principle of serendipity give us a definite reasonfor having this intuitive feeling of "injustice." In other words, the theory of natural selection provides a deepexplanation to this methodological rule. Thus, the empiricist requirement that evaluation should depend only on

observation will lead us to the absurd result that one can "cook" his hypothesis to match the data and continue todo so indefinitely; whenever some new predictions of the hypothesis do not agree with the observation, one wouladjust his hypothesis to the recalcitrant data. Even if in the course of doing so, the flexible hypothe-







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sis does not yield any successful predictions, the empiricist requirement will still be obeyed and the D-J distinctiothesis will still be valid, without gaining any genuinely new knowledge in the process. The evolutionist POR andthe principle of serendipity remedy this deficiency by demanding that information concerning the process of discovery or generation be relevant to the evaluation in the following respect: the hypothesis should be arrived atblindly or serendipitously. This includes the widely acknowledged requirement that a hypothesis would yield

unexpected predictions which agree with the observation, including predictions of already known effects whichhave not been taken into account in devising the hypothesis. The evolutionist theory provides us with anexplanation for this evaluative requirement. According to our justificatory-explanatory scheme, we should makesure that this requirement or rule is indeed practised in science. If the rule has been practised in most cases, or inmost important cases, we still would not be entitled to recommend it to scientists since it might be an accidentalrule. Only if the rule is backed by an explanatory theory, then it has a normative strength, according to our non-absolutist conception of justification.

7.5.2 Cultivation: Preparing the Collective Mind

Socio-evolutionary processes of discovery are not controlled by the individual scientist and the products of discovery cannot be evaluated by him. Thus, the distinctive features of the sociologist POR is that "rules" of discovery are not directed solely towards individuals but also, and perhaps mainly, towards the institutions of the

scientific community.

If we employ the metaphor of the farmer who cultivates the soil and scatters the seeds, we would say that the seedin this process are the ideas which initiate the cooperative process of discovery. These ideas are sown in the mindof the members of the community. Thus, the scientists' minds are analogous to the ground or the soil in which theseeds are sown. The process is nourished with other ideas which are already present in the minds of the membersof the community. Some are brought from other fields. This "soil" is cultivated only if two main requirements aremet: First, the members of the scientific community should be knowledgeable in the field so that they can"nourish" the body of knowledge which is growing out of the original ideas. A major source of "nourishment"comes from information obtained from ongoing observations and experiments. Second, there should be acommunication network conveying the ideas to all members of the community, and a social infrastructure whichencourages scientists to submit their ideas for public scrutiny through this network. The institutional advice will b

that the scientific community will foster epistemic cooperation by setting up appropriate norms and appropriateinstitutions. If these requirements are met, we may talk about the "collective mind" of the scientific community,which provides







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the fertile soil for discoveries to flourish; by the act of cultivation, we prepare the collective mind.

The dependence of the final product on observational data that nourishes the process of discovery reflects thelegacy of empiricism. Different data would lead to a different product. The product is also cultivated by ideas,knowledge and information embedded in the scientific community. However, also the social characteristics affectthe final product. Without an efficient communication network, the process would not benefit from all the ideasand information spread throughout the community; actually the whole process, which is cooperative in nature,would not come into being. This social element is absent from traditional empiricism. The recommendations for cultivating discovery may, therefore, be of two categories. First, recommendations regarding the social structureand dynamics of the scientific community. Second, recommendations regarding the kind of knowledge processed("nourished").

The above recommedations are directed to the whole community. In parallel, there are recommedations for theindividual scientist. The first recommedation to the scientist would be to integrate within the scientific communityThe individual scientist should not keep his ideas to himself, trying to be original. He should submit his ideas topublic scrutiny not only for giving other scientists the opportunity to criticize them, but also for employing theideas in different contexts. This also applies to long-range historical processes which may be triggered off by theoriginal idea and which result in great discoveries. Another recommedation is to be socially involved in order to

pick up the climate of opinions, or the emerging collective world picture, which determines what kind of ideashave more chances to be accepted for processing by the community.

From a related view, according to which the collective world picture of the scientific community is mainly a taciknowledge, one might derive a similar recommedation. It is not advisable to spend all the time sitting in the librarand reading textbooks and even research papers. In a less developed science and in contemporary scienceeducation, the prevailing conception is that the alternative to "indoors" activities such as textbook reading andattending lectures is to go to the field, make observations and experiments. According to our socially orientedview, a different advice is offered: Travel as much as possible and observe your colleagues at work and atmeetings. Indeed, the twentieth-century scientist is a travelling scientist, no less, and maybe more, than anexperimenting scientist.

7.5.3 Strategies of Discovery

The two evolutionary patterns discussed in section 7.3.3 have immediate implications for the strategy of generatinnew theories. The principle of growth by expansion implies that solutions for problems arising in a given







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domain may be found by going beyond that domain. Serendipity may carry us unintentionally beyond the presentdomain or stratum of knowledge. Hence, rules for cultivating serendipity will have implications for this strategy. problem solver who deals with problems in a given domain may discover a solution to a problem in another domain. However, scientists can try intentionally to look for broader domains in order to solve unresolvableproblems or to explain recalcitrant anomalies. This advice may be implemented by trying to generalize present

concepts and theories and by trying to perform experiments in wider domains. For example, in particle physicsanomalies were resolved and explanations were provided by a chain of generalizations: first, the notions of electrcharge and charge independence of nuclear forces were generalized to the notions of isospin and isospin-symmetry. Then, the notion of hypercharge was invented and isospin was generalized to SU(3) symmetry, wherethe isospin symmetry was included in this symmetry. Every such generalization yielded new predictions, whichhad to be tested by new experiments and new experimental methods which involved collision experiments athigher energies. Thus, theoretical expansion proceeded hand in hand with aggressive experimental intervening.There is no general recipe as to how to implement this strategy of problem solving by expansion and interventionit is left for the creative and skillful scientist to find the direction of generalization, to invent fruitful concepts andto perform new kinds of experiments. In so doing, he may learn from preceding cases and try to imitate them. Infact, the above chain of generalizations was generated by scientists imitating successful models.

Polya offers the following rules for problem-solving. The first rule is: "Stay as close to the problem as possible."And he adds: "Yet we cannot predict how close to the problem we shall be able to stay." He offers a principle of gradual advance: "we first explore the proposed problem itself; if this is not enough, we explore the immediateneighborhood of the problem. If even this is not enough, we explore a wider neighborhood; whenever our exploration fails to discover a path to the solution, we are obliged to go further. ... Yet be prepared to go as far away from the problem as circumstances may oblige you to go" (Polya 1965, 9192). These rules clearly express aexpansionist strategy of problem-solving, although a step-by-step expansion.

The methodological implications of the principle of coevolution of the sensorimotor and cognitive capacities arenot always clearly recognized or practised by scientists. When a scientist proposes a radically new theoryprematurely, without having sufficient experimental data, he is violating this principle. For instance, we can viewProut's model (nineteenth century), which described all atoms as composed of hydrogen atoms, and the 1932 modthat described them as composed of nucleons and electrons as two theories based on almost the same fundamental

idea: that every atom is composed of basic units which have the characteristics of the hydrogen atom.







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However, Prout's theory was premature. The nucleon theory could benefit from the data accumulated in chemistryand physics since Prout's time. This required the evolution of experimental techniques, such as those employed byRutherford, Geiger and Marsden for unveiling the structure of the atom. And vice versa: when a scientist preformnovel experiments without having a sufficiently elaborated theory for guiding him, he is violating the principle. Inthe first case, we would say that the theory is too speculative, or premature, and in the second casethat the

experiments are going ahead of theory. In general, the principle implies that the rate of theoretical growth will noexceed the rate of experimental growth and vice versa.







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Chapter 8Tinkering And Opportunism: The Logic Of Creation

Heraclitus says that man's conjectures are like children's toys.Iamblichus, De Anima (Wheelwright, 88)

8.1 Evolutionary Tinkering in Science

In this chapter, I would like to introduce the notion of tinkering , which will shed light on the significance of allkinds of unintentional, serendipitous and opportunistic processes of scientific creation. Levi-Strauss (1962)introduced this notion in describing savage thought and Francois Jacob (1977) borrowed it for characterizingevolutionary progress. The basic idea can be described in the following way.

In addition to the model of blind-variation-and-selective-retention, which underlies evolutionary changes,evolutionary progress is characterized by the following historical pattern. The evolution of organs along anevolutionary line is not a preplanned process. Rather than reflecting a program or a purpose, the structure of an

organism reflects the past, namely the history of the evolutionary line. If the evolutionary line starts with a certainstructure, imperfectly adapted to a certain niche, all future adaptations to changing environmental conditions will "ad hoc" modifications imposed on the initial structure. Note that these "ad hoc" modifications are not generated aa response to environmental pressures. According to the natural selection model, they are generated as blindvariations. Environmental pressures select them opportunistically from the repertoire of variations thus formed. Inthis way, organs undergo changes which make them capable of performing new functions.







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Jacob offers several examples of tinkering. For instance, he describes Ernst Mayr's hypothesis (1964) about theformation of the lung of terrestrial vertebrates:

Its development started in certain fresh water fishes living in stagnant pools with insufficient oxygen. Theyadopted the habit of swallowing air and absorbing oxygen through the walls of the esophagus. Under theseconditions, enlargement of the surface area of the esophagus provided a selective advantage. Diverticula of the esophagus appeared and, under continuous selective pressure, enlarged into lungs. Further evolution of the lung was merely an elaboration of this themeenlarging the surface for oxygen uptake andvascularization. To make a lung with a piece of esophagus sounds very much like tinkering. (Jacob, 1164)

A second example offered by Jacob is the evolution of the human brain. The latter was formed by imposing newstructures on old ones. The neocortex, which controls intellectual and cognitive activity, was added to therhinencephalon of lower mammals, which controls emotional and visceral activities. "This evolutionaryprocedurethe formation of a dominating neocortex coupled with the persistence of a nervous and hormonal systempartially, but not totally under the rule of the neocortexstrongly resembles the tinkerer's procedure. It is somewhatlike adding a jet engine to an old horse cart" (ibid., 1166).

Other examples may be added: according to some evolutionary theories, jaws were developed in fish from gill

arches, and legs developed from fin supportsto serve perhaps for locomotion in very shallow water. Homo sapienshands, which paved the way to human culture, were probably developed from the forelimbs of a predecessor species which served mainly for climbing trees. It should be stressed that not every structure is amenable to everyad hoc modification, and if the latter is successful, it is due to the potentialities inherent in the original structure.

The above pattern has its counterparts in the evolution of science, when scientists exploit existing tools for newtasks. This might happen to an individual scientist, or to a local group of scientists, when they employ a tool theyhappen to have, or to a whole scientific community, when they use an element of their tradition for solving a newproblem. This phenomenon exhibits "opportunism" or tinkering.

The notion of evolution as tinkering is expressed by Jacob as follows: "Natural selection does not work as theengineer works. It works like a tinkerera tinkerer who does not know exactly what he is going to produce but usewhatever he finds around him...uses everything at his disposal..." (ibid.). Each of the materials and tools he findscan be used in a number of dif-







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ferent ways. The use he makes of the materials and tools around him depends on opportunities. ''Evolution behavelike a tinkerer who, during eons upon eons, would slowly modify his work...cutting here, lengthening there, seizinthe opportunities to adapt it progressively to its new use. ... It does not produce novelties from scratch. It works owhat already exists" (ibid.).

According to this view, weour organs and brainare the products of tinkering. I suggest that the theories of molecular biology and particle physics, for example, are also the products of tinkering. This would be a plausibleconclusion of a theory which views science as the extension of our sensorimotor organs and cognitive apparatus.Since we expound here an evolutionary theory of science, and since we have already seen some evidence insupport of the serendipitous and opportunistic facets of scientific discovery, it would be natural to conjecture thatthe above conception applies to science. The main point implied by the notion of tinkering is that evolution "workon what already exists." This point was emphasized in Chapters 5 and 7, where it was related to the gradualist vieof scientific progress.

Knorr-Cetina (1981, 34) illustrates the notion of tinkering as it is reflected in laboratory practice, when the scientuses the local material resources at his disposal and exploits situational contingencies in an opportunistic manner.However, in science, opportunism and tinkering are not restricted to the manipulation of tangible resources.Opportunism is exhibited, for example, in the phenomenon of intellectual migration; the scientist "carries" with

him his tangible and intangible tools of research when he moves from one field to another, seizing opportunitiesfor using the tools in different contexts. A scientist acts as a tinkerer when he makes a serendipitous discovery; heexploits an opportunity which occurred to him for solving a problem. A scientist may exploit situationalcontingencies, such as an idea which occurred to him, as well as a piece of equipment which happens to be in hispossession.

