Technology and human sciences: a dialogue to beconstructed or a common tread to be rediscovered?

Fabio Aurelio D’Asaro∗, Valerio Perticone∗, Marco Elio Tabacchi∗† and Settimo Termini∗‡∗DMI, Universita degli Studi di Palermo (Italy)

Email: fdasaro@gmail.com, valerio@pertico.net, marcoelio.tabacchi@unipa.it, settimo.termini@unipa.it†Istituto Nazionale di Ricerche Demopolis

‡ECSC Mieres, Asturias - Spain

Abstract—In this contribution we begin to discuss the thesisthat an analysis of the similarities and differences of typicalmethodologies of human sciences, technology and hard sciencesshow some unforeseen but strong similarities between humansciences and technologies. In this context fuzzy sets ideas provideuseful tools which help to render the analysis more quantitativebut without loosing the connection with a purely descriptiveanalysis. These kinds of considerations would have been hardlyconceivable in the setting of XIX Century conception of science.It is the development of Information sciences that has allowedthese problems to emerge.

In this paper we shall then briefly outline the general contextin which the questions must be asked. The present paper, then,should be considered a (necessary but only a) prolegomenon toa future more specific analysis, the main (in our view) steps ofwhich will be listed in the final Section.

Index Terms—Fuzzy logic, Technology, Human sciences

I. INTRODUCTION

The present paper is a first step in a planned analysis of therelationships existing among human sciences, hard sciencesand technology in the light of the new conceptual toolsprovided by the emergency of fuzziness as a new scientificconcept. in particular, what we want to study is a similaritybetween human sciences and technology apparently stronger(at least from a methodological point of view) than boththe ones between hard sciences and technology on one sideand between hard and human sciences on the other side.As a matter of fact all the previous topics grew up as verychallenging corollaries of an analysis of the role that fuzzylogic has played and can play in many fields and, morespecifically, trying to understand the reasons of the difficultiesit has encountered and faced along the years. For this reasonthere is no need to underline and stress the fact that themain question stated above will be seen in connection withfuzzy sets and fuzzy logic. Let us also observe that whenusing the statement ”fuzzy logic” not only we mainly referto what Lotfi Zadeh calls ”fuzzy logic in a wider sense” butwe look at the subject as an experimental discipline exactlyin the sense foreshadowed by Enric Trillas in many occasionsand places. For clarity, let use quote in extensor one of hiscomments: “The flexible subjects fuzzy logic deals with (thatare in contraposition to the typically rigid or formal logic)force a different methodology than that of formal sciences toapproach the problem. This is like the case of Physics, whose

methodology is not that strictly formal of Mathematics, eventhough mathematical models play an important role in Physics.But these models are to be experimentally tested against theword. Like it happens with the mathematical models in fuzzylogic, that are important in the measure that they allow towell representing the linguistic description of system and/orprocesses. [...] Fuzzy logic is closer to an experimental sciencethan to a formal one.”

We want to remark also that all these topics and consider-ations (although phrased in a more general terminology andmainly referred to more general (and sometimes - culpably- generic) questions, are in fact strongly related to somecrucial discussions emerged in various places with respectto problems asked in the setting of CWW. We think thatthey would strongly benefit from a comparison and dialoguewith them and plan to do it in the occasion of subsequentsdevelopments; we hope – and are also convinced – that ourcomments and analyses could also provide additional hintsto these interesting discussions on these hot topics. See, forinstance, Question 4 of the Report Overview of the Panel atWCCI-2012 by Boris Kovalerchuk [?]: “Why do we havethe major applications of the fuzzy linguistic variables andcomputing with words (CWW) in fuzzy control not in theNatural Language Communications (NLC) that had originallymotivated CWW?” Let us finally observe that these kinds ofanalyses and problems not only wouldn’t have been consideredas crucial a few decades ago but they would have beenhardly conceivable in the setting of XIX Century conceptionof science. This is due to the development of new problems,questions, methodologies and open problems related to thenew question asked by Information Sciences. For this reason,the present paper will present in a cursory way a series of toursinto these new fields, listing questions and new possibilities.This is a necessary background for asking (before answeringthem) the correct questions. These will summarized in thefinal Section and will specifically tentatively answered insubsequent papers, of which the present one aims at beinga sort of prolegomenon.

