looking for arguments
TRANSCRIPT
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SUBMITTED VERSION – NOT TO BE QUOTED
Looking for Arguments
Hugo Mercier
Philosophy, Politics and Economics Program
University of Pennsylvania
313 Cohen Hall
249 South 36th Street
Philadelphia, PA 19104
http://hugo.mercier.googlepages.com/
267-340-2285
Keywords: Argumentation, Reasoning, Dual-process theories, Relevance, Satisficing.
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Abstract: How do people find arguments while engaged in a discussion? Following an
analogy with visual search, a mechanism that performs this task is described. It is a
metarepresentational device that examines representations in a mostly serial manner until it
finds a good enough argument supporting one’s position. It is argued that the mechanism
described in dual process theories as ‘system 2’, or analytic reasoning fulfills these
requirements. This provides support for the hypothesis that reasoning serves an argumentative
function.
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How do people find arguments? When engaged in a discussion, in a debate, everyone is able
to find arguments defending her position, and do to so quickly (Shaw, 1996). Even very
young children can perform this feast—something their parents are not always happy about
(see Mercier, submitted, for review). Despite the omnipresence of argumentation in daily life,
we know very little about the psychological mechanisms underpinning this ability. A goal of
this paper is to describe and ground in empirical data a model describing the psychological
mechanisms that are used to find arguments. ‘Argument’ is to be understood here as a
synonym of ‘reason’ or ‘supporting statement’—what we say when we want to convince
someone—and not in its technical, logical meaning. These are the arguments we use when
arguing in daily life.
Several lines of work are relevant to the psychology of argumentation, but none of them has
asked directly the question ‘how do we find arguments?’ First, when people argue, they
reason. If psychologists agree that reasoning is involved in argumentation, standard theories
of reasoning would seem to have little to say on this topic: The word ‘argumentation’ does not
appear in the index of the three books describing the major theories of reasoningi. Moreover,
most tasks in this literature involve participants either evaluating the conclusion of an
argument or trying to determine if a logically valid conclusion follows from some premises.
In neither case do they have to actually find premises for a given conclusion. Despite these
apparent methodological shortcomings—regarding the question at hand—I will argue that the
ability psychologists of reasoning have been studying is the same ability we use to find
arguments, thus rendering their conclusions highly relevant.
A small but growing field of research investigates argumentative abilities more specifically.
With a few exceptions, these experiments usually deal with the understanding, not the
production, of arguments. They have shown that participants can adequately follow the
commitments of different speakers (Rips, 1998), attribute the burden of proof (Bailenson &
Rips, 1996) and that they react appropriately to fallacies of argumentation (Baum, Danovitch,
& Keil, 2007; Corner, Hahn, & Oakfsord, 2006; Hahn & Oaksford, 2007; Hahn, Oaksford, &
Bayindir, 2005; Neuman, 2003; Neuman, Weinstock, & Glasner, 2006; Oaksford & Hahn,
2004; Rips, 2002; Weinstock, Neuman, & Tabak, 2004). Psychologists interested in
argumentation and informal reasoning have recorded the production of arguments by
participants, but there have not developed processing models as those offered in standard
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psychology of reasoning (e.g., Kuhn, 1991; Perkins, 1985). In social psychology dozens of
experiments have tested the effect of the argument strength on persuasion but, again, this only
speaks to evaluation and not production (see Petty & Wegener, 1998 for review). Linguistics
is another domain suffering from the same asymmetry between the study of understanding
and that of production. But what comparatively little work there is in language production
(e.g., Levelt, 1989; Levelt, Roelofs, & Meyer, 1999) does not speak to the much more specific
issue of argument production. Finding a good argument and knowing how best to express it
are two relatively distinct problems. As I explain later, standard communicative skills are not
sufficient to find good arguments.
Aside from the experimental literature, one can find many models of argumentation (see van
Eemeren, Grootendorst, & Henkemans, 1996, for an introduction). These models are often
concerned with creating typologies of arguments or arguments parts. For instance, Stephen
Toulmin devised the famous distinction between claim, datum, warrant, backing, rebuttal and
qualifier (Toulmin, 1958). These models may be very helpful heuristics in designing
psychological theories but they are not, in and of themselves, psychological theories either of
argument evaluation or argument production.
Given how little research has been dedicated to the topic, starting from scratch may seem to
be the only way to proceed. I will argue otherwise. In the next section the argumentative
theory of reasoning will be briefly introduced. According to this theory, arguing—finding and
evaluating arguments—is the very function of reasoning. If this theory is correct then the
capacity that has been studied and described by psychologists of reasoning is precisely the
capacity required to find arguments. In order to prove this point, the first step will be to
predict what kind of psychological mechanism would be best fitted to the task of finding
arguments. It will then be possible to compare this list of requirements to the actual attributes
of reasoning. I will try to show that there is a very good match between what is required of an
ability that has to find arguments and reasoning as described by current theories. This will
fulfill the two goals of the paper: providing a model of how we find arguments and, while
doing so, supporting the argumentative theory of reasoning.