In particular, tinkering is characteristic of the situation when there is no widely accepted theory in a field andscientists proceed by employing theoretical tools and models they find "around them," which have been used for other purposes. In other cases, when a general theory is available, scientists try to explain unexpected phenomenaby making ad hoc modifications, "cutting here, lengthening there." In fact, these are the situations which prevail imost fields of science most of the time; either a general theory has not been discovered, or there is a general theowhich has been successfully applied only for solving problems in a certain domain, and in order to extend its

domain of application, it has to be modified. The difference between this kind of ad hoc modification and the kintreated unfavorably is that in the latter kind scientists devise the modification in response to the problem to besolved, whereas as tinkerers they employ existing elements they find ready for use.

For the sake of illustration, I will give two examples; one is from Greek science and one from modern times. Thefirst example of tinkering can be







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found in the Timaeus. Plato (429348 B.C.) set out to construct a theory of matter. He worked in the Pythagoreantradition which determined the range of (intangible) materials and tools he found "around him." He incorporatedinto his theory elements from the theories of his predecessor, Empedocles (490-430 B.C.), and his contemporary,Democritus (460370 B.C.). He wanted to erect Empedocles' theory of four elements on geometrical foundations. his disposal was a recently discovered mathematical theorem. Theaetetus (415?369 B.C.) found that there are onl

five regular convex polyhedra: the tetrahedron, the cube, the octahedron, dodecahedron and icosahedron. Platoseized upon this opportunity and tried to match the four elements and the five solids. He devised intricatearguments for choosing the tetrahedron as the atom of fire, the cube as the atom of earth, the octahedron as that oair and the icosahedron as that of water. No earthly element remained to match the dodecahedron, which consistsof twelve pentagons. Plato matched this polyhedron with the boundary of the universe. Thus, for solving hisproblem, Plato used a mathematical theorem that happened to be discovered at his time. He opportunisticallyexploited an existing tool for constructing his theory. This reminds us of cases where the modern physicist emploa recently developed mathematical tool for solving his problems.

Toulmin and Goodfield (1962) describe Plato's theory, and they add the following remark in brackets: "The closeapproximation of the dodecahedron to a sphere was well known to the Greeks, who made their footballs frompentagons of leather sewn together in sets of twelve" (ibid, 86). This is presumably an insinuation that in devisinghis theory, Plato may have drawn upon this piece of information. As a support for this speculation, we may notethat among the five solids, it is the icosahedron, rather than the dodecahedron, which has the largest number of facesi.e. twenty triangles. So that at first thought, one might think that the icosahedron is the closest approximatioto a sphere. If this plausible conjecture is correct, it might further confirm the view that in devising his system of geometrical atomism, Plato acted like a tinkerer. The intricate system of argumentations by which Plato justifies hchoice gives the impression that he arrived at his discovery only by pure reason. Thus, according to the aboveinterpretation, we can distinguish here between the context of justification and the context of generation, where tlatter was dominated by tinkering.

The second example is the chain of events which led to Rutherford's discovery of the emptiness of the atom.Rutherford discovered alpha particles in 1899. He and his colleagues had been conducting experiments with thesparticles for several years. Rutherford later recalls: "One day Geiger came to me and said, 'Don't you think thatyoung Marsden, whom I am training in radioactive methods, ought to begin a small research?' Now I had though

that too, so I said, 'Why not let him see if any alpha particles can be scattered through a large angle?'" (ibid.). Therest of the story was told in section 2.2.







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Geiger tried to exploit his trainee's expertise for "a small research." He had the tool and he looked for a problem.Rutherford suggested one. Rutherford did not believe the exercise would yield anything of great interest. Theexperiment which led to the greatest revolution in humanity's conception of the structure of matter was a result ofsheer tinkering. Here it was a skill, or a human resource, that was exploited.

In general, when a scientist uses an existing model for solving a new problem, it looks very natural. However, thican be viewed as the work of a tinkerer. In particular, solving problems by making analogies can be viewed astinkering. This is one of the major ways of generating novelty in science. When the scientist encounters aphenomenon which requires an explanation, he tries to explain the phenomenon by making an analogy with afamiliar one which is explained by a familiar model. He does not look for the best explanation possible or theoptimal solution to his problem. Rather he employs familiar models. Thus, he adopts the strategy of the tinkerer. the analogy is successful and applies to a wide range of phenomena, it may develop into a full-fledged theory. Inthis case, the way to novelty is paved by tinkering.

The scientist does not try to find or devise the best conceivable solution to his problem. He picks up whatever model he can find around him, a model he is already familiar with. This is, for instance, what Leverrier did whenhe proposed his conjecture about the existence of the planet Vulcan. Leverrier had suggested this model for explaining the anomalies in the motions of Uranus and it had worked successfully. In the case of Mercury,

however, it did not work. In fact, in normal science, every scientist who employs a model drawn from the restrictrepertoire of models of the tradition acts as a shortsighted tinkerer who employs Polya's rule that was mentioned the last chapter: "Stay as close to the problem as possible" and "be prepared to go as far away from the problem acircumstances may oblige you to go." This recommendation is diametrically opposed to Popper's policy. The lattewould require that scientists propose bold conjectures that go as far as possible from what is already known.

8.2 Tool-Oriented Scientists: Intellectual Migration

Tinkering provides the raw material of variations for the selection process. If all scientists find around them anumber of similar models that belong to the tradition, the number of variations will be restricted. One way of increasing the range of variations is to encourage the flow of ideas from other fields. In the last chapter, Imentioned the phenomenon of intellectual migration as a







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novelty-generating mechanism. Scientists move to a new area of research and apply the tools or techniques theyemployed in their original field for solving the problems they encounter in the new area. We may say that thesescientists are "tool-oriented," rather than " problem-oriented." They are not primarily interested in a specificproblem, rather they look for new opportunities for using their tools. Their tools are "solutions in search of problems." This opportunistic behavior is characteristic of the above pattern of biological evolution. Genes which

were selected for their function in overcoming certain environmental pressures, are opportunistically exploited inovercoming new pressures, possibly in a new niche. Thus, these tools which were developed for solving a given of problems A are exploited for solving a new set of problems B. The process whereby these tools were generatewas, therefore, ''blind" to the problems they eventually solved.

Drawing upon Dubos' book (1951), Mulkay relates the example of Louis Pasteur (Mulkay 1972, 917) "who movecontinually from one area of research to another, seeking significant problems and attempting to resolve them bythe introduction of ideas and techniques developed during his earlier work." No one would blame Pasteur for beinan opportunist, in the negative sense of the word. Rather opportunism was his method of research, and it proved tbe quite successful. He started his work in a well-established tradition of crystallographic research. First, he solvthe problem of why tartrate solution rotates the plane of polarized light, while the paratartrate is optically inactiveBoth are chemically identical, but, as he found out, the optically active tartrate has an assymmetrical crystallinestructure, whereas the paratartrate is a mixture of right-handed and left-handed crystals. After Pasteur acquiredrecognition for his research on tartaric acid and molecular and crystalline dissymmetry, he began to pursue hishypothesis that life is a function of molecular dissymmetry. This work evoked strong objections in the scientificcommunity. Then he moved on to the problem of fermentation. Since the processes of fermentation gave evidenceof molecular dissymmetry, he conjectured, against the accepted view in the field, that they are related to theactivity of living organisms. Then he turned to spontaneous generation and attempted to prove that it does notexist.

Another example which is offered by Mulkay is the growth of the phage network within molecular biology (ibid.3435). During the 1930s, a group of physicists, including Delbruck and Szilard, "concluded that research inphysics was unlikely to reveal any interesting problem for some time to come; that biology seemed to offer themost promising opportunities for using the physical methods with which they were familiar." They undertook research into bacteriophages. Since they used the distinct methods they brought with them from physics, they

formed a distinct group which developed later into the new field of molecular biology. Following the discovery othe structure of DNA by Watson and Crick, the field grew explosively. There was a continuous flow of physicists







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of the "general" or the "unified" theory is restricted to a more or less narrow range of phenomena, and in order toadjust it to a wider range, they will have to resort to tinkering again. This pattern of development has beencharacteristic of physics since the advent of quantum mechanics. But in particle physics it was pushed to itsextreme.

The opportunistic exploitation of existing tools for new tasks, as it has appeared in particle physics, is described bAndrew Pickering under the title "opportunism in context" (Pickering 1984). However, Pickering treats thisphenomenon on a "shallow" level, without offering a deeper explanation for it. Equipped with the evolutionarymodel of tinkering, we can exploit this opportunity and offer an explanation for this phenomenon.

According to the picture offered by Pickering, each scientist, in the course of his scientific experience, has acquirtangible and intangible techniques and methods and he seizes upon opportunities to use the resources at hisdisposal in different contexts. If an individual scientist successfully exploits an existing tool for solving a newproblem, this can be viewed as personally motivated opportunism since it would lend him recognition. But whenthe tool belongs to the shared resources of the scientific community, the community might adopt it for solving theproblem. In this case it may be viewed as communal opportunism. In some cases the tool may not be familiar tomost members of the community. And yet, if it is successfully exploited for solving current problems, it might beadopted by the community, although some time will elapse before the new tool is assimilated into the shared

resources.

Employing traditional terminology, we would say that particle physics has been developed through a process of making analogies and constructing models. From our present viewpoint, we would say that, in a typical case, wheparticle physicists have faced a new problem they have tried to employ the theoretical or experimental expertisethey had at their disposal for solving new problems. In describing hadrons as quark composites, they used themodel which proved successful in atomic and nuclear physics, describing the atom as composed of electrons andthe nucleus, and the nucleus as composed of nucleons. Quantum electrodynamics (QED), that treatedelectromagnetic interactions with great success, served as a major resource for constructing theories and models fweak and strong interactions. It inspired the development of relativistic quantum field theory and later, of currentalgebra and gauge theories of quark and lepton interactions. The composite model and QED were among the majitems included in the standard tool-kit of the particle physicist. Let us turn to some major examples.

8.3.1 Symmetries without Dynamics

In order to illustrate the mechanism of the analogical extension of existing theoretical tools into new areas, let usconsider first the era of internal symme-







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tries in the history of elementary particle physics, when particle physicists extensively employed group theoreticatools. Some of these tools were inherited from pre-World-War-Two atomic, nuclear and relativistic physics, andsome were borrowed directly from mathematics. These tools were applied to symmetries and conservation lawswhich, in the absence of a satisfactory dynamical theory, were supposed to bring order into the plethora of particland their interactions.

The application of symmetry groups to elementary particle physics began with the introduction of the notion of "isotopic spin" (later called "isospin"). The first step in the invention of isospin was made by Werner Heisenberg 1932, immediately after the discovery of the neutron, when he introduced the notion of nucleon. Heisenbergsuggested to look at the proton and the neutron as two states of the same "particle," the nucleon. He employed hethe quantum-mechanical machinery of spin, introduced by Wolfgang Pauli in 1927 for describing the electron spiThe electron had been described by a wave function with two components, corresponding to the two spin states othe electron''spin up" and "spin down." Spin was an angular momentum magnitude, describing spatial properties othe electron. The spin formalism had been invented to explain the fine structure of atomic spectra. It was notsupposed to distinguish between charge states.

Thus, in order to adapt to the new situation which came about with the discovery of the neutron, Heisenbergexploited the spin formalism. We might say that he made here an analogy with spin. But the notion of analogy w

not capture the significance of the innovation. Everything can be made analogous with everything. Which analogis acceptable and which is not is determined by the standards prevailing in the scientific community. According tothe prevailing conceptions, the two phenomenathe existence of two spin states of a particle, and the existence of two particles which are close in their mass and differ in their electric chargewere far from being similar. Byexploiting the spin concept for describing the proton and the neutron as two states of one "particle," Heisenberg sup a new standard of similarity, which paved the way to the notion of "internal" symmetry, eventually leading tothe SU(3) symmetry and the quark model.

The spin operators generated an SU(2) group of rotations in ordinary space. Isospin did not correspond to rotatioin ordinary space. Eugen Wigner later described the isospin operators as the generators of a new SU(2) rotationgroup in an abstract isospin space, in analogy with the SU(2) group of ordinary spin. Thus, the notion of isospinbrought with it the resources of group-theory into elementary particle physics. Hadrons were classified into iso-

multiplets, in analogy with the splitting of the energy levels of a spin multiplet. These corresponded to therepresentations of the SU(2) group of isospin. This led to a conservation law for isospin, in analogy with the lawcoservation of angular momentum. One of the variations in the analogical







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transfer from spin to isospin was that isospin conservation was violated by electromagnetic and weak interactionswhereas angular momentum was universally conserved. The symmetry-breaking due to these violations of thesymmetry was responsible for the relatively small mass difference between the members of an iso-multiplet, i.e.between the pions (forming an iso-triplet) or between the nucleons (forming an iso-doublet). Thus, the abovevariation was represented by the notion of symmetry-breaking. Symmetry-breaking within an iso-multiplet was

small in comparison to the strong interaction and this was expressed by the small mass differences between themembers of an iso-multiplet.