II. A TOUR ON FUZZYLAND

Concepts as well as technical results and methodologies ofFuzzy Sets Theory and Soft Computing have been fruitfullyapplied to many different fields and domains. This has hap-

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pened – as often happens in the real history (and differentlyfrom the “rational reconstructions”) – following very tortuouspaths and in many cases not the ones expected by the peoplethat was constructing the more meaningful aspects of pieces ofnew scientific enterprises. Just to provide some examples weremember a few points. First, as has been remembered by RudiSeising in [?], it is interesting to observe that Zadeh’s originalforecast when he conceived the idea of fuzzy set, was thathis original approach would have been applied first to humanand social sciences. This is clearly stated by Zadeh in hisinterview with Betty Blair [?]: “I expected people in the so-cial sciences-economics, psychology, philosophy, linguistics,politics, sociology, religion and numerous other areas to pickup on it. It’s been somewhat of a mystery to me why even tothis day, so few social scientists have discovered how usefulit could be.”

But this did not happen. Why? As a matter of fact, theuse and application of his ideas went initially more in thedirection of the world of Engineering, after the model of fuzzycontrol by Mamdani-Assilian appeared, and in the direction of(pure) hard sciences, provoking many discussions with regardsboth to the debate probability vs fuzziness and to the (true)relationship of fuzziness with mathematics and (mathematical)logic. For what regards the first point, let us remember that,ironically, not only the “social” development of the newproposal went in a direction different from the one thoughtand envisaged by its founding father (Engineering instead ofhuman sciences), but as has recently observed Ron Yagerin this preface to the volume “On Fuzziness” [?] also thewide application of fuzzy techniques in Control Engineeringfollowed new paths with regard to his own “orthodoxy”: “[i]nmany ways Lotfi is still an outsider, in this case in his ownfuzzy set community. Most of the applications of fuzzy setsare based on the Mamdani-Sugeno model. This paradigm isa kind of disjunctive approach, as we get more informationwe add possibilities. Zadeh’s perspective, as conveyed withhis paradigm of restriction-based semantics, is a kind ofconjunctive approach, as we get more information we reducepossibilities.”

For what regards the second point, it is well known thatZadeh himself has often stressed that not only it is possibleto distinguish between two different meanings of fuzzy logic,but one must do so. So, from one side, Zadeh’s ideas havetriggered along the last decades a new interest of logicians andmathematicians towards old ideas of Jan Łukasiewicz and EmilPost, read in the light of the qualitative more extended preciousrequirements which has permitted to develop these old intu-itions along unforeseen and at the time unpredictable avenues.So this development, “fuzzy logic in its narrow sense”, isprimarily applied to extend and generalize preexistent logicalsystems through the introduction of degrees of truth. We canalso affirm that these developments went in the directionforeshadowed by John von Neumann [?], [?] of helping logicto go out the “fences” of the most difficult part of mathematic,i.e. combinatorics.

However, we can bet that this is not what Lotfi Zadeh

was primarily thinking about. What he had and still has inmind – as a crucial point – is much more than a purelylogical system. With the expression “Fuzzy logic” we shouldrefer to a (precise) system of reasoning able to work withclasses having unsharp boundaries – i.e. objects of reasoningand computation which can be usefully represented by fuzzysets. More generally, a fuzzy logic could be an organizedand interconnected aggregation of interacting systems of theprevious type. So, “fuzzy logic” in a wide sense is much morethan a logical system, and many of its applications involve nologic at all in the traditional (modern) use of this word. Sowhile fuzzy logic in a narrow sense has found a traditionalplace in the setting of hard sciences, in the wider sense,fuzzy logic has much more to deal with problems pertainingto the domain of social and soft sciences. Following a fewsuggestions from Zadeh one could also maintain that fuzzylogic in the wider sense is not properly “a logic” according tothe canon fixed by mathematical logicians, although it can berightly considered so according to more general and colloquialcanons referring to the “art of reasoning”, in this case havingto do with concepts and notions that naturally exhibit in theirdefinition an ineliminable absence of sharp boundaries. Whyare we bothering so much with questions and facts which,however important and crucial, are also widely well knownto all the fuzzy community? First they are not equally knownoutside it, but however, a good example of “social interactions”in a scientific community as well as another good exampleof the subsequent drift of meaning of some crucial notionsand of the change of the central goals of a new emerginginquiry that a true interaction can involve and produce. Thesecond reason impinges to the relevance of the net of the factssummarily recollected above to some of the questions posedby Veronica Sanz and Rudolf Seising in the motivation of thisSpecial Session. Not only “scientific methodologies” of SoftComputing are very apt to “describe or model phenomena ofphilosophical and social aspects of science and technology”,but the real historical development of soft computing is in itselfa very good example, maybe a case study, of the interactionamong new ideas, new technologies and their social images:images of science, images of technology, images of howscience and technology interact, and how they interact withculture in a general sense. An analysis of this type, involvesa general setting in which to take into considerations themeaningful innovative aspects of the involved notions andscientific developments. In the following Sections we shalldiscuss the following problems:

• Which is the natural domain in which these generalquestions can be “correctly” asked?

The relationships among human sciences, hard sciences andtechnology are usually studied having in mind, in a moreor less explicit form, a sort of general connection amongthere which directly link hard sciences and technologicaldevelopments on one side and, more loosely, humanities andhard sciences. No really meaningful and conceptually deepconnection is assigned to the interaction of humanities and

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technology (besides, of course, the obvious ones of the culturalreflection on the role of technology and its use in humansciences.

• We ask whether this received view should be revised – ata methodological level – in the light of the experience ofthe more than half a century development of informationsciences and their technological developments.

The search for new methodologies has opened the way for apossible new dialogue between hard and soft sciences. In allthis very creative confusion, Fuzzy Sets Theory has played avery crucial role since its typical features put it at the crossroadof all these problems, challenging questions and difficulties.Also for this last reason – we think – it has paid, along theyears, a very high price for its assessment.

III. THE “NATURAL” CONTEXT

Let us now turn to the first question asked at the endof the introduction. There are, in fact, domains in whichsome questions can be more naturally asked. Now, whilethe natural scientific background is automatically provided inmore traditional disciplines (such as mathematics or physics);it should be carefully pinpointed and constructed in the caseof recently emerged fields of investigation or of fields inwhich different attitudes and methodologies interact as is thecase for interdisciplinary investigations. Now, as it is wellknown, one of the early reference points for topics dealingwith information in a general sense, in the middle of lastCentury has been Cybernetics, as well argued and documentedby Rudolf Seising in [?], [?]. Although, today, cybernetics isa neglected name, it can be, however, useful to look at a fewfragments of his history to pinpoint and characterize somefeatures central to the development of information sciencesin general. See also [?] and the volume in which the paper iscontained [?]. Questions about cybernetics seem to be relevant– although the name seem to be obsolete – since this disciplineposed for the first time new problems that seem to be crucialfor all information sciences still today. But while cyberneticshas always aspired to be considered a classical science, at leastfrom a methodological point of view, two arguments weightagainst it being a normal scientific discipline: its very scatterednature, and its strong relationship with interdisciplinarity. Wewill discuss both points in the following subsections.

A. A scattered discipline

It is clear by looking at the historical perspective thatcybernetics encompasses a lot of sub-disciplines, that in asharp contrast with other, older scientific disciplines, such asmathematics or physics, do not fuse into a single, coherentwhole. There is something in this already in Wiener’s defi-nition of what cybernetics is: “Communication and Controlin the Animal and the Machine” [?], a definition embracingso many different fields, competences, aims and scopes. Thisreflects what happened in the heydays of the disciplines, theforties and fifties of the twentieth century, when cyberneticsacted as a sort of catalyst, being the converging point of a lotof interesting and new ideas, concepts and formalisms stirring

in a very creative as well as disordered way, breaking theboundaries of traditional disciplines. A better shot at the unityof the discipline was had by Eduardo Caianiello, proposingthe thesis that the unifying element of all the cyberneticsresearch program was its relationship with the vague yet fun-damental concept of intelligence. He maintained in differentcircumstances that cybernetics could be characterized by itssubstantiation as a scientific approach to the modeling ofdifferent aspects of intelligence. Unfortunately this attemptat unification failed, as different schools of thoughts, whileenjoying the concept of intelligence search, assumed differentand often not easily conciliable attitudes with respect to thespecific problems posed by this framework. For some generalviews on the problem see also [?], [?], [?].