The argumentative theory of reasoning
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Many fields of psychology have converged on the idea that the mind can usefully be divided
into two broad categories of mechanisms. Thus one can find a distinction between automatic
and controlled attention (Posner & Snyder, 1975), implicit and explicit memory, learning or
attitudes (Berry & Dienes, 1993; Reber, 1993; Schacter, 1987; Wilson, Lindsey, & Schooler,
2000) and heuristic and systematic evaluation processes (Chaiken, Liberman, & Eagly, 1989;
Gawronski & Bodenhausen, 2006; Petty & Cacioppo, 1986). More recently (though see
Wason & Evans, 1975) these dual process theories have spread to the field of reasoning and
decision making (Evans & Over, 1996; Kahneman, 2003; Kahneman & Frederick, 2002;
Sloman, 1996; Stanovich, 2004). Despite some underlying commonalities in the way the
distinction is drawn, it is not entirely clear that the two categories of psychological processes
have the same extension in these different domains of psychology. Here we will focus on the
distinction used in the field of reasoning and decision making and well represented by Evans’
heuristic-analytic theory (Evans, 2006, 2007). According to this theory, cognitive mechanisms
can be divided into heuristic processes—fast, nearly costless and generally unconscious—and
analytic processes—slow, effortful and generally conscious. When first looking at a choice of
cookies your heuristic system will direct your attention towards the most delicious or the most
colorful looking treats—or simply those you usually buy. Then your analytic system may (or
may not) kick in and urge you to compare the calories you would get from different brands in
order to make a more rational (diet-wise) choice. There is growing evidence both in reasoning
and in decision making supporting the validity of such a distinction (see Evans, 2003, 2008;
Evans & Frankish, 2009, for reviews). A related way to frame this dichotomy is to draw a line
between intuitive inferences (or intuitions) and reflective inferences (or reasoning) (Mercier &
Sperber, 2009). In this model, reasoning is a very specific cognitive mechanism that finds and
evaluates reasons. In this article, ‘reasoning’ will only refer to this sense of reasoning: a
mechanism that bears on reasons. It is to the function of this ability that we now turn.
Most theories of reasoning—in psychology or in philosophy—assume that reasoning fulfils
an overall epistemic and/or practical function: it generates new beliefs, creates knowledge,
and drives us towards better decisions. Pointing out some flaws in this assumption Sperber
has suggested instead that reasoning has an argumentative function (Sperber, 2000, 2001).
Building on standard theories of the evolution of communication, he makes a good case that
reasoning may have evolved in order to convince others and only be convinced when it is
worth it. This theory—the argumentative theory of reasoning—has profound implications for
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the way reasoning works, when it works well, and the results it should achieve. Drawing from
different literatures—psychology of reasoning and decision making, social psychology,
developmental psychology—it has been possible to find a great wealth of empirical support
for this view of reasoning (Mercier, submitted, in press; Mercier & Landemore, submitted;
Mercier & Sperber, 2009, in press; Sperber & Mercier, in press). For instance, people are
good at arguing but bad in abstract reasoning tasks, even though the later should be much
easier. Reasoning becomes much more efficient in argumentative contexts. The workings of
reasoning display a consistent and robust confirmation bias. And when we reason before
making a decision, reasoning drives us toward a decision for which we can argue but not
necessarily a good one. But for one—the confirmation bias, that will be mentioned later—
these predictions bear more on the contexts that lead to felicitous reasoning and on the effects
of reasoning than on the way reasoning actually works. Making the hypothesis that one of the
main functions of reasoning is to find arguments, it should be possible to draw predictions
regarding the workings of reasoning. The remainder of this article will be dedicated to making
and testing these predictions. I will try to show that they fit in very well with standard
descriptions of the workings of reasoning, descriptions that were arrived at with very different
theoretical assumptions. This fit can thereby be seen as further validation of the argumentative
theory of reasoning.
The task: finding arguments
When trying to find arguments several elements have to be taken into account. The most
important is the message (the conclusion) that we want to communicate. We are trying to find
arguments either because this message has been rejected or because we think it may be if we
try to deliver it on its own. The other important elements are the audience and the context.
Different arguments may be effective for a child or an adult, and different arguments expected
in a pub or a courtroom. Here is a very mundane example in which the need to find arguments
arises:
Simon and Margo want to go to the opera.
Simon says ‘let’s take the Tube’.
Margo answers ‘I’d rather walk’.
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At this point Margo and Simon may try to convince each other to use their favorite mode of
transportation. The task they face is to find good arguments supporting their respective ideas.
The first problem they encounter is that the space within which they have to search is huge.
Many different beliefs could be used as potential arguments. Beliefs about the weather—is it
too cold outside, or just warm enough? Beliefs about the esthetic qualities of parts of
London—it’s nice to walk along Tottenham Court Road. Beliefs about the location of good
shops—if we walk we could buy food for dinner on the way. Beliefs about previous
interactions—last time I let you choose. Beliefs about public transportation in London—the
central line is out of order. Beliefs about a person—I know you recently broke your ankle,
you shouldn’t walk too much. The list could go on to encompass beliefs that are only dimly
related to the topic at hand, such as beliefs about astronomical phenomena—if we walk we
may have a glimpse of the lunar eclipse that will happen tonight.