The particle physicist in the fifties was equipped with the conservation laws of energy-momentum, angular momentum, electric charge, baryon number, lepton number and parity, which were regarded as having universalscope. The appearance of isospin introduced the notion of conservation law which is not universally obeyed. Thishas been the evolutionary pattern to follow. The price of extending the application of an existing tool to a newarea, or to solving a new kind of problem, was the modification of the tool. As agents capable of actingintentionally, physicists devised some of the modifications in response to the problems which they faced. This kinof modifications was, therefore, treated unfavorably. The general feeling among particle physicists was that thesewere ad hoc modifications, in the "bad" sense.

Strangeness was the next quantum number which was introduced into the elementary particle tradition by Gell-

Mann (1953) and Nishijima (1954), for solving the problem of why some strongly interacting particles weredecaying slowly as in weak decay processes. The conservation of strangeness was modeled on the conservation ocharge, but with a slight variation. It was not universally conserved; it was not conserved by weak interactions.

After the isospin symmetry was established, it served as a model for constructing theories of "internal" symmetrieIn the next step the SU(2) group was extended to include strangeness. And finally the SU(3) symmetry, or theunitary symmetry, proposed by Gell-Mann (1961) and Ne'eman (1961), was selected. Since the unitary symmetrywas modeled on isospin, it was sometimes called "unitary spin." As Pickering rightly notes, both Gell-Mann andNe'eman aimed at constructing a gauge theory as a particular version of quantum field theory of stronginteractions, as well as providing a classification scheme of hadrons. But in the following years, quantum fieldtheory quickly went out of fashion. So that "very soon after its invention, SU(3) was divorced from its roots ingauge theory and left to stand or fall on its merits as a classification system" (ibid., 57). This was, therefore,

another example of a partially serendipitous event. The main point was that in the construction of the theory, thetools of both quantum field theory and the armory of symmetry groups were employed, without knowing inadvance what would be the nature of the final product.







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Again, a further ad hoc variation was imposed on the model. The relative mass-differences between the membersof an SU(3) supermultiplet were much bigger than in the case of an iso-multiplet. The large broken symmetry waaccounted for by the Gell-Mann-Okubo mass formula (Gell-Mann 1961, Okubo 1962). This formula enabled theprediction of the mass of the missing member of the unitary decuplet, the W-, which was detected in 1964 at theAlternating Gradient Synchrotron at Brookhaven (Barnes et al. 1964), having the predicted mass.

The next step was SU(6). Gursey, Pais and Radicati (1964) constructed this group by analogy with the approximaSU(4) symmetry of the nucleus proposed by Wigner in 1936 (Wigner 1937). The latter corresponded to thecombination of two SU(2) symmetries: isospin independence of nuclear forces and spin-orientation independenceof the nucleons within nuclei. The SU(2) of isospin was extended to the SU(3) of unitary symmetry. The result wan approximate SU(6) independence of strong interactions. The variation here arose from the problems related tothe fact that the symmetry was good only for non-relativistic cases. The attempts to extend the group so that itwould accommodate both the Lorentz group (which represented the relativistic effects) and SU(6) were notsuccessful. But, in the meantime, these efforts yielded a variety of groups, which were not symmetry groups, andwhich included the Lorentz group, having infinite representations.

The termination of this evolutionary line came as a result of the appearance of the quarks (as theoretical entities).But the origin of quarks was in this evolutionary line: in the SU(3) symmetry. Eventually, the unitary symmetry

was abandoned and the quarks have remained. This is a perfect example of a cooperative-historical creativeprocess. It started with Heisenberg's idea of isospin and ended up with the discovery of quarks. When Heisenbergproposed his idea for explaining the difference between the proton and the neutron, he did not envisage that theidea would eventually lead to the discovery of quarks. Many minds contributed their ideas and expertise to thisenterprise. So, who discovered the quarks? If we use the notion of discovery in a narrow sense, the answer wouldbe: Gell-Mann and Zweig. But if we take into account the whole process, Heisenberg made a decisive step in thediscovery process. (When I say that quarks were discovered, I do not mean, of course, that quarks have beenobserved. Rather I mean that a successful theory in which quarks appear as theoretical entities was discovered.)

8.3.2 The Resources of Quantum Field Theory

The use made of quantum field theory by particle physicists in the 1950s and the 1960s is an architypical exampl

of tinkering. Particle physicists inherited QED from the 1920s and the 1930s, when it was successfully applied tomany phenomena in atomic physics. However, the theory suffered from a severe dif-







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ficulty. It was impossible to calculate certain integrals corresponding to experimentally measurable quantities. Thsecond order perturbative corrections of these quantities yielded infinite integrals. The problem was solved by atypical tinkerer's stratagem which turned out to be successful. This was the "renormalization" procedure of absorbing the infinities into physical constants. The trick gave the correct result in calculating the Lamb Shift, wia very high degree of accuracy. The physicists did not have full understanding of the physical meaning behind th

procedure. But the theorists were satisfied, since this technique enabled them to calculate measurable quantities.Following the success of the renormalization technique developed by Tomonaga, Schwinger and Feynman in thelate 1940s, QED became a very powerful tool for calculating measurable quantities of electromagnetic interactionVia this process, the meaning of the term theory was shifted. Traditionally, one of the main functions of a physictheory had been to provide a description or an explanation. With this shift of meaning, a theory was concievedmainly as providing a tool for calculations. Elementary particle physicists in the early Forties, therefore, tried toexploit QED for calculating the quantitative properties of weak and strong interactions. I will not dwell here on thapplication of quantum field theory to weak interactions. I will mention only that already in 1934 Enrico Fermiconstructed a quantum field theory for the weak interactions in beta-decay. He modeled his theory on QED, butone of the difficulties was that the theory was non-renormalizable.

The first application of quantum field theory to strong interactions was proposed by Yukawa in 1935. Again, it wa

modeled upon QED. But it was a non-starter. Since the coupling constant of strong interactions is greater than onthe higher order terms in the perturbation expansion are increasingly greater than the first-order term. This led toinsurmountable difficulties in the calculations when the renormalization procedure was applied. Having no other alternative, physicists turned then to the S-matrix theory which was available since the mid-1940s. Being a "blacbox" theory, it treated only the transition probabilities of the input/output states. The S-matrix was treated as ananalytical function and the tools of the mathematical theory of complex-variables functions were exploitedextensively. Nevertheless, quantum field theory was still used as a guide in investigating the analytic properties othe S-matrix. Meanwhile, those who developed the "bootstraps" approach to the S-matrix abandoned field theoryaltogether.

A widespread tool, which was picked up from a work on non-relativistic potential scattering in the late 1950s andapplied to the S-matrix tradition, was Regge poles theory. Regge introduced the concept of complex angular

momentum, purely as a mathematical technique for solving his nonrelativistic problem. "Regge himself never backed the cavalier applications of his results (which had been proved only in norelativistic Schroedinger theory)to the relativistic problem" (Cushing, 131). Regge poles theory was a central research topic that







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engaged many particle physicists in the 1960s and the early 1970s. Since then, it has been totally abandoned. 10

8.3.3 Playing with Quarks

The idea that strongly interacting particles are composed of elementary constituents goes back to 1949. Accordingto the Fermi-Yang model (1949), the pion was not an elementary particle; it was a nucleon-antinucleon composit

The Sakata model, which extended this model to include strange particles, followed in 1956 (Sakata 1956). Thefundamental particles were the three Sakatons, i.e. the two nucleons and the "strange" baryonlambda. The rest of the baryons and all the mesons, including the strange ones, were Sakaton composites. With the advent of SU(3)symmetry, the Sakatons were replaced by the three quarks. The quarks corresponded to the fundamental group-theoretical representation of SU(3), the triplet, while the baryons and mesons occupied octets representations. Anearlier version of the model was suggested as a mere mathematical possibility in 1962 by Goldberg and Ne'eman(1963) and a more elaborate version was independently developed in 1964 by Gell-Mann (1964) and Zweig (1964who discussed the physical application of the model. The main difference between the Sakata model and the quarmodel was that in the former the nucleons and the lambda were not composite particles, whereas in the latter all observed hadrons were composed of quarks. At this point quarks have gradually become independent of their group-theoretical origin. Thus, the quark model followed in the footsteps of the S-matrix theory and currentalgebra which became semi-independent of their field theoretical origin.

The main difficulty in this model was that a free quark had never been detected. Nevertheless, this non-realisticmodel yielded very good results and the quark-game continued. It was an effective tool for classifying hadrons anfor calculating their dynamic properties. Particle physicists employed the composite system model because it wasfamiliar to them from nuclear physics and it served as a good tool for calculations.

8.3.4 Tool-Oriented Particle Physicists

In particle physics we very frequently encounter the phenomenon of tool-oriented scientists. I will describe severacases taken from Pickering (1984) which can be viewed according to the tinkerer's principle.

Dalitz

Richard Dalitz was trained in nuclear physics and specialized in the analysis of composite systems. In the late1950s he moved into elementary particle physics and dealt with strange hadronic resonances. He borrowed the toof spectroscopic analysis from atomic and nuclear physics and employed it in dealing with quark systems. Theobserved hadrons played the role of the energy levels of composite quark systems. Many theoreticians followedhim







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and since the mid-1960s the quark model was developed with the tools of nuclear physics (ibid., 9697).

Ting

Experimental high-energy physicists are prone to be tool-oriented since their equipment is so expensive and sincthey invest many efforts to gain expertise in using it. Samuel Ting had a lot of experience in the detection of

electron-positron pairs following a series of experiments he had conducted since 1965 at DESY in Hamburg. Atfirst he was mainly engaged in the production of e+e- pairs for testing QED. Then he turned to investigating theproperties of neutral vector meson by detecting e+e- pairs. In the early 1970s he was looking for a new subjectwhere he could use his expertise. He decided to look for vector mesons at higher energies. In 1974 his groupconducted an experiment at the Alternating Gradient Synchrotron in Brookhaven, bombarding a beryllium target a proton beam. They scanned the energy region from 2.4 to 4 Gev, counting e+e- events. Around 3.1 Gev they saa strong and exceptionally narrow peak. They interpreted the results as the decay products of a new vector mesonThis was the discovery of the J-psi particle (discovered simultaneously by Burton Richter's groupin a collidingbeams experiment, where hadrons were produced from electron-positron collisions, at Stanford)a turning point inthe history of particle physics.

Yang-Mills Theory

The history of Yang-Mills gauge theory provides us with instructive examples of the phenomena of tool borrowinand tinkering. It also demonstrates the cooperative nature of theory-construction.

The gauge field theory which was first proposed by Yang and Mills (1954), was modeled on QED. The twophysicists intended to extend QED beyond electromagnetic interactions. C. N. Yang started the process byemploying his knowledge in group theory, which he had acquired in his undergraduate studies. His BSc thesis waentitled: "Group Theory and Molecular Spectra" (Pickering, 161). Thus he was one of the first physicists whointroduced the group-theoretical tradition in particle physics. He applied the QED formalism to strong interactionHe replaced the electron field in the QED Lagrangian by the nucleon field, for example, which belonged to anisospin doublet. The local gauge transformations which kept the QED Lagrangian invariant, generated the groupU(1). With the nucleon field, he aimed at constructing a Lagrangian which would be invariant under the isospinsymmetry group SU(2). However, in order to keep the Lagrangian invariant under the SU(2) group, he had tointroduce, instead of the photon, an isospin triplet (W+, W0, W-) with spin 1, as the quanta of the field. Thedifference between these particles and the photon was that they carried an electric charge and this led to theappearance of self interaction terms in the Lagrangian, in addition to the terms describing the propagation of freeWs in space.

Since 1954, when the theory was proposed, many authors made contributions to it. Among them were Sakurai,Gell-Mann, Schwinger, Glashow and







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Salam. They were mainly engaged with the masses of the vector particles. Since the photon is massless, theoriginal QED Lagrangian contained no mass terms for the photon. But the Yang-Mills theory was intended to treastrong and weak interactions which are short-range. In particular, the possibility of identifying the Ws as themediators of weak interactions was attractive, since this may have led to the unification of the electromagnetic anthe weak interactions. For example, the W+ and W- and the photon may belong to the same family. But the

electromagnetic force is much stronger than the weak force and the photon is massless, whereas the mediators of weak interactions are massive. So the idea to put them in one family raised difficulties.

In 1961 Glashow suggested, therefore, that the gauge symmetry would be SU(2)xU(1) so that the photon may besingled out. Salam and Ward made a similar suggestion. In these theories, the masses of the intermediate vector bosons were not derived from the theory but were inserted in the Lagrangian in an ad hoc manner. But this causethe theory to be non-renormalizable. A solution to this problem was found by the model of spontaneous symmetrybreaking, where the intermediate vector bosons acquired mass, whereas no mass terms for the Ws appeared in theLagrangian. This model had been introduced by Nambu and Jona-Lasinio in 1961, in another context.