B. Interdisciplinarity and Cybernetics

A central and crucial role in cybernetics is played by inter-disciplinarity – to the point of it being sometimes defined as atransdisciplinary approach to system control and replication.The role interdisciplinarity played in the development of thefield has rarely been assessed in a complete and clear way,and as such it deserves to be better analyzed as a model ofinvestigation, complete of its chaotic but creative, unsystematicbut full of innovative insights, since it can provide usefulsuggestions and ideas. In order to assess the real centralrole that interdisciplinarity plays in scientific development,we should start by asking why interdisciplinarity does playsuch an important role in cybernetics while it seems to playa negligible role in other, older scientific disciplines (mathe-matics comes to mind, but for sure is not the only one). Wemaintain that interdisciplinarity is not an add-on that if stickedto any discipline instantly makes it better and deeper-reaching:the use of interdisciplinarity frequently creates problems, andmore often than not its superficial use serves only to hide thefact that no innovative problems are really being discussed. Inhis still current and full of hindsight “The University in Ruins”[?], Bill Readings acknowledges that “the benefits of inter-disciplinary openness are numerous” but also warns againstthe negative role that an uncontrolled use of interdisciplinaritydone by academic authorities can produce in the setting ofthe present transformations of the University: “[w]e can beinterdisciplinary in the name of excellence, because excellenceonly preserves preexisting disciplinary boundaries insofar asthey make no larger claim on the entirety of the system andpose no obstacle to its growth and integration. To put thisanother way, the appeal to excellence marks the fact that thereis no longer any idea of the University, or rather that the ideahas now lost all content.” (ibidem, p. 39)

Let us make a distinction. We call scientific disciplinesthose springing out of problems and which are related to therational reconstruction of the connection of answers providedto the questions posed by them. We call academic disciplinesthose coming out from the stabilization of the results obtainedby studying important old problems. In this contest, Inter-disciplinarity often arises in order to discuss new, potentiallyimportant problems in the discipline itself, hoping that a fresh

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perspective, a different way of seeing things could be ofhelp. As such, its use highlights the uneasiness in facingnew problems often displayed by the academic disciplinesin a specific historical moment. Undoubtedly, science goesforward by solving the problems that scientists and humankindalike encounter. Problems usually arise from nature: not byitself, obviously, but from a natura naturata, viewed throughthe tinted glasses of culture, or of the specific tradition inwhich we are immersed. Of course, problems do not belongto a single and specific discipline, unless we assume anessentialistic attitude, which involves a classification of thephenomena according to their true nature, their essence: anattitude of Aristotelian type, not so familiar with modern sci-entific thought. Scientific disciplines are different and separate,but their difference and separation are a function of theirdevelopment and of the historical moments in which suchdisciplines were born and evolved. Furthermore, such bound-aries are not set in stone; as an example just think to Opticsand Electricity and Magnetism, which had been consideredseparate disciplines until they were unified by Maxwell theory.However at some point in their history scientific disciplinesmay also become academic disciplines, which differ from theformer in being rigid, and obeying a socially induced divisionof labor. In academia interests as different as humanly possiblefrom the pure development of scientific ideas are present, andoften these interests are preponderant.

Here’s the exact situation where Interdisciplinarity playsa role: it tells us that a new problem can be tackled onlyif we escape the boundaries of established disciplines; suchapproach induces an updating of scientific disciplines as theyare organized at a specific juncture of their history. Maybean example of this kind of interaction is also provided bythe resolution problems connected with the use of informa-tion theory concepts in dealing with aesthetic questions and,perhaps, as suggested in [?], [?] more easily tackled throughthe use of concepts arisen in a fuzzy context like the theoryof measures of fuzziness. Moreover, It helps in overtaking therigid constraints imposed by “academic” disciplines, whoserigidity can impede the full explication of the results thatthe “scientific” knowledge of a certain time would allowto obtain. A look at the development of cybernetics fromthis observation point shows its positive role played for therenewal of all the disciplines which interacted with it notonly at the height of its splendor but every time a complexproblem was seriously approached through its undogmaticmethodology. Such a legacy should be fully drawn on byinformation sciences in their most general sense.

C. Different attitudes, different methodologies

So these are the roots and the crucial methodologicalproblems in which we can try to correctly ask, before tryingto answer, questions related to the interaction between hardsciences, technology and humanities and see which is therole that the same idea of “Fuzzy Sets” and “Fuzzy Logic”and their induced methodology can play in this dialogue. Itis perhaps useful to reflect on the methodological difference

between the standard Galilean methodology of hard sciencesand a purely descriptive attitude which seems more similar tothe methodology used by soft sciences and which has beenfruitfully explored in new terms by such approaches followedin soft computing. We consider this problem crucial to ourdiscussion, and as well pointing at its existence seems oblig-atory in the discourse’s development. As such, we confrontthe descriptive attitude with the more common approach of“making bold hypotheses” followed by a controlled “testing”.