The size of the search space would not be a problem if it were structured in such a manner
that the best arguments would simply be the most accessible elements. But this will only
rarely be the case: what makes a good argument is highly contextual and the whole cognitive
system is not geared towards finding good arguments. Beliefs about the weather could be
good arguments for Simon or for Margo depending on their tastes and on what the weather
actually is like. Beliefs about esthetic qualities can be either relevant as arguments for Margo
(if the scenery is beautiful), for Simon (if it’s downright ugly), or simply irrelevant (if it’s
mediocre). Beliefs about good shops could be relevant as arguments for Margo (if the shops
are on the way), for Simon (if they are close to the Tube station), or irrelevant (if they have
nothing to buy). This could go on for all potential arguments. For instance, the first things that
Margo will think of may be ‘if we walk we will arrive on time’, which is a good argument
only if the Tube doesn’t allow that; ‘it’s a bit cold outside’ which would be a
counterargument; ‘I usually walk there’ which is rather irrelevant as an argument, etc. The
order in which the beliefs are examined will only be loosely related to their value as
arguments. What this means is that the task of finding arguments comes down to a filtering of
beliefs until one that is deemed to be a relevant argument is foundii. In order to better
understand how doing such a thing is possible, we can use an analogy with another
mechanism that involves a similar filtering: visual search.
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Visual search can work in very different manners, depending on the target and the context of
the search (see Li, 2002). It can proceed in a parallel, fast fashion if the target does not share
many attributes with the surrounding objects: if they belong to different and well defined
categories (Duncan & Humphreys, 1989). If you are looking for a tennis ball that was
misplaced in the cutlery drawer, there is no need to scan different objects: you are going to
focus immediately on the ball. On the other hand, if either the other objects are similar to the
target (a tennis ball among other yellow balls of a similar size—or the proverbial needle in a
haystack), or if the other objects do not belong to a well defined category (a tennis ball in the
closet you have been filling with junk for 20 years), then you cannot immediately focus on the
target. Instead, your visual system focuses on different objects, in turn, and decides if they are
the one you are looking for—it uses a serial search. Reasoning, the ability we use to find
arguments, works in a similar manner, but instead of searching through objects, it searches
through representations. Much in the same way as searching through objects implies creating
representations of these objects, searching through representations requires creating
representations of these representations. Thus reasoning is a metarepresentational mechanism:
a psychological device that creates and deals with representations of representations (Sperber,
2000). This is the first important prediction to be tested, in the next section. But the task
reasoning has to perform is in fact even more complicated that finding a needle in a haystack,
because it does not even know what the needle looks like.
When we are looking for an argument we rarely, if ever, know exactly what it is that we are
looking for: Often, there will be no way to tell in advance exactly what will be a good
argument for a given conclusion in a given context. There may be some broad indications,
explored later in the article, but rarely a precise picture as in the case of the tennis ball or the
needle. A better analogy than visual search for a known object is that of a search for an ‘ad-
hoc’ category (Barsalou, 1983). For instance, you just moved in a new place and you have to
drive a nail but you do not have a hammer. You can look for an object that could be used to
drive a nail instead of a hammer. ‘Objects that could be used to drive a nail instead of a
hammer’ is a novel, ad-hoc category that you developed on the spot. Compared to the
category ‘hammers’ this category is very poorly defined. The object should not be too small
or too big. It should not be too fragile. It should not be too expensive. It should be relatively
easy to handle. But apart from that, it can have many shapes, any color, etc. What you do to
find such an object is scan your environment and for each object that attracts your attention
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see if it matches your list of requirements. The order in which objects are going to be scanned
is influenced by these requirements—very small or very large objects may not even be
considered for instance—but it will mostly be directed by factors largely irrelevant to the task
at hand. Attributes such as color or proximity will drive the order in which the search is
conducted. Likewise, the order in which reasoning considers potential arguments is driven by
considerations that are partly irrelevant to the task of finding a good argument, as illustrated
earlier by the thoughts that are the most accessible for Margo but that are not relevant as
arguments. The order in which beliefs are considered is explored in the fourth section that
deals with relevance. Another property of this type of search is its seriality. Only one object
(in visual search) or one representation (in the search for arguments) is considered at a given
time. That reasoning mostly functions in such a manner will be demonstrated in section five.
But before this, we turn to the most fundamental property a mechanism whose function is to
find arguments should have: that of being metarepresentational.
Reasoning as a metarepresentational device
The question of whether reasoning should be seen only as a metarepresentational device is
both semantic and substantial. On the semantic level, the answer will depend on the field in
which ‘reasoning’ is used. In some areas of philosophy and psychology reasoning has
acquired a very broad meaning that is, in fact, much closer to the meaning of ‘inference’ than
to the common sense meaning of ‘reasoning’ as conscious ratiocination. This ‘reasoning’
clearly does not only refer to metarepresentational mechanisms. I will argue, however, that
within most dual-process theories at least part of what is usually called analytic or system 2
reasoning (and what is simply called reasoning here) is indeed a specific type of
metarepresentational device. This is a substantial claim, that there exists a specific mental
mechanism exerting a specific function in a specific manner—whether one wants to call it,
and only it, reasoning or not.
If one grants that being an argument—good or bad—is a property of representations, as
opposed to other things in the world, then any mechanism that tries to find and evaluate
arguments must be metarepresentational: it must construct representations of representations
in order to evaluate them as argumentsiii. So the question is: are the psychological
mechanisms described by psychologists of reasoning metarepresentational?