Yoichiro Nambu had specialized in the application of quantum field theory to many-body phenomena in both solstate physics and particle physicstwo relatively disconnected specialities. In the late 1950s he worked on thephenomenon of superconductivity which was then a subject of central interest. He continued to work also in

particle physics. He applied his expertise in solid state physics to construct "A Dynamical Model of ElementaryParticles Based Upon an Analogy with Superconductivity" (Nambu and Jona-Lasinio 1961). According to thismodel the Lagrangian which describes a physical system may be invariant under a symmetry group which is"spontaneously broken" by the physical states of the theory. Originally, in the early 1960s, the model wasemployed to account for the symmetry breaking of SU(3). Since then, the resources of solid state physics havecontinued to fertilize particle physics.

Jeffrey Goldstone, who also was an expert in the theory of superconductivity, argued that spontaneous symmetry-breaking implies the existence of massless, spin-zero particlesGoldstone bosons. Salam and Weinberg joined himin this conclusion in 1962. Yet, as another solid-state physicist, P. A. Anderson, argued, massless particles do notappear in superconductors. This problem led to further developments of the theory, to the Higgs mechanism andfinally, to the Weinberg-Salam model which did not differ much from Glashow's model.

Yet, one obstacle remained in the way of the construction of a unified electroweak gauge theory: the problem of renormalizability, which Yang and Mills had failed to solve. The renormalization procedure would bridge the gapbetween the theory and the calculation of measurable quantities.







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Two figures played a decisive role in solving the problem. The graduate student 't Hooft who solved the problemand Veltmanhis supervisorwho brought the problem in its final form to his student's attention. Now we come to thmost crucial step in the process: Veltman and 't Hooft's contributions to the development of Yang-Mills theory. Iwill describe their contributions in some more detail, since they were typical of the whole process of discoveringthe unified elecroweak model and since they demonstrate our thesis. I shall follow here mainly Pickering's

description, and all citations will be from there (ibid., 174178).The story begins as Martin Veltman tried to understand current-algebra, using the techniques developed in his Phwork on Lagrangian field theory. He looked for a subject which could be treated by the techniques and methods hhad acquired. He attempted to derive current-algebra results from manipulation of quantum fields. This was GellMann's strategy in a reverse order. Gell-Mann constructed current-algebra with the heuristic guidance of gaugefield theory and then discarded the gauge theory and treated the resulting current-algebra independently of itsorigin.

In 1966 Veltman found that some of the current-algebra results could be derived from two field-theoretical curreequations. Richard Feynman told Veltman that the equations' structure was characteristic of Yang-Mills theory. Bhe argued that it was related to strong interaction rather than to weak interaction. By this he followed the SakuraiGell-Mann and Ne'eman's approach to gauge theory, which was the mainstream approach at that time.

Later, Veltman's collaborator John Bell became interested in Veltman's equations and in 1967 he published a pap"arguing that what was needed was a Yang-Mills structure for the weak interactions. Veltman later recalls thatBell's paper on the subject 'became a great mystery for me for a while. It kept on going in my mind. ... If finallydawned upon me that the current equations were a consequence of a Yang-Mills type structure of the weak interaction'." Here we have an event which has all the ingredients of an eureka moment.

Veltman then went on "to investigating the renormalizability of gauge theory, drawing further upon the resourceshe had acquired in his thesis work." His interest was in massive Yang-Mills theory, where the masses wereinserted "by hand," since the massless gauge invariant theory was unrealistic. The received opinion was thatmassive theories were non-renormalizable. He found that the obstacle to the renormalizability of the theory werecertain higher-order calculations in perturbative field theory which involved self-interacting intermediate massive

vector bosons. Technically speaking, these were the calculations which corresponded to Feynman diagramscontaining two loops.

On the other hand, he had learned that massless gauge theories similar to his massive theory had been showed tobe renormalizable. At this stage he began to investigate the possibility that perhaps appropriate scalar (spin-zero)







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fields could be introduced into the massive Yang-Mills Lagrangian in such a way as to cancel the two-loopdivergences due to the the self-interacting vector bosons. This was the stage where Veltman's student, Gerald 'tHooft, entered the scene.

In 1969, at the suggestion of Veltman, 't Hooft studied the renormalizability of the "sigma-model." This was "asimple Lagrangian field theory used in heuristic current-algebra calculations. It was not a gauge theory, but itdisplayed spontaneous symmetry breaking. ..." When he was going to start working for his PhD under Veltman'ssupervision, he proposed to work on gauge theory. "Veltman agreed, although he felt that it 'was so much out of line with the rest of the world that very likely one was producing specialists in a subject that nobody was interestin'" and he suggested that 't Hooft work on the renormalization of massless gauge theory, since some problems stremained even there.

't Hooft published a paper where he presented the first detailed argument that massless theory was renormalizableThen Veltman asked him whether he could devise a renormalizable theory with massive vector bosons. Hisimmediate answer was positive, since he had the appropriate tool for carrying out the taskthe sigma-model. In apaper published in 1971 ('t Hooft 1971) "'t Hooft used the technique of spontaneous symmetry breaking, familiarhim from his earlier work on the sigma-model, to give masses to the vector bosons of the pure gauge theory. Byadding multiplets of scalar particles into the massless Yang-Mills Lagrangians. ..." With this result he found that

gauge theories, in which vector bosons acquired mass by spontaneous symmetry breaking, were renormalizable.This was the breakthrough which brought the Yang-Mills gauge theory into the focal attention of particle physiciand which paved the way to electroweak unification.

The last episode demonstrates the role played by professional marginality in the process of innovation. Pickeringquotes Ne'eman:

"Current opinion" rejected quantum field theory regarding it as hopelessly wrong. ... Hence the quantizationof Yang-Mills dynamics was finally achieved by workers who happened to be immune to that consensus'view. It required geographical remoteness (Fadeev-Poppov, Veltman-'t Hooft [in the USSR and Utrecht,respectively]), professional remoteness (De Witt, working in gravitation theory). ... (Ne'eman 1983, 2, note2)

After quoting the above citation, Pickering adds that Veltman was both geographically isolated from themainstream of particle physics at Utrecht and "professionally remotehis route to entanglement with gauge theoryand the resources he brought to bear were unique and distinctive" (note 60, 199200). Thus he could contributenovel variations to the pool of ideas, methods and







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techniques. This supports the thesis that intellectual marginality is one of the sources of novelty in the scientificcommunity.

Intellectual marginality as a source of innovation corresponds to the evolutionary phenomenon in which genes wilow frequency are activated by new environmental conditions, or pressures, and spread through the population.Mayr (1959) describes the following mechanism for the evolution of a new species, which demonstrates thecontribution of marginality to the generation of novelty. Speciation occurs according to this theory as a result of the separation of a "peripheral isolate" from the original population. A new species may arise from a smallpopulation cut off in a remote corner at the edge of the range occupied by the "parent" species. The conditions inthe isolated niche, which differ from those prevailing at the center of the range, together with the small size of theisolated population, may bring about the evolution of radically new characteristics on the basis of the existing genpool. The new species formed in this manner may return to the area occupied by the parent species, be better adapted and displace the parent species. The case of 't Hooft demonstrates this phenomenon. The new species inthis case can be identified with the gauge theories and unified field theories which were brought to the forefront particle physics following the success of electroweak unification.

<><><><><><><><><><><><>

To summarize, the history of the Yang-Mills gauge theory exhibits the following characteristics.

1.The theory was gradually evolved. New variations accumulated in an evolutionary manner.2.Most of the novelties were introduced by tool-oriented scientists: the theory's inception was inspired by the tools of group theory brought from the field of molecular spectra. Then, ideas and methodsdrawn from the resources of solid state physics were injected into the research program.

3.Marginal scientists who were "immune to the consensus" employed their tools.4.The process was cooperative, wherein many minds participated. The decisive step was done on soil prepared by all participants. The discovery was a product of the contributions of numerous scientists.

5.The breakthrough was achieved by a scientist who set out to solve a very specialized problem, whichturned out to be a crucial problem. 't Hooft was just a "cog in the wheel." He appeared on stage at theright moment and "put his stone into place," to use Hegel's metaphor. He was fortunate to get theright question from Veltman. Although he had specialized in







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using a marginal tool, it turned out to be the right tool for solving the crucial problem.6.The process was not preplanned. Veltman did not expect the research to result in a breakthrough. He

agreed somewhat reluctantly to his student's proposal, thinking that no one would be interested in thatsubject. This also reminds us of Rutherford, who gave young Marsden an ''exercise" for practicing hisskill, while he did not believe that any significant result would be obtained.

According to the tinkerer's principle, scientific products are generated by situational contingencies. Knorr-Cetinadescribes the tinkerer's principle as it emerges from "laboratory studies." And the conclusion is that "similar problems tackled by different people in different environments will yield different solutions" (Chubin and Restiv1983, 70). The impression is made that "anything goes" in the scientific laboratory. But the point is that tinkering,in theoretical as well as in experimental science, is a mechanism for generating variations. Eventually, certainvariations, presumably the "fittest," will be selected, or accepted by a given community. And in normal science,different laboratory sites in the same research area have similar resources. Therefore, similar situationalcontingencies are encountered in different laboratories, and the range of variations is restricted. Furthermore, the"environmental" conditions and the standards of selection are also similar. The same happens in theoretical sciencScientists in different places have at their disposal more or less the same repertoire of models, methods and

theories, which are characteristic of their research tradition. And the standards or mechanisms of selection aresimilar. Therefore tinkering will generate radical novelties only in an open system, where scientists can draw upomarginal or external resources. Thus, marginality, migration and other sources of cross-fertilization are among thfactors contributing to the generation of radical novelty. Historical contingency might therefore be exhibited at thtime of radical scientific change. The present world picture of physics, for instance, reflects the historicalcontingencies which were incorporated by the scientific revolutions of the seventeenth and twentieth century.Contemporary physics is a very successful science, but the present theories of physics are by no means "perfect."The same can be said about the living world; no species is perfect, included Homo sapiens. This is a directconclusion of the tinkerer's view of science and natural selection.

The progress of science is not attained by erecting monumental systems of thought. Only in rare cases are theproducts of science cathedrals planned by an ingenious architect. Rather, scientific creation is in many cases the

work of a tinkerer. Jacob intended this principle to be applied to natural selection. He did not envisage that themodel of natural selection might be applied to







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science. The conclusion which he perhaps did not intend to reach is that the same principle governs savage thoughand scientific thought. And yet, this very conclusion is a product of tinkering; the principle of tinkering wasborrowed by Jacob from the context of savage thought and was transferred to the context of biological evolution(this creative transfer was perhaps the result of the following situational contingency: Levi-Strauss wrote French,making his work more accessible to Jacob, the Frenchman), whereas here it is borrowed from the latter context an

transferred to the context of science.







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Chapter 9Completing The Picture: Is There A Role For The Genotype-Phenotype Process?

Two kinds of novelties are exhibited by organic evolution. The first kind is the new variation (mutation or recombination) which is selected by the environment. Blind or serendipitous discoveries in science correspond tothis kind of novelty. The second is the grown up organism. The more complex is the organism and the moreversatile is the environment, the larger is the novelty which may be embodied in the mature organism. The procesof ontogeny, i.e. the growth of the organism after conception, yields a grown up "product" which has somephysical characteristics which depend on both the environmental conditions under which the process took placeand on the genotype's constitution. The phenotypic variability in our species is much larger than in other species,since in addition to the physical variability there is also a personal and mental variability. Correspondingly, theenvironment includes the sociocultural environment in addition to the physical and organic environment. Thegrown-up human being constitutes a novelty, in particular in personality and intellectual capacities. Personal andintellectual novelty depends much on the sociocultural environment.

Ontogeny happens to be the most concrete manifestation of the life phenomenon. The following question therefo

arises: is there a counterpart of ontogeny in an evolutionary theory of discovery? The mainstream program of evolutionary epistemology models the evolution of science on phylogeny and leaves ontogeny without an analoguI will try, therefore, to exploit this neutral analogy in our evolutionary model, which has remained untouched, andto convert it into a positive analogy (Kantorovich 1989).

On the other hand, there is a fundamental scientific process that is left in our model without a biologicalcounterpart. This process turns out to be the commonest mode of scientific research in "normal" science, i.e. theprocess of developing a newly generated idea or model. In this process we







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exploit the potential inherent in an embryonic idea, while being engaged in problem solving. Here logic, in thewide sense, enters into the game of science. This process is what we have called "research program" or "dynamictheory." It seems natural, therefore, to consider the possibility of modeling the research program on ontogeny.

