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CHAPTER 25

Adaptations for Reasoning About

Social Exchange

LEDA COSMIDES and JOHN TOOBY

If a person doesn’t give something to me, I won’t give anything to that person. If I’m

sitting eating, and someone like that comes by, I say, “Uhn, uhn. I’m not going to give

any of this to you. When you have food, the things you do with it make me unhappy.

If you even once in a while gave me something nice, I would surely give some of this

to you.”

Nisa from Nisa: The Life and Words of a !Kung Woman, Shostak, 1981, p. 89

Instead of keeping things, [!Kung] use them as gifts to express generosity and friendly

intent, and to put people under obligation to make return tokens of friendship ....In

reciprocating, one does not give the same object back again but something of

comparable value.

Eland fat is a very highly valued gift . . . . Toma said that when he had eland fat to give,

he took shrewd note of certain objects he might like to have and gave their owners

especially generous gifts of fat.

Marshall, 1976, pp. 366–369

ISA AND TOMA were hunter-gatherers, !Kung San people living in Botswana’s

inhospitable Kalahari desert during the 1960s. Their way of life was as

different from that in an industrialized, economically developed society as

any on earth, yet their sentiments are as familiar and easy to comprehend as those of

your neighbor next door. They involve social exchange, interactions in which one party

provides a beneﬁt to the other conditional on the recipient’s providing a beneﬁtin

return (Cosmides, 1985; Cosmides & Tooby, 1989; Tooby & Cosmides, 1996). Among

humans, social exchange can be implicit or explicit, simultaneous or sequential,

immediate or deferred, and may involve alternating actions by the two parties or

follow more complex structures. In all these cases, however, it is a way people

cooperate for mutual beneﬁt. Explicitly agreed-to forms of social exchange are the

focus of study in economics (and are known as exchange or trade), while biologists

625

Cosmides, L. & Tooby, J. (2015). Adaptations for reasoning

about social exchange. In Buss, D. M. (Ed.), The Handbook of

Evolutionary Psychology, Second edition. Volume 2:

Integrations. (pp. 625-668). Hoboken, NJ: John Wiley & Sons.

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and anthro pologists focus more on implicit, deferred cases of exchange, often called

reciprocal altruism (Trivers, 1971), reciprocity, or reciprocation. We will refer to the

inclusive set of cases of the mutually conditioned provisioning of beneﬁts as social

exchange, regardless of subtyp e. Nisa and Toma are musing about social exchange

interactions in which the expectation of reciprocity is implicit and the favor can be

returned at a much later date. In their society, as in ours, the beneﬁts given and

received need not be physical objects for exchange to exist; they can be services (valued

actions) as well. Aid in a ﬁght, support in a political conﬂict, help with a sick child,

permission to hunt and use water holes in your family’s territory—all are ways of

doing or repaying a favor. Social exchange behavior is both panhuman and ancient.

What cognitive abilities make it possible?

For 25 years, we have been investigating the hypothesis that the enduring presence

of social exchange interactions among our ancestors has selected for cognitive

mechanisms that are specialized for reasoning about social exchange. Just as a lock

and key are designed to ﬁt together to function, our claim is that the proprietary

procedures and conceptual elements of the social exchange reasoning specializations

evolved to reﬂect the abstract, evolutionarily recurring relationships present in social

exchange interactions (Cosmides & Tooby, 1989).

We picked social exchange reasoning as an initial test case for exploring the

empirical power of evolutionary psychological analyses for a number of reasons.

First, the topic is intrinsically important: Exchange is central to all human economic

activity. If exchange in our species is made possible by evol ved, neurocomputational

programs specialized for exchange itself, this is surely worth knowing. Such evolved

programs would constitute the foundation of economic behavior, and their speciﬁc

properties would organize exchange interactions in all human societies; thus,

if they exist, they deserve to be mapped. The discovery and mapping of such

mechanisms would ground economics in the evolutionary and cognitive sciences,

cross-connecting economics to the rest of the natural sciences. Social exchange

specializations (if they exist) also underlie many aspects of a far broader category

of implicit social interaction lying outside economics, involving favors, friendship, and

self-organizing cooperation.

There was a second reason for investigating the computational procedures engaged

by social exchange. There are many counterhypotheses about social exchange reason-

ing to test against, but they all spring from the single most central assumption of the

traditional social and behavioral sciences—the blank slate view of the min d that lies at

the center of what we have called the standard social science model (Tooby & Co smides,

1992). On this view, humans are endowed with a powerful, general cognitive capacity

(intelligence, rationality, learning, instrumental reasoning), which explains human

thought and the great majority of human behavior. In this case, humans putatively

engage in successful social exchange through exactly the same cognitive faculties that

allow them to do everything else: Their general intelligence allows them to recognize,

learn, or reason out intelligent, beneﬁcial courses of action. This hypothesis has been

central to how most neural, psychological, and social scientists conceptualize human

behavior, but it is almost never subjected to potential empi rical falsiﬁcation (unlike

theories central to physics or biology). Investigating reasoning about social exchange

provided an opportunity to test the blan k slate hypothesis empirically in domains

(economics and social behavior) where it had been uncritically accep ted by almost all

traditional researchers. Moreover, the results of these tests would be powerfully telling

for the general issue of whether an evolutionary psychological program would lead to