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Among the proponents of dual process theories, at least two argue directly, if in other words,
for a metarepresentational view of reasoning. Stanovich suggests that reasoning is (at least in
part) a device that allows us to create ‘representations of our own representations’ (Stanovich,
2004, p. 51). This, however, still leaves open the possibility that there may be other forms of
reasoning. Evans is clearer on the fundamental nature of this distinction. He is careful to
oppose his epistemic mental models—those underlying reasoning—to semantic mental
models—representations of the world (Evans, 2006, 2007). For Evans, epistemic mental
models are akin to epistemic attitudes (I am sure that X, I doubt that Y). Epistemic attitudes
are metarepresentational because they judge other representations: you can doubt ‘that there is
a chair’ (a representation) but you cannot doubt ‘a chair’ (a simple object).
Beyond these broad characterizations of reasoning, it may be more useful to look at specific
examples in order both to illustrate the difference between representational and
metarepresentational mechanisms, and to make a stronger point that reasoning is purely
metarepresentational. Non-metarepresentational processes can lead to inferences or behaviors
that are superficially similar to the ones performed by reasoning. Margo (or, for that matter,
her cat) knows that there is food in either one of two places. Upon visiting the first place and
finding it empty, she moves on to the second. Even thought this inference could be formalized
as a disjunctive syllogism, there is no need for reasoning proper: all that is needed is a
mechanism that stacks intentions and switches to the next one in line if the current one is not
fulfilled. On the other hand, Margo (but not her cat) is also able to solve a disjunctive
syllogism such as “there is food in location A or B; there is no food in A; therefore there is
food in B” through reasoning. In this case Margo explicitly uses the two premises as
arguments to draw the conclusion. She knows the reasons for drawing the conclusion, and it is
because she understands them that she draws the conclusion. Since the premises are
considered as arguments, or as reasons, they must have been metarepresented.
Even though, in this case, intuitions and reasoning can lead to similar outcomes, the two
processes are very different. In the case of reasoning, of the explicit consideration of reasons,
Margo can explain on the spot why she drew the conclusion, without having to try to retrace
his steps. When decisions or inferences are the result of other mechanisms, people are
generally only able to offer a rationalization in guise of explanation (Evans & Wason, 1976;
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Nisbett & Wilson, 1977; Wilson & Dunn, 2004). If Margo was under time pressure or
stressed her ability to perform intuitive inferences would likely be unchallenged but her
ability to reason may very well be impaired (see e.g., Markman, Maddox, & Worthy, 2006).
The distinction between intuitive inferences and reasoning may be clearest when we consider
premises that can be used as arguments or not. Margo and Simon, still arguing about how to
go to the opera, are coming out of their flat. Simon steps out just before Margo and says ‘it’s
windy.’ Upon hearing this, Margo can have two reactions (that are not mutually exclusive).
She can draw an intuitive inference from this new piece of information, inference that will
make her less likely to choose to walk, much in the same way as if she had experienced the
wind herself. In this case, once she has accepted the communicated information, and if she
does draw the inference, then she will accept its output. But Margo can also understand
Simon’s utterance as an argument in their ongoing conversation: as a reason not to walk. In
this case, she will represent the same proposition and evaluate its validity as an argument for
not walking. She may very well believe Simon but still decide that it is a bad argument
because it is very unlikely that the wind will be strong enough to make a difference. She can
perfectly well accept the truth of the utterance without accepting it as an argument. Moreover,
the opposite can also happen. Margo accepts Simon’s utterance as an argument. Then she
steps out and decides that there is so little wind that it does not even qualify as windy. At this
point she refuses Simon’s utterance: she does not think it is windy. But she can still think that,
had it really been windy, it would have been a good reason not to walk. This shows two
things. First, that reasoning is a distinct mechanism. It is possible to separate its effects from
that of other inferences, even in cases where the premises (‘it’s windy’) and the conclusion
(‘walking is not a good idea’) are similar. Second, that reasoning is metarepresentational.
What matters in evaluating ‘it’s windy’ as an argument is not its relation to the world—
whether it is, in fact, windy or not windy. What matters is the relation between ‘it’s windy’
and the conclusion ‘we should not walk.’ And such relationships between representations
have to be evaluated by metarepresentational mechanisms, in the same way as relationships
between things in the world have to be evaluated by representational mechanisms.
Seriality
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Even if one grants that reasoning is metarepresentational, it does not follow that it should
work as a mechanism that relies in great part on serial evaluation. In the case of visual search,
some searches rely on highly parallel processes. When searching for a tennis ball in the
cutlery drawer, the properties of many different elements are evaluated in parallel, allowing
you to focus directly on the tennis ball. One could imagine a metarepresentational process that
would function in a similar manner. Parallel search is made possible, however, by the fact that
we have a category for the target of the search (the tennis ball) and a category for the other
objects (the cutlery). In the case of arguments, we have neither: we generally do not know
what a good argument will be, and the representations that are not good arguments do not
belong to a single category (they may all be bad arguments for different reasons). In a latter
section some stable categories reasoning can rely upon are discussed, and it is only to the
extent that these categories are used that reasoning can work in a parallel manner. Otherwise
parallel processes are ill-suited to the task. Instead, reasoning should proceed mostly in a
serial fashion: considering one representation at a time until one that fits with some criteria of
being a good argument is found.
Several psychologists have claimed that reasoning can only focus on one item at a time.