Phylogeny emerges from the totality of all ontogenies. Hence, understanding ontogeny is essential for comprehending and explaining phylogeny. Similarly, the evolution of science is the sum total of scientific researcprograms; the scientist, qua-scientist, is only engaged in research programs. Hence it is essential for theevolutionary epistemologist to study the mechanism by which a research program develops. Organisms surviveenvironmental pressures, and before they die they grow and change. Living theories, likewise, have a finitelifetime; before being replaced they develop and undergo modification. We will see that in addition to theseparallelisms, the two processes, the growing organism and the developing theory, have structural similarities. Thiwould strengthen the conjecture that the counterpart of ontogeny is a research program. Thus, I will propose toextend the evolutionary model for science such that it will do justice to the life history of an idea or a theory. I wiargue that the latter can be treated analogously to ontogeny, and that in science the "logic" of ontogeny iscomplementary to the "logic" of selection.

9.1 Non-Creative Discovery: The Genotype-Phenotype Logic of Growth

As we have seen, there is an epistemological significance not only to the death of a theory, i.e. to its refutation orreplacement, but also to its growth and life history. The discovery of the idea or model which initiates the researcprogram is the most creative phase of the process. It is a product of blind variation exhibited in our approach byserendipity, tinkering and involuntary processes. The continuation of the process whereby the initial idea "endswith algebra" is no less important; it consolidates the product of the creative process, exhausts its potentialities anmakes it susceptible to evaluation. It is carried out as a process of exposure, guided by some kind of logic.

The analogy between the growth of a dynamic theory and the growth of an organism can be demonstrated asfollows. First, both a research program, and an organism are engaged in problem-solving. A research programsolves, for instance, problems arising from the need for adjusting its basic ideas (which constitute the "hard core"in the Lakatosian terminology) to new observational data. Similarly, an organism adapts to new environmentalconditions on the basis of its genetic makeup. The metaphor of an organism as a problem-solver is employed, for

example, by Karl Popper.







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Secondly, there is a structural similarity between the growth processes in both cases. The growth of a dynamictheory in a research program resembles ontogeny, where the action of the environment transforms the genotypeinformation from potentiality to actuality in the form of a growing phenotype or organism, including behavior andlearning. I suggest, therefore, to consider the following analogy: the basic ideas of the dynamic theory areanalogous to the genotype, whereas the explicit theory develops as the phenotype . The analogy implies the

following main points:

1.The basic ideas are determined with the initiation of the research program, as the genetic informationof an organism is fixed at conception.

2.The basic ideas of the model can be seen as providing a program or a blueprint for developing theexplicit theory, as the genetic information represents a blueprint for the development of the organism.

3.The environment within which a research program evolves is comprised of observational data andother developing research programs. This is analogous to the fact that the environment for anorganism is comprised of other organisms, as well as the non-organic environment.

4.The "central dogma" of molecular genetics says that information flows in the cell only in onedirection: from the DNA molecules to the RNA molecules, which direct protein synthesis onribosomes. The process cannot be reversed; phenotypic modifications that are brought about by theinteraction between organism and environment cannot influence the hereditary information encodedin the DNA. Similarly, the relation between basic ideas and theory is unidirectional; the basic ideasdirect theory construction, but are never modified as a result of theory-observation interaction, i.e. bythe attempts to adjust the theory to the data.

5.The decoded genetic information can guide cell development only if the appropriate environmentalinputs are provided. Similarly, the basic ideas can be decoded, that is expressed explicitly in the formof instructions for constructing the theory, only if the appropriate experiments are made and theappropriate observational data are provided. The basic ideas of a research program are by themselvesdevoid of empirical content in the Popperian sense, since they are not falsifiable. They are notfalsifiable since they do not entail possible observations that may refute them, and sometimes they arenot explicitly formulated. This is the reason why they can be kept untouched. The empirical contentis built up as the research program progresses. For example, as we have seen, in the Bohr-atomresearch program some of the model's elements were left without clear specification at the beginning.The initial version of the model left open, for example, the implications for atomic structure of thefinite size of the rotating electron-planet, such as its degree of freedom of rotation around its axis.The open points constitute the neutral analogy of the model. Only the attempts to explicate andformulate the basic ideas and to utilize unambiguously the neutral analogy give these ideas empiricalcontent.







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should attempt to construct a theory of science that will give appropriate weights to the influence of the basic ideas inherited by the research program, as well as to the external data, in constructing ascientific theory. As an organism cannot begin life without genetic information, so also a research program cannot start without basic or "innate" ideas. As an organism cannot grow without input fromthe environment, so a dynamic theory cannot grow without interacting with observational data andother external information. The manner in which the genetic information is expressed in the growingorganism depends on the organism's diet and exposure to environmental pressures. Similarly, themanner in which the basic ideas are expressed in the developing theory is influenced by the exposureto experiments and to inputs from other research programs. Thus, theory building is not blind to thedata; the same master plan or blueprint will yield different theoretical constructions when different"environmental" inputs are provided, although they will have some basic characteristics in common.

6.The category difference between the genotype and the phenotype is reflected in the parallel categorydifference between the "metaphor" and the "algebra," the basic idea and the formulated theory, theimplicit picture and the explicit theory. On the one side of the relation stands a potential entity, aninnate design, which materializes into an actual entity; a visible or explicit construction stands on theother side of the relation. Furthermore, in biology the genotype is a "theoretical" entity, whereas the phenotype is "observational." A similar distinction may be made in the framework of a naturalistictheory of science. The most direct and unambiguous data available for the theorist of science are theexplicit scientific claims and the manifest behavior of the scientists, whereas their tacit assumptions,transparent rules of inference and the basic ideas that guide them can mainly be inferred or theorized.Hence, for the theorist of science these background models, tacit ideas or material rules of inferenceare "theoretical'' entities, whereas an explicit theory-version or a statement is directly "observable."

7.From the evolutionary point of view, the difference between the genotype and the phenotype is thatnatural selection operates directly only on the latter. Selection in science operates in a similar way:only explicit theory-statements can clash with observational data and be selected by the scientificcommunity, whereas basic ideas of a research program cannot, since they are not linguistic entitiesand are not fully communicable. The question of what the unit of selection is, whether it is an idea, a(dynamic) theory, or perhaps an entire world picture or "paradigm" has a direct counterpart in biology. The parallel question in biology pertains to "the level (or levels) at which selection can take place" (Hull 1981, 23). In our model we adopt the view that parallels the current majority view in biology: "that genes mutate, organisms are selected, and species evolve" (ibid.). A basic idea isanalogous to a gene, and a theory is analogous to an organism. Our unit of direct selection is thetheory, whereas







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basic ideas are indirectly selected through the selection of entire theories, just as genes are selectedindirectly through the selection of entire organisms.

8.We still have to determine what in our model constitutes the analogue to the species. It is natural tochoose the population of research programs that evolve within a given paradigm or world picture asthe analogue of a species. If we take the definition of a species to be a set of individuals that caninterbreed, then we can see that the analogy will work if indeed only research programs within one paradigm or tradition can communicate and contribute ideas to produce new research programs. Thisreminds us of the incommensurability thesis: research programs from different paradigms cannotintercommunicate. The species can also be characterized by its genotype (the genotype of the species)or by its gene-pool. Similarly, a population of intercommunicating research programs is characterized by their common world picture, or by its repertoire of ideas ("idea pool"). A research program thatsurvives and succeeds in "mating" with other ones contributes some of its basic ideas to itssuccessors so that these ideas disseminate in the normal science and will appear in high percentage inthe repertoire of ideas of the paradigm. At any given time, the world picture in normal science is a product of natural selection in antecedent generations of research programs. The information stored inthe world picture reflects the long phylogenetic history during which environmental pressures produced and selected the currently selected ideas ("genes").

In other words, only via selection operating on dynamic theories can information about the world be transmitted tthe repertoire of ideas of the paradigm, i.e. to the world picture. Thus, according to this model, there is no way topass on to the common world picture the information that has been acquired in the course of the development of the theory. Hence, our model would predict, for example, that the information included in the advanced versions oBohr's theory will not be transmitted to the hard core of successive research programs. This seems to be a seriousshortcoming of the model. Although we do not expect the idea-pool to include explicit theoretical developments othe model, it should include new significant ideas, such as spin, which were developed in a successful researchprogram. I shall give three arguments for answering this question.

The first one is the following. The G-P model has descended from the Popperian model, which claims that nothin

can be learned positively in science; the only thing we can learn from experience is that a theory was refuted. ThG-P model constitutes in this respect a considerable advance over falsificationism without being inductive: itimplies that our repertoire of ideas gains positive knowledge by increasing the relative weights of basic ideas whichave guided successful research programs. This pool of ideas serves as a source of basic ideas for subsequentresearch programs. However, this is only a slight consolation. Let us turn, then, to a stronger argument.







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example, an undesired negative analogy of the basic model which guides the development of the program. The idis then disseminated throughout the entire population of research programs belonging to the same "paradigm."

9.2 The Selection Cycle in Science

We can summarize the picture outlined above by a cybernetic model of the selection process offered by C. J.Bajema (1971, 2). The model describes how the information flows from the organism-environment interaction tothe gene pool and back. The organism (the phenotype) is produced via genotype-environment interaction in theontogenetic process. The organism in its turn adapts to (interacts with) the changing environment. Subsequently,the process of differential reproduction affects the content of the gene pool. The gene pool undergoes further variations via mutations and recombinations. This affects the genetic makeup of the organisms in the nextgenerations, and so on. There are two sources of change in this cycle: changes in the environment and variationinput to the gene pool.

We can translate the above biological feedback cycle into its counterpart in the evolution of science. The diagrambelow describes the corresponding information cycle in science.

It must be noted that there is some overlap between the G-P process (theory-construction) and the theory-data

interaction. The latter refers, however, mainly to a mature stage in the development of the theory. The sources of novelty in the evolution of science are two: discovery of new observational data and generation of new ideas. Bosources are necessary for the process to go on. Radically new observational data could not be accommodated, i.e.explained, without generation of novel ideas. New ideas could not become assimilated into the world picturewithout being confirmed by some new data (or without being selected by the new data).







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<><><><><><><><><><><><>

Finally, I would like to make the following remark. There have been some attempts to identify the G-P process inscience with the intellectual development of the individual scientist. However, according to our approach, science

is viewed as the continuation of the evolutionary process on the sociocultural level, extending our collectivecognitive apparatus and sensorimotor organs. Hence, ontogeny on this level does not coincide with the individualscientist ontogeny. The unit of selection according to our theory is a theory or maybe an idea; an individualscientist does not die with his ideas or theories. In our model it is thus a mistake to look for the G-P process in thintellectual development of the individual scientist.

Peter Munz demonstrates the similar roles played by an organism and a theory in the following way. He argues thsince an organism is equipped with a cognitive structure it can be viewed as "an embodied theory about itsenvironment" (Munz 1989, 241). "It takes signals or stimuli from the environment and immediately interprets or decodes them in terms of its structure and then responds. This is exactly what happens when we test a theory."Thus human beings " propose laws to nature" (rather than prescribe laws to nature, in the Kantian fashion).However, this argument leads to another conclusion. The laws that we propose to nature are determined by our

cognitive apparatus which develops in an ontogenetic process (as was described, for example, by Piaget).Therefore, when we say that we are theories, the latter should be understood as dynamic theories. On the other hand, Munz claims that ''consciously proposed hypotheses can be regarded as disembodied organisms" (ibid., 243Thus in science we "continue and extend the process of evolution in our minds" by generating and selectingtheories. We therefore arrive at the unavoidable conclusion that the disembodied organisms which we create andpropose to nature are dynamic entities.

In summary, the basic G-P formula is not a rule or a method of discovery. Rather it describes a general kind of process, which may have psychological and social dimensions and which may be cultivated by supplying to it theappropriate environmental conditions. The main lesson for cultivating discovery which can be drawn from thismodel is that a proposed idea or theory cannot be treated as a discovery in isolation from its environment, wherethe environment includes, in addition to the data, metaphysical, technological and social dimensions. A theory or

an idea may develop into a great discovery in a given context but not in another. As we have observed, thequestion whether a given idea or theory is a discovery is context-dependent. In the same way, the question whethan idea will develop into a discovery is also context-dependent. Thus, in assessing the prospects of a proposedidea, we cannot be satisfied with examining only the idea itself; we have to examine also the environment: what the state of knowledge, the experimental techniques available, and the climate of opinion within the scientificcommunity.







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In the above scheme I have exploited the evolutionary model in some more detail then it is customary to do in thepractice of evolutionary epistemology. Of course, there is a limit to the possibility of exploiting the neutral analogof a model. A scientific theory is not a living creature in the physical world, nor is normal science a population osuch creatures. Nevertheless, I have proposed the model since there seems to be a high degree of structuralsimilarity between the growth of a theory and ontogeny. True, there is also some negative analogy in the model,

that the balance between the negative and the positive analogy will determine the fate of the model.