The concept we want to stress here is that sometimes thebest solution to the problem of modeling a piece of realityis to try and mimic the behavior of the same fragment ofreality we want to model, entering an iterative path whichcan be summarized with a certain degree of simplificationin “mimicking, improving, repeat”. This apparently simpleway of doing science is all-encompassing: there is nothingelse, conceptually profound or otherwise, to be discovered orlooked for. This description can satisfy all the scientists bylimit themselves to a process of continuous refinement. Whilethis hypothesis may seem oversimplified, even caricatural, itis important to stress that this is nothing new. The so-called“naive physics” which has seen better fortunes a few decadesago, went exactly along these lines. Also some tendencies inAI, which stress the fact that “the computer program” is thetheory of a certain mental phenomenon or of an intelligentbehavior which is reproduced by a successful algorithmicsimulation - if they are taken literally and not in a metaphoricalsense - go in the same direction, at least methodologically[?], [?]. To stay true to our original aim even some resultsin Fuzzy Sets Theory, which are noted for their ability ofsatisfactorily mimicking the portions of reality under investi-gation, could suffer of the same fate. This is not, however, theonly path that can be followed: the ability to imitate realitywith increasing accuracy is certainly a good starting point forthe understanding of real phenomena, and at the same timecan be considered as a first step in focusing problems andquestions, and systematizing methodologies and tools to beused. The method itself is flexible in its application: after a fewiterations and refinements we can opt for different strategies,maybe more on line with the classical methodological attitudesof science, or for completely different paths altogether.

IV. HARD SCIENCES, HUMAN SCIENCES, TECHNOLOGYAND FUZZY SETS

Italian mathematician-turned-painter Mario Sangiovanni hasit when he says that “Science is the investigation of Creation,Art its continuation”. This intuition is an encouragement todiscuss the mutual relationships that exist between fuzzysets and human sciences, and also to extend the musing tothe involvement of technological developments, and humansciences in these relationship. We have already discussedaplenty [?], [?], [?], [?], [?], [?], [?], [?] the idea of a strongsimilarity, more of a methodological than of an ideal nature,between Fuzzy Sets Theory and human sciences; but this verysimilarity is the key in using Fuzzy Sets means and experi-mental apparatus as a bridge erected between human and hard

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sciences (again see [?], [?]) – though this also spells problemswhen solutions for problems that are inherently of a humanistnature are to be solved using the innovative techniques at theforefront of fuzziness, and also hints at why the use of fuzzytechniques and tools in human science domains, an apparentperfect match between aims and results, is not as widespreadas it ought to be. In asking ourselves why this is so, we cannotavoid pondering how there exists a link between technologyand human science which is more deep and strong than theself-evident association between technology and hard sciences:any time we embark in the critical analysis of a technologicalproduct, we deal with an artifact, and the means and tools weuse are the same that are employed in the same analysis whenthe objects is a human sciences’ “product”, be it a literaryeffort, some artistic representation or even an “humble” poem.Both in technology and in art (pick any of the septem artesliberales) we deal with artifacts, while findings and resultsfrom hard sciences, though often evoked by or directed attechnological applications themselves, only deal with natureand its complicated, sometimes inscrutable mechanisms.