Legrenzi and his colleagues have described several errors that may result from such a
phenomenon, known as ‘focusing’ (Legrenzi, Girotto, & Johnson-Laird, 1993). But it is
Evans who has made the most convincing claim for the seriality of reasoning, when defending
his singularity principle. According to the singularity principle, ‘when we think hypothetically
[i.e. when we reason] we only consider one possibility or mental model at a time’ (Evans,
2007, p.17). Evans gathers several pieces of evidence in support of his claim that I will
quickly summarize here. First he reviews work on hypothesis testing showing that people
consider only one hypothesis at any given time (Mynatt, Doherty, & Dragan, 1993, see also
Shaklee & Fischhoff, 1982). He also cites classical work on inductive reasoning that has come
to the same conclusion (in particular Bruner, Goodnow, & Austin, 1956, who speak of an
‘abhorrence of disjunctiveness’ (p.160, see also Levine, 1966). If people can only consider
one possibility at a time, they should have trouble with tasks that require the concurrent
representation of two possibilities. And indeed performance plummets when problems involve
exclusive disjunction (‘A or else B’), as illustrated by the famous THOG problem (Wason &
Brooks, 1979). More recently Johnson-Laird and his colleagues have created problems
involving ‘or else’ that can mislead more than 90% of participants (Johnson-Laird, Legrenzi,
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Girotto, & Legrenzi, 2000). Studies of everyday decision making come to the same
conclusion: people only consider one option at a time when reasoning about a problem (see
e.g., Klein, 1998). While this evidence does not rule out the possibility of parallel processes
working in a manner that would be hard to assess experimentally, it shows that serial
processes play a considerable role in reasoning.
Relevance
If the type of search that has been advocated above is necessary, it is because the objects
among which the search is conducted do not present themselves in the right order. If it were
the case, there would be no need for a serial search mechanism: picking the first answer
would be enough. When we search for an unusual object, such as something to drive a nail
instead of a hammer, a good solution is not going to pop out of the visual scene. Instead,
solutions are going to present themselves in an order determined by some partly irrelevant
criteria. The same goes for arguments. In this case as well the order in which representations
are be evaluated is determined by factors that are partly irrelevant to the issue at hand. Which
representations are considered depends on their relative accessibility in the context of the
search. For instance, Simon’s beliefs about walking, about the Tube, and about Margo will be
more salient, more easily accessible. This is both a blessing—an insufficient one but a
blessing nonetheless—and a curse. This is a blessing because there is a very high probability
that good arguments will be found among such beliefs, much more than among, say, beliefs
about the foreign policy of Guatemalaiv. It is an insufficient blessing because most of these
beliefs are nevertheless bad arguments (or not arguments at all). And it can also turn into a—
very mild—curse in that it will make it very improbable that a good argument that lies beyond
these easily accessible beliefs will be considered.
Whatever its supposed advantages or drawbacks may be, what evidence is there that such
considerations of accessibility actually guide the search? Once again, we can turn to Evans
who has suggested that reasoning is guided by a relevance principle (Evans, 2006, 2007).
According to this principle, ‘mental models are generated by heuristic or pragmatic processes
that are designed to maximize relevance in a particular context, given the current goals of the
reasoner’ (Evans, 2007, p.18). What is important to understand here is that relevance is not
only determined by the problem that reasoning has to solve but by other factors such as prior
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beliefs, goals, and context. There are two ways to demonstrate this. The first is by showing
that the order in which beliefs are considered is not solely determined by their value for the
problem at hand. The other is by showing that this order is not random but can be explained
by the considerations of other factors.
The first point can be easily deduced from the fact that people’s ‘logical performance in
abstract reasoning tasks is generally quite poor’ (Evans, 2002, p. 981). If participants faced
with reasoning tasks were able to focus on the most relevant arguments for the task at hand,
they would solve them all effortlessly. The tasks used—conditional inferences, syllogisms and
the like—are computationally trivial; one might say that the solution is right under the
participant’s eyes. For instance, in the famous Wason selection task (Wason, 1966), all the
possible answers are easily accessible. What are not easily accessible are good reasons for the
good answers. Moreover, participants who failed at the task can be convinced that there was a
better answer (i.e. an answer supported by better arguments, see Maciejovsky & Budescu,
2007; Moshman & Geil, 1998). So it is not as if participants were unable to understand that
there are better arguments, it is simply that they do not consider them spontaneously.
Given that the order in which representations are considered is not simply determined by their
relevance for the task at hand, by what is it determined? A host of well known cognitive
factors will play a role. They go by different names and may refer to different psychological
mechanisms: availability, anchoring, salience, accessibility, framing, relevance, etc. The
heuristic and biases program has investigated several of these phenomena and showed how
the ease with which a solution is brought to mind has an important effect on the final answer,
even in cases in which the influence is wholly unwarranted (Gilovich, Griffin, & Kahneman,
2002; Kahneman, Slovic, & Tversky, 1982). In an oft-cited experiment, participants were
given a random number from 1 to 100 (the anchor) and this influenced their later answer to
the question ‘how many countries are there in Africa?’ (Tversky & Kahneman, 1974).