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Conclusion

In Chapters 5 through 9, I have proposed a naturalistic, or an explanatory, theory of science. According to thetheory, science advances via two intertwined creative processes which are manifestations of evolution throughnatural selection. These two processes feed one another with the raw material of variations. The intrapsychicprocess is fed by ideas created and selected in the interpsychic process, whereas the interpsychic process isnourished by ideas generated in intrapsychic processes. Novel ideas are injected into the system via tinkering. Ththe system remains open and proliferation of variations is ensured. The coupling of these two kinds of creativeprocesses form a system that can be viewed as the collective brain of the scientific community, which extendshumankind's cognitive capacities. The extended cognitive apparatus, therefore, magnifies creativity and theresulting creative process is very powerful and enables science to transcend the limits imposed on humanknowledge by the evolutionary heritage of our species. Modern science may, therefore, be viewed as a newevolutionary line on the sociocultural level, which emerged around the sixteenth to seventeenth centuries. From thperspective, science is viewed as a contingent phenomenon.

Arthur Fine (1986, 174175) considers the possibility that science is a contingent "historical entity ... like a

particular speciesthe horse for example." 11 He argues that as there is no "science of the horse," so there is noscience of science; there can be no science devoted to an individual (a historical entity). Yet, there is oneexception: the human species. Fine's claim would not apply to this contingent historical entity. More than onescience is devoted to the study of this species: for example, psychology, sociology, human biology, humanethology, anthropology, the medical sciences and economicsin shortthe human sciences. There is no reason why aleast one science will not be devoted to the study of science, which extends our natural capabilities and carries usbeyond our evolutionary "home-base.''12

The above theory of science has implications for the discoverer who participates in the process of science. Aninevitable consequence of the natural-selection model is that the creative steps in the evolution of science are theproducts of serendipity, opportunism and tinkering. These creative facul-







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ties are not method-governed, but they require a prepared mind. Furthermore, these notions imply that science hano goal. From the vantage point of the individual discoverer, there are two major involuntary or unintentionalnovelty-generating mechanisms in science. One is a creative process which the scientist hosts in his mind. Theother is the cooperative enterprise in which the scientist participates. In both cases the discoverer is a passiveobserver on the arena of creation.

Yet, there is an indispensable role for logic and method in scientific discovery. When a new conceptual tool or anew information channel with nature is created, logic enters into the game after the new channel is black-boxedand becomes transparent. At this stage, scientists try to expose new phenomena and new aspects of reality by usinthe new information channel. And they do this by using logic, in the broad sense, which serves as a tool for uncovering the information conveyed by the new channel. In this case the discovery is not generational or creativrather it is discovery by exposure. Logical rules, or material rules of inference, serve as tools of exposure. This issituation analogous to the uncovering of the information hidden in a set of statements by using deductive rules.This role of logic is no less important for discovery than the role played by involuntary processes and tinkering; thlatter create new ideas and logic consolidates them as discoveries. The general pattern of scientific progress is thaof creation followed by exposure and vice versa. A new idea or theory is created and then its potentialities areexposed. Novelty may arise from an unintentional deviation from a strict procedure. The intentional activity of thscientist takes place within research programs, where he is trying to solve problems and to convert his ideas intoexplicit formulations. Unintentional creative leaps may appear as by-products of this activity.







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when the teacher supplies him with a hint such as what law or theory to use in order to explain a givenphenomenon. A problem in physics may become an exercise with a unique answer if the teacher leaves only asmall missing gap between the premises and the conclusion. The child learns how to apply a well defined law to well defined situation. This is very far from treating the child as a "little scientist."

There are two contexts of science teaching. The first is the context of applied science, where problems can besolved in the above fashion, without entering into a "philosophy." The second context is that of learning a newconcept or law. In this context, the child should be taught that a scientific law or theory is not a final truth. And,further, that scientific concepts and theories are not derived from observation or experiments. Rather they areinvented or generated by scientists and then tested by experiment. Here, it might be helpful to give examples of unsuccessful theories, such as the theory of phlogiston, the caloric or Praut's theory, as well as of successfultheories which were replaced, such as classical mechanics.

In class we can hope to reconstruct some cases of discovery by exposure (discovery by observation, classificationcomputation and inference). We cannot reconstruct generational discovery, since different theories can beconstructed and there is no unique "right" answer; theories are underdetermined by the data. The standards of explanation change with the scientific paradigm or world-picture. Creativity in science is influenced bymetaphysical beliefs and cultural-technological background. The child's background differs from that prevailing a

the time of the real discovery.

A Lesson from the Social Dimension of Scientific Creativity

If we adopt the view that scientific discovery is a cooperative enterprise, we should not expect the child to achievwhat even individual scientists do not achieve. Most scientists do not make even a single discovery by themselvethroughout their lifetime. They participate in the process of discovery or they contribute to it. The only thing whiccan be done in order to simulate some facets of the discovery process in class is to try to set up working groupswhich will develop ideas, without expecting them to arrive at the "right" ideas, since those do not exist.

The above view seems to be confirmed by empirical research showing that the cognitive process of learningscientific concepts, such as the concept of velocity, is much more efficient when done as part of a small group

activity than when carried out individually through reading textbooks or through frontal teaching. The generalhypothesis is that internalization of unfamiliar concepts is more efficient as collective learning. This bears somesimilarity to what happens in science, when novel ideas are accepted only after being







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processed (and possibly modified) by the scientific community. Brainstorming (Osborn 1963) is the best availabltechnique for encouraging epistemic cooperation. According to this method, a discussion group is set up for solving a problem. Each participant in the group raises ideas, as "wild" as possible, without criticism or disturbanfrom the other members. The initial ideas are improved, and combinations of different ideas are generated, toproduce a collective solution. This stage is later supplemented by a mutual criticism.

A Lesson from Serendipity and Tinkering

Perhaps most major creative discoveries were made unintentionally: when the discoverer solved problem B whileaiming at solving a different problem A. We cannot expect the child to intentionally discover laws, theories,principles, etc. which were discovered in a serendipitous process. In class, the child is expected to solve problemin a routine fashion. However, one way to stimulate creativity is to ask the child to be alert to different problemswhich might be solved along the way in addition to, or instead of, the original problem. In order to encourage thikind of creativity, the teacher should not insist on solving the original problem. By this we can simulateserendipity. We can also encourage the child to try solving the original problem by using tools and methods whicwere devised for other purposes. This lesson is good for solving problems in any area, such as natural science,mathematics or in practical fields.

"Ontogeny Recapitulates Phylogeny"

The above slogan is well rehearsed by the students of science education. One of Jean Piaget's central claims in higenetic epistemology is that the intuitive views of the child mirror earlier stages in the history of science. There ia parallelism between the history of science and individual development (Piaget 1977). This view even led Kuhnto say that in order to understand dead scientists, he had to study living children. Some people go as far as to claithat they found Aristotelian physical thought in erring children. This view may sound plausible if we refer togenetically based scientific conceptions. If our intuitive conceptions are inborn, we have the potential for developing the same conceptions as our ancestors.

As long as we are dealing with teaching empirical knowledge and some basic laws of classical physics, thePiagetian view might be true. However, in view of the fact that modern science has carried us beyond our

evolutionary "home-base" and at the same time has become increasingly more cooperative, the Piagetianconception is inadequate in accounting for the evolution of sci-







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ence, in particular of twentieth-century physics. Hence, I would not agree with the following statement of NancyNersessian, which appeared in a recent collection on the impact of philosophy of science on science education:"there should be a single cognitive model for conceptual change in science and in learning science" (Nersessian1989, 178). For example, the conceptual change leading to the quantum revolution involved a long historicalcooperative and serendipitous process and tinkering. The process which started with Boltzmann and was continue

by Planck, Einstein, Rutherford, Bohr, Sommerfeld, Goudsmit and Uhlenbeck and then carried on by the collectivefforts of some of the greatest minds of twentieth-century physics cannot possibly be reconstructed by a singleinnocent child. This conceptual change was a social and cultural change rather than a cognitive change. It was socomplex, that even some of the major participants in the process, such as Planck and Einstein, could notcomprehend its results.

Skill, Mechanized Discovery and the Child

The above objections are similar to the objections I raised against mechanized discovery. The latter is inappropriafor replicating unintentional, involuntary or natural processes of scientific discovery. These include serendipitoussubconsious and collective processes and discoveries generated by discernment and by tacit faculties. What iscommon to the machine and the child is that both lack discerning power or tacit faculties which can only beacquired by apprenticeship and by active participation in scientific research. One of the shortcomings of computetechnology is that it cannot replicate the social dynamics of science. The social dimension of science cannot beincorporated into science teaching too. The small group activity mentioned above cannot, of course, replicate theintricate social dynamics of science, since this relies on institutions and social patterns which cannot beimplemented in the classroom. The classroom is not a miniature scientific community and the child is not a littlescientist. Hence, the most important kinds of scientific discovery cannot be replicated either by the computer or bthe child.







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Notes

1. EE has gained much interest in recent years. The bibliography in Donald Campbell's original paper (1974b)included nearly 100 references. The bibliography since then has exploded and its later version (Cziko andCampbell 1990) consists of nearly 1200 references (during the years 19871990, it was doubled).

2. I would like to make a methodological remark with respect to the notion of explication. This notion has beenextensively used in traditional analytic philosophy. For example, the notions of probability and confirmation werexplicated in the logical empiricist tradition by Rudolf Carnap (1950) or Mary Hesse (1974). According to thisconception, we start from an intuitive notion which we believe to be shared by most language speakers with whowe feel we can communicate. And then we look for a clear definition of the concepts (or embed the concepts in aformal sytem) which will capture at least some of these intuitions. We do not have to conduct field study in ordeto find out with whom we share these intuitions. We rely on our experience as language speakers. It may turn outthat the community with which we share these intuitions is narrow. But it should consist at least of the relevantprofessional community we belong to. And since we are not isolated from the rest of society, these intuitionsprobably reflect the intuitions shared by some of the general population. Empirical studies must be conducted onl

if we want to study the usage of a term in culturally remote societies with whom we have no communication.

The above procedure applies to concepts which appear in ordinary discourse. If one tries to explicate ametascientific notion such as the notion of discovery as it is used by scientists, then it depends on who ismaking the explication. A historian of science, or a philosopher of science, who is not an active scientist, or has never belonged to the scientific community, should interview scientists or study the history of science inorder to find out about the scientists' intuitions. Someone who is an active scientist may use the above procedure of explication, since he has had experience in communicating with other scientists. But this is truefor his specific scientific community. The notion may be used differently in other scientific communities. Theis no reason to assume that all metascientific terms are used in the same way by biologists and physicists, for example, or even by particle physicists and astrophysicists.

In analyzing the notion of discovery in ordinary discourse, I will rely on dictionary definitions, on the writingof other philosophers of science, as well as on my own intuitions. Since the metascientific notions have evolvfrom ordinary discourse, this might help us in understanding the metascientific usages of the term.







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3. I borrow this term from David Gooding, Thomas Nickles and Simon Schaffer (Gooding et al. 1989). Theseauthors employ the term with respect to the practices of scientists in using their experimental tools.

4. The numbers within the brackets indicate the masses in Mev.

5. I follow here the description of Edward Neville da Costa Andrade, who worked under Rutherford at the

University of Manchester (Andrade 1964).

6. I do not commit myself to all the interpretations provided by Koestler in this book. I try to rely only onuncontroversial material.

7. Throughout this chapter, all page numbers appearing in quotations, without further specification, refer to thisbook.

8. For further details see I. B. Cohen 1981, 123133.

9. For further details see DeLair and Sarjeant (1975) and Desmond (1975).

10. For further details see Pickering (1984).

11. David Hull (1980) treats biological species as historical entities or as individuals. According to the version ofevolutionary epistemology expounded in this book, science is not "like a particular species." Rather, it is like anevolutionary line which splits into several branches. But an evolutionary line, according to Hull's interpretation,can also be viewed as a contingent historical entity, or as an individual.