A. Imagination and Rigor: intuitions become notions

We have just briefly discussed the relationship between hardsciences, human sciences and technology in light of Fuzziness,but in order to better understand this link we also have tounderstand some crucial features of the development of infor-mation sciences [?], and in particular how can new intuitionsand innovative notions become stable founding blocks of newscientific theories. In our opinion, Gregory Bateson offersan inkling on what is going on with his description of theassociation between two crucial concepts: Imagination andRigor “the two great contraries of mental process, either ofwhich by itself is lethal. Rigor alone is paralytic death, butimagination alone is insanity.” ([?], page 242) A perfect bal-ance of imagination and rigor is as such a crucial aspect of thedevelopment of scientific thought, and from this perspectivethe birth and development of new theories and disciplinescan be observed with great precision. Alas this vantage point,although well known in principle and intuitively self-evident,has been seldom frequented by the academia: the only scholarwho deals with similar intuition but worked on in somethingdirectly applicable to the framework of scientific discoveryand to the scientific paradigm in general seems to be RudolfCarnap [?], who introduced the terms of explicandum andexplicatum to characterize the different epistemological rolethe informal and formalized notions play in the development ofa scientific discipline or theory. Defining these terms, Carnaprefers to a way of approaching and analyzing the problemof the development of scientific theories which keeps in theforefront Bateson’s idea, and establishes a method that canalso be employed to investigate in detail the path followedby the development of Fuzzy Sets Theory [?], [?], [?], [?],[?], [?]. A further analysis of the existing links between theidea of Bateson and the concepts developed by Carnap couldbe a good starting point for a better and deeper knowledgeof the innovative epistemological significance of information

sciences, and of Fuzziness in particular.

V. A REFLECTION ON SOME SPECIFIC IDEAS

A few general (although tentative and provisional) conclu-sions we propose to draw from this analysis are the followingones:

• Hard sciences (from Galileo on) strongly depart fromcommonsense and from a commonsense analysis of real-ity and of classes of “natural” or “social” phenomena.

• Technology – although “locally” based on specific resultsof hard sciences – seen from the point of view of the finalobtained/obtainable artifacts, follows a more traditional,commonsense methodological attitude that the one typicalof hard sciences. Perhaps we can say more: technologyis more methodologically similar to human sciences thanto hard, natural sciences.

• Information Sciences differ from traditional hard sci-ences, being grounded in more “immaterial” notions andconcepts. This should transform them in soft sciences,more similar to social sciences. A tentative hypothesis forexplaining why this does not happen has been presentedin [?], [?].

• The methodology of Fuzzy Sets plays in this generalscheme a crucial double role. From one side it is reallya bridge between Human Sciences and Hard Sciencesin the sense that it helps transferring ideas, methodsand intuitions between these two activities of humanintelligence by providing a sort of conceptual “neutral”language. From another side it helps focusing thosecommon aspects of humanities and technology which canbe usefully formalized through tools which continues tobe ”near” to commonsense but, at the same time, abstractenough to provide the possibility of constructing ”mod-els” of those pieces of reality taken into consideration.

A final remark: what we deal with in the last topic is whathas superbly been done by Mamdani in the case of ControlEngineering [?], and is also what is done in humanities orsocial sciences, where we try to abstract a little from our objectof study but not too much as to loose a direct connection withthe pre-scientific description of the problem. In a more directway: A model of a social phenomenon abstracts from the con-crete situation but an abstractism of the same level as the onedone in theoretical physics is methodologically unthinkable. Amodel of theoretical physics does bold hypotheses completelydifferent from the surface description of the phenomenon itaims at explaining. The connection is recovered, later, at thelevel of the necessary consequences of those bold hypotheses.Such a control is unfeasible for models in social sciences. Letus incidentally observe that some very abstract developmentsin economic seem to have produced undesirable consequences.In all these fields a moderate level of abstraction could be veryfruitfully (as also remarked by Zadeh many times, in particularin the interview previously quoted [?]) when using fuzzy toolswhich help to render the analysis more quantitative but withoutloosing the connection with a purely descriptive analysis.

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VI. WHERE DO WE GO FROM HERE

In the setting of the problems and developments of Infor-mation Sciences outlined above, it will be possible to analyzein more detail the crucial questions implicitly asked at thebeginning of the paper, namely, how can we reconstruct andrediscover a common tread that exist between technology andhuman sciences? This question is also strictly related to somedebated problem in fuzzy set community. Ariadne’s threadto be followed is the following: both technology and humansciences are a product of the activity of man, and both can befruitfully analyzed by trying to observe critical description ofwhat they do. The language as well as the conceptual “attitude”of fuzzy sets is a very good tool for doing such a precisebut not too abstract analysis. These hypotheses, of courseshould be tested on specific case studies. Two interestingexamples seem to be on one side Mamdani’s theory of ControlEngineering, already cited, and, on the other side, the analysisof a piece of literature as an example of a sociological analysisof reality, (the same thing could be done also for the analysisof a painting). It is interesting to remark – in concluding thepaper – that in [?], an interesting analysis of a novel of thecatalan writer Enrique Vila-Matas is fruitfully done by usingelements and tools of fuzzy logic.

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