Mussweiler and his colleagues have convincingly argued that this effect is mediated by an
increase in the accessibility of anchor consistent knowledge: participants will think first of
arguments that are consistent with the anchor (Mussweiler & Strack, 1999a, 1999b;
Mussweiler, Strack, & Pfeiffer, 2000). Likewise, the framing of problems affects choices
through ‘the generation of arguments for available choice alternatives’ (Milch, Weber,
Appelt, Handgraaf, & Krantz, 2009, p. 244, see Shafir, Simonson, & Tversky, 1993). The
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most precise formulation of these diverse influences can be found in relevance theory, as
formulated by Sperber and Wilson (Sperber & Wilson, 1995). Several experiments have
demonstrated that considerations of relevance determine what conclusion is going to be
considered most spontaneously when faced with a reasoning problem (Sperber, Cara, &
Girotto, 1995; Van der Henst, 2006; Van der Henst, Sperber, & Politzer, 2002). It is plausible
to think that the theory could account as well for the order in which arguments are then
considered.
There is ample evidence that the order in which arguments are considered is not driven
exclusively by their relevance for the task at hand. However, even if the order in which
reasoning considers different arguments is not optimal, the evaluation procedure could still be
so demanding that it ends up finding the best arguments. Some of the evidence we have
reviewed—the poor performances in reasoning tasks for instance—argue against this
possibility and the next section will explain why a mechanism that has to find arguments
should not be expected to look for the best ones.
Satisficing
Since the notion of satisficing was introduced by Simon (1982), it has become nearly a truism
that psychological mechanisms satisfice, that they do not behave in line with standards
models of optimization. This is only to be expected if one takes costs into account. Given that
oftentimes more precise calculations would be much more costly while yielding little
improvement, it makes sense to use heuristics instead—in some sense, it becomes optimal to
use heuristics (see e.g., Gigerenzer, Todd, & ABC Research Group, 1999). Claiming that
reasoning satisfices would not be terribly interesting, as all cognitive mechanisms are bound
to satisfice to some extent. My claim here is stronger: that reasoning satisfices much more
than most psychological mechanism.
When looking for arguments, there are two reasons for wanting to find a decent enough
argument. The first is that there is always a risk of looking foolish by uttering something
idiotic. But this risk does not apply only to arguments, it applies to anything one might say.
Therefore, it is probably dealt with by other control mechanisms linked with communication
more generally and can safely be ignored here. The second reason to find decent arguments is,
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obviously, so that we can convince our interlocutor. What is remarkable about this task is that
failing to find a convincing argument is as close as possible to a free error. First because it is
generally possible to try again: if our first argument fails to carry the day, we can suggest
another, and then another again, etc. There is no pressure to start by the best argument. This is
very different from most other situations; often a decision will entail a fork: if you think that
taking a given road will be faster, or that courting a given person is better, by shifting to
another solution you will generally incur a cost, sometimes a very important one. Not only is
failing to find the best argument first not a problem, but failing to convince at all is also often
not a big issue. Argumentation is typically used to gain something extra. Only very rarely will
it be a question of life or death, or even of important costs. Again, this is quite different from
many other psychological mechanisms for which failure is extremely costly, with a predator
recognition mechanism being a somewhat extreme example.
So, if reasoning is indeed a device designed to find arguments, it should be satisfied with
arguments that, far from being the best, are just good enough that they might have a chance to
work. In one sense, the whole of the psychology of reasoning bears testimony to the fact that
reasoning satisfices. If reasoning worked until it found the best possible argument, then it
would provide the correct answer for most reasoning problems, something that it clearly does
not do. Studying informal reasoning, Perkins comes to a similar conclusion: ‘many reasoners
could be characterized as "makes sense epistemologists." Such reasoners proceed to analyze a
situation only to the point where the analysis makes superficial sense.’ (Perkins, 1985, p.568).
Likewise, for Nisbett and Ross ‘the lay scientist seems to search only until a plausible
antecedent is discovered’ (Nisbett & Ross, 1980, p. 119, see also Rozenblit & Keil, 2002).
Analogical reasoning follows the same pattern: in standard tasks people are mostly guided by
superficial features (e.g., Gentner, Rattermann, & Forbus, 1993).
Such results, particularly those dealing with informal reasoning, may seem to undermine the
earlier claim that people are good at arguing, but the tension is only superficial. On the one
hand, being satisfied by relatively weak arguments when the context does not call for sounder
arguments is what one should expect once costs are taken into account. This is part of the
good overall organization of our cognitive systems that we only devote extra effort when
extra effects are expected (Sperber & Wilson, 1995). On the other hand, this ‘adaptive
laziness’ does not preclude people both from evaluating arguments accurately and from being
Looking for arguments
17
able to find better arguments when the need arises. A good illustration of this is the use made
of explanations (make sense causal theories) and evidence (data) by arguers. In a study of
informal reasoning, Kuhn asked participants to take a stance and defend their views on a
variety of topics (Kuhn, 1991). One of the ‘flaws’ that she observed was a lack of preference
for evidence over explanations: people were much more likely to be satisfied with a
superficial explanation than to resort to hard data. In the present framework, this should be
expected given that participants were not faced with a debating partner, but with an ‘inert’
experimentalist who would not contest their claims. People who had to engage in real debates
showed a marked improvement in the quality of their arguments—presumably because their
weakest arguments were refuted and they had to make the effort to find better ones (Kuhn,
Shaw, & Felton, 1997). Moreover, when people were offered easy access to evidence they
quickly realized that it would make for better arguments; they were also more likely to be
convinced by arguments relying on evidence than explanation (Brem & Rips, 2000). Children
are also able to provide better arguments, or warrants and backings for their arguments when
pressed by teachers or experimenters (Anderson, Chinn, Chang, Waggoner, & Yi, 1997;
Anderson et al., 1997; Anderson, Chinn, Waggoner, & Nguyen, 1998; Webb et al., 2008).