12. I use here Nicholas Rescher's expression (1986).







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Index

A

Abduction, 66

Adams, J. C., 94

Adaptability, 200, 206, 216

vs. adaptation, 207-8

and evolutionary progress, 207

and rationality, 193

Adaptiveness, 204

Ampere, A. M., 97, 105

Ampliative inference, 4, 63, 65, 68, 70, 74, 135-6, 152

Amundsen, R., 150

Analogy, reasoning by, 73, 85-6

and tinkering, 227, 230-3

Analytical type, 179

Anderson, P. A., 237Andrade, E. N. da C., 260

Archimedes, 35, 113, 180

Aristotle, 13, 137, 156, 201

Artificial intelligence (AI), 31, 82, 209

and heuristic search, 30

Association(s), 174, 178-83

chance, 185

infraconscious, 178-9

network of, 182-3

Association-strengths (between mental elements), 178

Avogadro, C., 80

Ayala, F., 150

Ayer, A., 200



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B

BACON, 78-80

Bacon, F., 3, 97

Bajema, C. J., 250

Barnes, V. E., 105, 233

Bayesian theory, 54, 88-91, 104, 125, 132, 177

dynamic assumption of, 89-90

Becquerel, H., 81, 167

Belief, degree of, 90

Bell, J., 238

Berzelius, J. J., 192

Black, M., 84

Blackbody radiation, 29, 77, 163-4

Black-boxing, 93-5, 246, 254

Blind conjectures, 146

Blind variation, 3, 7, 42, 125, 146-57, 174, 184, 186, 218, 223, 243-4

social dimension of, 197-9

Bohm, D., 92, 194

Bohr, N., 194, 258

Bohr-Rutherford model, 26, 32, 83-5, 159

Boltzmann, L., 77, 163-4, 258

Born, M., 194

Boyle, R., 24, 39, 55, 124

Bradshaw, G., 78

Brahe, T., 161

Brainstorming, 257

Bronowski, J., 216

Brown, R., 168

Buchanan, B., 82

Buckley, W., 45

C

Campbell, D. T., 3, 145, 148, 150-1, 174-5, 259



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Cannon, W., 168

Carnap, R., 90, 122, 135, 259

Chance configuration model, 174-6, 178, 185







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Conservation laws, 43, 47, 80-1, 231-2

Constructivist epistemology, 45

Context of discovery vs. context of justification, 5, 53, 56, 97-101, 117, 135, 199, 218-9, 226

and description-prescription dichotomy, 99-100

Context of generation, 102, 106-10

Convergent thinking, 179

Cooperation in science, 160, 189-97, 210-1, 240, 254, 257

diachronic, 191, 215

epistemological significance of, 212-5

synchronic, 190-1, 215

Copernicus, N., 59, 162, 165, 213

Coulomb, C., 22, 24

Creation, processes of, 173-88

Creativity

artistic vs. scientific, 186-8

in discovering natural kinds, 70-1

in discovering a theory, 27

and heuristic-guided generation, 152

and non-conformism, 185, 196-7

and opportunism, 223-6, 228-9

vs. reasoning, 61-2

and serendipity, 148

social dimension of, 182, 197, 256

and tinkering, 223-6, 229

and unintentionality, 113

Crick, F., 228

Crookes, W., 15, 72

Cultivation

of the collective mind, 219-20

of creativity, 62, 184-5

of discovery, 3, 5-6, 114-5, 251

of serendipity, 168-71, 221



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of the unintentional, 113-15

Curie, M. and P., 81, 167

Cushing, J., 134, 234

Cuvier, G., 190

Cziko, G. A., 259

D

D'Alembert, J., 156

Dalitz, R., 235

Dalton, J., 80, 101

Darwin, C., 23, 36, 178, 181-2, 190

De Broglie, L., 194

Delair, J. B., 260

Delbruck, M., 228

Democritus, 101, 226

Descartes, R., 59, 63, 65, 69, 190, 194

Descartes' rules of discovery, 50-1

Desmond, A. J., 260







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Dewey, J., 45

Differential dissemination, 250

Differential reproduction, 249

Dirac, P. A. M., 158, 194

Discoverability, 98

Discovery

blind variation view of, 7, 148

cooperative-historical process of, 5, 52, 78, 113, 142, 183, 189, 197, 203, 219, 233, 256, 258

efficiency of the process of, 55-6

epistemological aspects of, 12-6, 18

as an evolutionary phenomenon, 6-8, 29

by exposure, 4, 29-32, 38, 40, 43-4, 47-9, 64-5, 71, 74, 79-80, 86, 94-5, 101-2, 113-4, 178, 244, 254, 256

by generation, 4, 29, 32-4, 35, 38, 39-43, 47-9, 64, 71, 74, 79-80, 86, 94-5, 101, 113, 114, 122, 178, 254-6

and growth of knowledge, 57

by inference, 4, 30-3, 49, 61-8, 97, 98, 246

vs. invention, 4, 36-9

involuntary process of, 5-6, 35, 102, 110, 113-5, 118, 122, 141-3, 178, 191, 194, 258

mathematical, 34, 55, 62-3

by mathematical calculation, 30

mechanized, 2, 4, 77-80, 115, 142-3, 258

multiple, 185-8

naturalized, 2, 115, 142

object of, 11, 32

by observation, 4, 29

ontological aspects of, 16, 18

and philosophy of science, 1-2

of a problem, 28

process of, 11, 16

product of, 11, 16-29, 32-3

scientific, 13



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by searching, 30, 86

serendipitous, 3, 7, 42, 155, 157, 180-2, 225, 243

as a skill, 5, 92-5, 113, 258

of a theory, as a dynamic process, 26, 32, 80-5

unintentional process of, 5-6, 35, 49, 50, 52, 100, 102, 113-5, 191, 257-8

Discovery-generating argument, 63

Disembodied organisms, 251

Dissemination, the social dimension of, 199

Divergent thinking, 179

D-J distinction, see context of discovery vs. cotext of justification

D-J-D distinction, 199

Dobzhanski, T., 150

Donovan, A., 105

Dormant genes, 165, 204

Dormant ideas, 249

Dubos, R. J., 228

Duhem-Quine thesis, 109, 198

Dynamicism, 106

E

Easton, S. M., 181-2, 190

Edwards, W., 90

Einstein, A., 7, 12, 148, 159, 165-6, 168, 173-4, 177, 189, 192, 196, 258

Electroweak unification, 12, 190, 237-40

Embodied theories, 251

Empedocles, 226

Empirical generalizations, 25, 28, 152

discovery of, 16, 21, 54, 66

vs. laws of nature, 21, 22

Empiricism, 218-20, 246

vs. rationalism, 218

Epicurus, 177

Epistemic cooperation, 3, 184, 189-97, 219, 257



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Epistemic profit, 69, 106, 157-8

Epistemologizing biology, 147

Epistemology

constructivist, 45, 47

evolutionary, see evolutionary epistemology

social, 7, 184, 189, 192, 212

naturalized, 133, 147

transactionalist, 45, 47







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Euler, L., 156

Eureka event, 5, 35-6, 101, 113, 177, 182, 238

Evidential support, 90

Evolutionary epistemology (EE), 2, 7, 77, 145-8, 199-200, 210, 243-4, 252, 259-60

Evolutionary line, 260

Evolutionary POR, 178, 193, 199, 215, 218-9

Evolutionism, 125, 142

Expectedness, degree of, 89

Experimentation, as generational discovery, 33

Expert systems, 4, 56-7, 92

Explanation

bootstraps kind of, 24

deductive-nomological, 28

discovery of, 49

non-circularity, 24

theoretical, 27-8, 88, 124, 130, 134, 138-9, 212-3

Explication

of basic ideas in a model, 245

of intuitions, 84, 88-90, 103-4, 122-3, 135, 137, 179, 259

Extended sensorimotor organs and brain, 202, 209-12, 225, 253

F

Falsificationism, 14, 83, 125, 248

Faraday, M., 166

Fermat, P., 190Fermi, E., 234

Feyerabend, P., 109, 156, 213

Feynman, R., 234, 238

Fine, A., 253

Finocchiaro, M., 105

Fleming, A., 15, 113, 154-5, 168-9



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Flores, F., 92

Focal vs. subsidiary awareness, 17, 94, 179

Fodor, J., 140

Freedom of research, 170-1

Fresnel, A., 173

Fuchsian functions, discovery of, 177

G

Galileo, G., 29, 41, 59, 105, 162, 187, 190

Galvani, L., 168

Gauss, K., 178

Geiger, H., 72-3, 222, 227

Gell-Mann, M., 192, 232-3, 235-6, 238

Gene pool, 150, 156, 216, 240, 248, 250

of human species, 204-5

vs. idea pool, 209, 247

Generationism, 98-101

Genetic epistemology, 257

Genius, 52, 174-5, 178, 184

Genotype, 150

Genotype-phenotype (GP) model, 8, 243-52

Giere, R., 45

Glashow, S. L., 236-7

Goals of science, 53, 118-22, 125, 143, 254

Goeranzorn, B., 93

Goldberg, H., 235

Goldstone, J., 237

Goodfield, J., 226

Gooding, D., 94, 260

Goodman, N., 120-3, 126, 135

Goudsmit, S., 258

Gradualism in the growth of knowledge, 156, 171, 180, 217, 225

Grosseteste, R., 58, 71



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Growth by expansion, principle of, 7, 122, 206-9

strategies of discovery derived from the, 220-1

Gursey, F., 233

H

Hacking, I., 89

Hahlweg, K., 145

Hamilton, W. R., 156

Hanson, N. R., 4, 66, 85-8, 91

Hegel, G., 189, 240

Heidegger, M., 92-3

Heisenberg, W., 194, 231, 233

Helmholtz, H. von, 178, 185

Hempel, C., 28f

Hermite, C., 51

Herschel, J., 97-100

Hertz, H., 166







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Hesse, M., 68, 84, 122-5, 258

Heuristic rules, 75, 149-50, 152-4, 246

domain specific, 81

recursive, 79

Heuristic search, 30, 57

Hilbert, D., 43

History of science, 127

Hofmann, J. R., 105

Hooke, R., 190

Hooker, C. A., 145

Hull, D. L., 210, 215, 247, 260

Hurd, D. L., 167

Huygens, C., 190

Hypothesis-generating argument, 86

Hypothetico-deductive (HD) method, 66-7, 98, 127-8

I

Idea pool, 209, 239, 248-9

Incommensurability, 75, 217, 248

Incubation, process of, 3, 5, 7, 35, 113, 142, 169, 174, 178, 180-2, 194, 217

Induction

elliminative, 30

enumerative, 65-6, 69, 81

justification of, 200

rules of, 149-50Inference

ampliative, 4, 63, 65, 68, 70, 74, 135-6, 152

deductive, 4, 30-1, 68-74, 81, 86, 102, 136, 151-2, 154, 161-2, 254

inductive, 4, 21, 31-2, 68-9, 86, 121, 154

license, 152

material rules of, 32, 74, 76, 93-5, 246, 254



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scientific, 152-3

Inferential practice, 120-1

Inhelder, B., 46

Innovation-tradition tension, 184-5, 197

Institutions of the scientific community, 142

Instrumentalism, 24, 25, 45

Intellectual migration, 185, 196, 225, 227-9, 241

Internal symmetries of hadrons, 42-3, 230-3

Interpsychic processes, 3, 174, 176, 217, 253

Intervention

cognitive, 19, 21, 26, 45

observational/experimental, 17-20, 40-1, 45, 121, 201, 221

technological, 207

Intrapsychic processes of creation, 3, 113, 173-88, 191, 197, 217, 253

Intuition, 61, 135-9, 142

Intuitionism, metamethodological, 134-5, 137-8

Intuitive type, 178

Invention vs. discovery, 4, 36-9

Inventive arguments, 4, 73, 95

Invisibility

of cognitive apparatus, 17

of premises, 5

of presuppositions, 93-4

Invisible college, 190

Involuntary processes of creation, 3, 5-7, 178, 191, 244, 254

Is-ought fallacy, 134, 138-9

J

Jacob, F., 3, 223-4, 229, 241-2

Jeans, J., 163

Jona-Lasinio, G., 237

Justification

of belief, 13



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consequential, 98, 100

generational, 98, 100

of methodological rules, 120-2, 124-6, 219

of scientific practice, 124-6, 131

Justificatory vs. generational parts of discovery, 62-3, 97-8

K

Kant, I., 44, 149, 251

Kantorovich, A., 3, 39, 82, 148, 210, 243

Kekule, A., 35, 185

Kelvin, Lord, 213-4

Kepler, J., 15, 28, 59, 64, 86, 95, 160-5, 169, 190, 203






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Kepler's laws, 12, 14, 23, 27, 66, 78, 124, 160-3