The picture that has been painted of reasoning so far fits perfectly with what is required of a
mechanism that has to find arguments. It is metarepresentational; it evaluates potential
arguments one by one, in an order that is driven by general considerations of relevance; and it
is satisfied by weak arguments if they are not contested. The next feature to be explored is
particularly interesting because, if it is expected of a mechanism that has to look for
arguments, it would be deeply maladaptive for other kinds of mechanism.
The confirmation Bias
When Margo wants to convince Simon to walk to the opera, she is only interested in
arguments that will support her point of view or that will undermine Simon’s. More generally,
a mechanism that looks for arguments should have a very strong confirmation bias: it should
only try to find arguments that will support the individual’s conclusion. There is a huge
literature in psychology—from reasoning to decision making through social psychology—
claiming that people suffer from such a bias (see Nickerson, 1998, for review). In many cases,
however, these results can be accounted for by the use of a ‘positive testing strategy,’ based
Looking for arguments
18
on the assumption that one’s original hypotheses are not too far off the mark (Klayman & Ha,
1987). Given that using such a strategy is the rational thing to do in most situations, it hardly
deserves to be called a ‘bias.’ More importantly, it is also misleading to call it a
‘confirmation’ or ‘confirmatory’ bias since its goal is not to confirm one’s initial ideas. Such a
strategy can sometimes lead to undue confirmation of our ideas, but only as a side-effect of its
overall search for accuracy. Many phenomena that were once explained as instances of a
confirmation bias are now explained as the results of other mechanisms that are not
confirmatory in nature (Evans, 1998; Klayman, 1995). But these mechanisms are intuitive. It
is only by turning to reasoning that one can find evidence of a genuine confirmation biasv.
Maybe the best example is that of the Wason selection task. This is a simple reasoning task
that involves a conditional rule and requires that participants understand how to falsify the
rule in order to succeed. At first, it was thought that participants had an intuitive tendency to
confirm the rule instead of falsifying it (Wason, 1966). Later research has shown, however,
that the answers are better explained by positing a two stages process. First, intuitions related
to utterance comprehension will guide the participants’ attention towards a given answer. In
the standard task, this answer will confirm the rule, but slight changes in the task will lead
these intuitions towards an answer that falsifies the rule (Evans & Lynch, 1973; Girotto,
Kemmelmeier, Sperber, & Van der Henst, 2001; Sperber et al., 1995). This means that these
intuitions do not aim either at confirming or at falsifying the rule. After this initial stage
reasoning kicks in and, in the vast majority of the cases, it only looks for justifications
supporting participants’ initial intuitions (Evans, 1996; Lucas & Ball, 2005; Roberts &
Newton, 2002). Here is a genuine confirmation bias. Reasoning is not trying to produce the
best answer; instead finding confirmatory arguments is its very goal. And the case of the
Wason selection task is not an exception: ‘[The] confirmation bias is perhaps the best known
and most widely accepted notion of inferential error to come out of the literature on human
reasoning’ (Evans, 1989, p. 41).
It is important to stress that the confirmation bias does not stem from an inability to grasp
falsification. Participants are perfectly able to use diverse and sophisticated strategies in order
to falsify something they disagree with. Coming back to the Wason selection task, when
participants are motivated to prove that the rule is false, they become much more apt at
finding the answer that does exactly that (Dawson, Gilovich, & Regan, 2002). Likewise, when
Looking for arguments
19
an hypothesis is given by someone else and we have reasons to doubt its validity, falsification
comes much more easily (Butera, Legrenzi, Mugny, & Pérez, 1992; Cowley & Byrne, 2005).
And when a syllogism has a conclusion that contradicts our beliefs we look for sophisticated
arguments to justify its rejection (Klauer, Musch, & Naumer, 2000). In all these cases,
falsifying strategies are only used to confirm our initial hunch that a proposition is false.
That reasoning displays a prevalent and robust confirmation bias would be hard to contest.
This is quite striking, especially since it can lead to rather poor outcomes when reasoning is
used in the wrong contexts (see Mercier & Sperber, in press). If reasoning was supposed to
help us improve our epistemic status or help us make better decisions, then the existence of
such a bias would be a deep mystery. On the other hand, it is an expected feature for a
mechanism designed to find arguments.