Kepler machine, 79

Keynes, J. M., 90

Kipling, J. J., 167

Kirchoff, G. R., 163

Klein, M., 164

Knorr-Cetina, K., 47, 225, 241

Knowledge

endosomatic and exosomatic, 145-6

as justified true belief, 13-4, 145

Koertge, N., 76

Koestler, A., 153, 160-4, 260

Kohn, A., 15, 168

Krohn, W., 92

Kuhn, T., 52, 60, 64, 75, 124, 185, 197, 211, 255, 257

L

Lagrange, J. L., 156

Lakatos, I., 14, 32, 82-3, 109, 127, 132, 159, 244, 246

Lamb, D., 181-2, 190

Lancaster, J. B., 202

Langley, P., 78

Laszlo, E., 216-7

Latour, B., 44

Laudan, L., 98, 105, 134-5, 137Laudan, R., 105

Lavoasier, A., 12

Laws of nature, 43, 59, 119, 152

vs. empirical generalizations, 21, 22

falsity of, 54

ontological status of, 22



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vs. theories, 16, 22-6

Leibniz, G. W., 51

Lenard, P., 15-6, 72

Leverrier, U., 85-6, 94, 227

Levinson, P., 210

Levi-Strauss, C., 3, 223, 242

Lindman, H., 90

Linneus, C., 159

Logic

community-specific, 4, 95, 74-6, 121, 136

material (content-dependent), 7, 93, 74-6

of ontogeny, 246

of pursuit, 5, 85-92

Logical empiricism, 1, 5, 52, 91, 97, 100-1, 117

Logicism, 6, 118, 125, 131-2, 139, 212

Lorentz, H. A., 158, 189

Lornez, K., 145

Lukacs, G., 190

M

Malthus, T. R., 36, 181-2, 190

Mann, H., 154

Mantell, G. A., 190

Marginality

intellectual, 240

professional, 239, 241

social, 185

Marsden, E., 72-3, 222, 226, 241

Material logics, 7, 74-6, 93

Maxwell, J. C., 23-4, 64, 151, 157-9, 189

Mayr, E., 224, 240

McMullin, E., 83

Mead, G. H., 45



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Page 2

origin of, 58-60

postmortem, 4-5, 50

Methodological rules, 120-2, 124-7, 130-1, 139, 157

Methodological theory, 124-6, 130-1, 135

Meyerson, E., 80-1, 168

Mill, J. S., 3

Mills, R. L., 236

Model

behind a research program, 32, 83-5

negative analogy of, 43, 84-5, 250, 252

neutral analogy of, 83-5, 245, 252

positive analogy of, 43, 84-5, 243, 252

Mulkay, M. J., 185-8, 192, 196-7, 228

Multiple discovery, 185

Munz, P., 251

Musgrave, A., 4, 70-1, 73-4, 86

Mutation, blind/quasi-random, see blind variation

N

Nagel, T., 205

Nambu, Y., 237

Nativism, 246

Natural kinds, 17, 21, 32, 70-1, 75, 136, 149, 187

Natural selection, 145-51, 153, 200, 216, 223, 237, 247

mechanized, 77models of creation and discovery, 2-3, 7, 29, 173-4, 241, 253

models of sociocultural evolution, 42

paradigm of rationality, 147

Naturalism, 6, 142

normative, 134-43

Nature vs. nurture dichotomy, 114, 246



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Necessary truths, 63

Ne'eman, Y., 3, 7, 81, 148, 154, 232, 235, 238-9

Nersessian, N., 258

Newton, I., 13-4, 23-4, 27, 31, 33, 35, 64, 66, 79, 94-5, 124, 128-9, 137, 143, 152, 156, 159, 162-3, 173, 176, 187190-1, 201, 203, 214

Newton's Rules of Reasoning in Philosophy, 50-1, 59

Nickles, T., 76, 94, 98, 260

Nicod's Rule, 104

Nisbett, R., 121, 136

Nishijima, K., 232

Normal science, 52, 60, 64, 83, 150-1, 153, 165, 186-7, 197, 215, 217, 243, 248, 252, 255

Normative-descriptive (ND) dichotomy,

and method of discovery, 57

and philosophy of science, 117-34

Novelty-generating argument, 65

O

Ockham's Razor, 59

Oersted, H., 168

Omega-minus, discovery of, 20, 233

Okubo, S., 233

Ontogeny, 8, 243-6, 250-2, 257

Opportunism

in context, 230

in natural selection, 228

in science, 229, 253

Osborn, A., 257

Osiander, A., 165

P

Pais, A., 233

Paradigm of rationality (POR), 6, 124-7, 130-3, 139, 142, 147, 157-8

Paradigm, scientific, 83, 130-1, 153-4, 187-8, 196-7, 203, 211, 217, 248, 250, 256

Particle physics, 12, 19-20



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authorities in, 192

experimenting in, 39-43

observation in, 33, 39-44

strategies of problem-solving in, 221

tinkering in, 8, 229-42

Particularism, 1, 6

Pasteur, L., 6, 113, 181, 228

Pauli, W., 194, 231

Peirce, C. S., 4, 66-8, 87-8

Penicillin, discovery of, 15, 113, 154, 165, 168

Performance errors, 140-1






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Periodic Table, 39

Philosophy of science

descriptive, 127-30

and discovery, 1-2

explanatory, 6, 110, 117, 123-34

naturalistic, 5-6, 109, 133, 145-6, 212, 255

normative, 126-7, 130, 132-3

Phylogeny, 145, 151, 216, 243-4, 248, 257

Piaget, J., 45-7, 201-2, 251, 257

Pickering, A., 45, 230, 232, 236, 238-9,260

Pinch, T., 92

Planck, M., 36, 72, 78, 163-5, 168, 171, 183, 194, 197, 203, 258

Plato, 226

Platonic solids, 160-1, 169, 226

Plausibility of hypothesis, degree of, 90-1, 104

Poincare, H., 34-5, 36, 61, 68, 86, 88, 99, 102, 110, 114, 177-8, 181, 189

Polanyi, M., 17, 94

Polya, G., 169, 180, 221, 227

Popper, K., 13, 14, 23, 54, 70, 74, 82, 98, 100, 108, 125, 128, 145-6, 148, 198, 209, 227, 244, 248, 255

Preadaptation, 150

Predictability, 88, 91, 104-6, 157, 178

explained, 219

Prepared mind, 113-5, 142, 181-2, 254

and recommendations for cultivating serendipity, 157, 168-71, 221

Probability of a hypothesis

conditional, 89-91

posterior, 89-90

prior, 54, 89-91, 104, 177

subjective, 89-90

Problem-oriented scientists, 228



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Problem solving, 28-30, 151-2, 157, 169-70, 257

by expansion, 207-8, 220-1

in normal science, 150, 153

in research programs, 155, 244

strategies of, 221

Projectible predicates, 69

Proto-theoretical entities, 24, 26

Prout, W., 221-2, 256

Pstruzina, K., 173

Ptolemy, 80, 158, 162, 203, 213

Putnam, H., 102-3

Pythagoras, 65

Pythagoreanism, 59, 160-2, 226

Q

Quantum gravity, theory of, discovery by serendipity, 155, 169

Quantum mechanics, discovery by serendipity, 163

Quine, W. V. O., 133

R

Radicati, L., 233

Radioactivity, discovery of, 165-8

Rationalism, 98

vs. empiricism, 218

Rationality

categorical, 53, 76, 108, 118

as cautiousness, 69

community-specific, 121

domain-specific, 76

ideal theory of, 139-41

instrumental, 53, 118

intuitionistic theory of, 134

naturalistic, 119

normative theory of, 140



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rules of, 6

scientific, 133, 137-8

shallow vs. deep theories of, 6, 134-43

theory of, 120, 122, 134-43

therapist model of, 141

Rawls, J., 121

Rayleigh, J. W., 163

Realism

and collective discovery, 195

constructive, 44-5, 47

convergent, 44, 46

and creative discovery, 36-48

epistemological, 44

and laws of nature, 23

naive, 44

metaphysical, 44

with respect to theories, 45

Reality, shallow vs. deep levels of, 47-8






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Page 2

Recombinations, 156

Recommendations for cultivating discovery, 114-5

Reconstruction of the discovery process, 64, 73, 98, 100, 179,

see also Method, postmortem

Recursive procedure, 77-80, 82

Reflective equilibrium, 121-3, 126, 136-7

Refutation of a theory, 12, 100, 109, 117, 198, 244

as a discovery, 19

Regge, T., 234

Regge poles theory, 229, 234

Reichenbach, H., 99, 103, 135

REM sleep, 173

Representation, 45-7

Rescher, N., 260

Research program, 7, 8, 25, 32, 80-5, 130, 152, 154-5, 159, 244-9, 254

degenerative, 83

hard core of, 82-3, 244, 246, 248-9

positive heuristic of, 82-3, 246

progressive, 14, 159

protective belt of, 83

Restivo, S., 241

Retroduction, 4, 66-8

Revolutionary science, 52, 153, 187, 217

Richter, B., 236

Roberts, R. M., 168

Roentgen, W. C., 15, 166-7

Rorty, R., 195

Ruse, M., 204-5

Rutherford, E., 32, 72-4, 83, 86, 95, 159-60, 192, 222, 226-7, 241, 258, 260

S



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Sakata, S., 235

Sakurai, J. J., 236, 238

Salam, A., 237

Sargeant, W. A. S., 260

Savage, L. J., 90

Schaffer, S., 260

Scherk, J., 155

Schroedinger, E., 56, 194

Schwarz, J. H., 155

Schwinger, J., 234, 236

Science education, 8, 255-8

Science of science, 117, 130

Science policy, 8, 170-1

Scientific method, 52-3, 127-8, 137-8

Scientific practice, 124-6, 130-4, 136-9

Selection, 139

vs. generation, 34-5, 68, 86-8, 101

process of, 7

social dimension of, 198-9

Selection cycle in science, 250

Self organization, goal of, 176, 183-4

Sensorimotor organs, extension of, 202, 209, 212, 214, 251

Serendipity, 3, 7, 27, 148-71, 174, 179, 198, 203, 216, 221, 223, 225, 229, 232, 244, 249, 253, 257-8

and adaptability, 208

and cooperation, 154, 160

cultivation of, 168-71, 220

explanation of, 180-2

and freedom of research, 170-1

the principle of, 8, 42, 148-57, 169-70, 217-9, 255

Shapiro, G., 168

Siegel, H., 103

Simon, H., 4, 78, 95



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Simonton, D. K., 3, 7, 36, 169, 173-8, 180-6

Skill of discovery, 5, 92-5, 113, 258

Skill-laden discovery, 94

Social acceptance, 193, 195

Social dimension of science, 7, 36, 49, 115, 119, 133, 160, 189-97, 203, 208, 258

Social epistemology, 7, 184, 189, 192, 212

Social recognition, 183-4, 196

Sociocultural evolution, 42, 147, 203-6, 209, 251

Socio-evolutionary POR, 160, 255

Socio-evolutionary processes of discovery, 219

Sociologism, 6, 125, 142, 219

Speciation, 240

Stahl, G. E., 12

Stein, E., 44

Sommerfeld, A., 258







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Stich, S., 121, 136

Storer, N., 36

Stratified stability, 156, 171, 216

Superstring theory and serendipity, 155, 169

Suppe, F., 106

Suppressed premises, 5, 64, 94

Szilard, L., 228

T

Tacit Knowledge, 76, 92-3, 136, 220

Taton, R., 34

Thagard, P., 148

Theaetetus, 226

Theory, (scientific), 20-7, 129, 252

dynamic, 25, 27, 82-4, 106, 244-6, 248, 251

vs. law of nature, 16, 22-6

mature (version of), 26-7

ontological claims of, 24-5

plasticity of, 20-7

as a statement, 23-4, 26-7

unified, 229-30

-versions, 32, 83-5

Theory-construction

dynamic, 26, 32, 80-5, 102, 246, 250

as a generational discovery, 33, 148heuristic-guided, 80, 152, 246

methods of, 150

Theory of science, 126, 139-40

explanatory, 7, 131-2, 138, 157, 253

evolutionary, 7, 133, 139, 147, 157, 173

naturalistic, 134, 247, 253



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Thomson, J. J., 73, 166

't Hooft, G., 12, 190, 238-40

Ting, S., 236

Tinkering, 3, 7, 8, 87, 225-7, 229, 244, 253-5, 257-8

in the context of generation, 226

in current algebra, 229, 238-9

evolutionary, 223-4

with group-theoretical tools, 231-3

in particle physics, 229-42

in quantum chromodynamics (QCD), 230

with quantum electrodynamics (QED), 230, 233-4, 236-7

with quantum field theory, 229, 232-5

with quantum mechanics, 230

with the quark model, 229, 235

and reasoning by analogy, 227

and renormalization procedure, 229, 234, 237-9

in savage thought, 223, 242

and short sightedness, 227

in S-matrix theory, 234-5

in Yang-Mills gauge theory, 236-41

Tomonaga, S., 234

Tool-oriented scientists, 227-9, 235-41

Toulmin, S., 145, 226

Tradition-innovation tension, 184-5, 197

Transactionalist epistemology, 45

Transparency

of cognitive apparatus, 17

of information channels, 95, 254

of observational instruments, 94

of premises, 5

of presuppositions, 18, 95, 246

of the principle of induction, 32



e_280


of rules of inference, 247

and skill, 93-5

of theoretical tools, 94-5

Truth criterion, 192-3, 215

U

Uhlenbeck, G. E., 258

Ultra-violet catastrophe, 29, 163, 165

Uniformity of nature, principle of, 59, 69

Unintentional processes of creation, 3, 6, 27, 36, 113-5, 153, 178, 191, 197, 223, 254

V

Variability and adaptability, 216

of ideas, 217

Variation, 139

unjustified, 148

Vaux, J., 93

Veltman, M., 12, 238-41

Vico, 46

von Neumann, J., 92







e_281

i 281

aharon kantorovich-scientific discovery.pdf

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