Categories of arguments
Rhetoricians have developed elaborate classifications of arguments—ad hominem argument,
argument by analogy, argument by examples, etc. Moreover, we know that categories are
extremely useful in facilitating other kinds of searches, such as visual search. Thus, one would
think that these categories could be used to find arguments. But it is not clear that naïve
people can rely on such categories while looking for arguments. In fact, these categories are
partly orthogonal to the problem at hand, which is to find a good argument, whatever kind of
argument it may be. When you want to find a good restaurant, and if you have ecumenical
tastes, then the categories ‘Japanese restaurant,’ ‘Italian restaurant’ or ‘French restaurant’ are
rather irrelevant. What you are looking for is a category ‘good restaurant.’ The analogy is
limited because in the case of restaurants, it would be possible to create a category ‘good
restaurants,’ but this is generally not possible in the case of argumentsvi. Depending on the
present topic, the context, the interlocutor, etc., any given representation can be a good or a
bad argument (or not an argument at all). Still, sometimes you will not have had the time to
form a category ‘good restaurants’—you are in a new city, say. In this case, the analogy with
the restaurants can provide us with a useful clue. For instance, there may be an area in this
city that is likely to have several such restaurants, and you might just decide to stroll around
these streets until you find a place that satisfies your requirements. This is possible because
Looking for arguments
20
cities are organized in a manner that will make your search easier. Are our minds organized in
the same helpful way?
By ranking possible arguments in a manner that is, if insufficient, at least extremely helpful,
relevance makes it at least possible to find arguments. This is the first manner in which the
organization of the mind helps us find arguments. But this ranking is agnostic regarding other
important properties that a representation has to have to be a good argument. For instance, a
proposition may have equally relevant consequences that have a positive and a negative
valence. But the former will be a good argument to support the proposition and the latter will
not. This pattern holds generally: positive consequences of one’s proposition, as well as
negative consequences of one’s interlocutor’s proposition, often make good arguments, while
the converses don’t. So if our minds are organized in such a way that negative and positive
consequences are somehow compartmentalized, then we could rely on this
compartmentalization for a more efficient search. Much like we can choose to only look for
restaurants in a given area, maybe we can choose to focus on positive or negative
consequences. At least that would save us the trouble of looking at representations that will
only very rarely turn out to be good arguments. It may be possible to direct the search in other
ways. Instead of consequences, one could focus on antecedents—representations from which
we can draw inferences leading to the conclusion—in which case restricting the search to the
antecedents of one’s own position will be a good idea. The converse would be to look for
representations that are incoherent with our interlocutor’s position. Or we may look for
representations that have a similar relationship with one another as one premise and the
conclusion we want to convey, creating an argument by analogy. So it is possible that the
search for arguments can be oriented in a given direction.
All of these suggestions make assumptions about the structure of the mind that are not trivial,
and there is a dearth of empirical work examining this question of categories of arguments.
Moreover, the theory presented here does not have to make precise predictions regarding what
strategies, or categories, can be used when looking for arguments, so I will not belabor the
point any further.
***
Looking for arguments
21
Starting from the description of a computational problem, it is possible to develop hypotheses
regarding the kind of mechanism that would be best able to solve it. The problem that has
been tackled here is that of finding arguments. In this case, I have argued that one should
expect a metarepresentational mechanism, so that it can evaluate representations as
arguments. This mechanism that works in a serial manner, examining each possible argument
in turn. The need to examine several arguments arises partly from the fact that representations
are ordered following general considerations of relevance, and not only their relevance as
arguments. Moreover, such a mechanism should satisfice and it should have a confirmation
bias. Evidence has been presented showing that reasoning, as investigated in the psychology
of reasoning and decision making, fits very well with these requirements. This fit is taken as
further evidence in favor of the argumentative theory of reasoning, according to which
reasoning evolved precisely to fulfill an argumentative function. The last two properties—an
extremely high degree of satisficing and a very strong confirmation bias—are particularly
striking in that they are not expected of a psychological mechanism that would have another
function.
Given that the question of finding arguments has not been thoroughly explored in the
psychological literature, the model suggested here has to be considered as a tentative first
step. Hopefully, it will lead to more elaborate suggestions and stimulate empirical research on
this topic.
Looking for arguments
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i The Psychology of Proof (Rips, 1994) for mental logic theory, How we Reason (Johnson-Laird, 2006) for mental models theory and Hypothetical Thinking (Evans, 2007) for (one) dual process theory. It should be said however that Rips has devoted a lot of work to argumentation aside from his theories of reasoning. ii A similar idea is expressed by Perelman and Olbrechts-Tyteca in their classic study of argumentation: ‘One datum in argumentation consists of the agreements available to the speaker as supports for his argument. But this element is so large and capable of being used in so many different ways, that the manner in which one makes use of it is of paramount importance. Accordingly, before examining the use of this datum in argumentation, it is essential that we say something of the part played by preliminary selection of the elements that are to serve as the starting point of the argument and by the adaptation of these elements to its purpose’ (Perelman & Olbrechts-Tyteca, 1969, p.115).
iii See Sperber (2000). This point does not garner unanimity (Dancy, 2000) but is consensual enough to warrant accepting it, at least provisionally, here.
iv Accessibility, or relevance, will be particularly effective at organizing the space of possible arguments after someone has already given an argument. In this case, relevance mechanisms may triangulate quite effectively on counter-arguments. For instance, if Margo says ‘walking will be fast’, one of the first things that may spring to Simon’s mind is ‘but taking the Tube will be even faster,’ precluding the need for an extensive search.
v This argument is developed in Mercier & Sperber (in press) so it will only be brushed here.
vi The exception would be arguments that are made very often in similar contexts and for similar audiences. In this case, it should be possible to have an idea of what a good argument may be. A teacher may think, for instance, that arguments by analogy are particularly efficient in explaining a certain class of concepts.