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far-reaching and fundamental revisions across the human sciences. Why ? If mecha-

nisms of general rationality exist and are to genuinely explain anything of signiﬁcance,

they should surely explain social exchange reasoning as one easy appl ication. After all,

social exchange is absurdly simple compared to other cognitive activities such as

language or vision, it is mutually beneﬁcial and intrinsically rewardi ng, it is economi-

cally rational (Simon, 1990), and it should emerge spontaneously as the result of the

ability to pursue goals; even artiﬁcially intelligent agents capable of pursuing goals

through means-ends analysis should be able to manage it. An organi sm that was in

fact equipped with a powerful, general intelligence would not need cognitive special-

izations for social exchange to be able to engage in it. If it turns out that humans

nonetheless have adaptive specializations for social exchange, it would imply that

mechanisms of general intelligence (if they exist) are relatively weak, and natural

selection has specialized a far larger number of comparable cognitive competences

than cognitive and behavioral scientists had anticipated.

Third, we chose to study a form of reasoning because reasoning is widely considered

to be the quintessential case of a content-independent, general-purpose cognitive

competence. Reasoning is also considered to be the most distinctively human cognitive

ability—something that exists in opposition to, and as a replacement for, instinct.

If, against all expectation, human reasoning turns out to fractionate into a diverse

collection of evolved, content-specialized procedures, then adaptive specializations

are far more likely to be widespread and typical in the human psychological architec-

ture, rather than nonexistent or exceptional. Reasoning presents the most difﬁcult test

case, and hence the most useful case to leapfrog the evolutionary debate into genuinely

new territory. In contrast, the eventual outcome of debates over the evolutionary origins

and organization of motivation (e.g., sexual desire) and emotion (e.g., fear) are not in

doubt (despite the persistence of intensely fought rearguard actions by traditional

research communities). No blank slate process could, even in principle, acquire the

motivational and emotional organization found in humans (Cosmides & Tooby, 1987;

Tooby, Cosmides, & Barrett, 2005). Reasoning will be the last redoubt of those who

adhere to a blank slate approach to the human psychological architecture.

Fourth, logical rea soning is subject to precise formal computational analysis, so it is

possible to derive exact and contrasting predictions from domain-general and

domain-speciﬁc theories , allowing critica l tests to be devised and theories to be

potentially or actually falsiﬁed.

Finally, we chose the domain of social exchange because it offered the opportunity

to explore whether the evolutionary dynamics newly charted by evolutionary game

theory (e.g., Maynard Smith, 1982) had sculpted the human brain and mind and,

indeed, human moral reasoning. If it could be sh own empirically that the kinds of

selection pressures modeled in evolutionary game theory had real consequences on

the human psychological architecture, then this would help lay the foundations of

an evolutionary approach to social psychology, social behavior, and morality

(Cosmides & Tooby, 2004). At the time, most social scientists considered morality

to be a cultural product free of biological organization. We thought on theoretical

grounds there should be an evolved set of domain-speciﬁc grammars of moral and

social reasoning (Cosmides & Tooby, 1989) and wanted to see if we could clearly

establish at least one rich empirical example—a grammar of social exchange.

One pleasing feature of the case of social exchange is that it can be clearly traced

step by step as a causal chain from replicator dynamics and game theory to details of

the computational architecture to speciﬁc patterns of reasoning performance to

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speciﬁc cultural phenomena, moral intuitions, and conceptual primitives in moral

philosophy—showcasing the broad integrative power of an evolutionary psychologi-

cal approach. This research is one component of a larger project that includes mapping

the evolutionary psychology of moral sentiments and moral emotions alongside moral

reasoning (e.g., Cosmides & Tooby, 2004; Lieberman, Tooby, & Cosmides, 2003, 2007;

Price, Cosmides, & Tooby, 2002; Tooby & Cosmides, 2010).

What follows are some of the high points of this 25-year research program. We argue

that social exchangeis ubiquitously woven through the fabric of human life in all human

cultures everywhere, and has been taking place among our ancestors for millions and

possibly tens of millions of years. This means social exchange interactions are an

important and recurrent human activity with sufﬁcient time depth to have selected

for specialized neural adaptations. Evolutionary game theory shows that social

exchange can evolve and persist only if the cognitive programs that cause it conform

to a narrow and complex set of design speciﬁcations. The complex pattern of functional

and neural dissociations that we discovered reveal so close a ﬁt between adaptive

problem and computational solution that a neurocognitive specialization for reasoning

about social exchange is implicated, including a subroutine for detecting cheaters. This

subroutine develops precocially (by ages 3 to 4) and appears cross-culturally—hunter-

horticulturalistsinthe Amazon detect cheaters as reliably as adults who live in advanced

market economies. The detailed patterns of human reasoning performance elicited

by situations involving social exchange correspond to the evolutionarily derived

predictions of a specialized logic or grammar of social exchange and falsify content-

independent, general-purpose reasoning mechanisms as a plausible explanation for

reasoning in this domain. A developmental process that is itself specialized for social

exchangeappears to be responsible for building the neurocognitive specialization found

in adults: As we show, the design, ontogenetic timetable, and cross-cultural distribution

of social exchange are not consistent with any known domain-general learning process.

Taken together, the data showing design speciﬁcity, precocious development, cross-

cultural universality, and neural dissociability implicate the existence of an evolved,

species-typical neurocomputational specialization.

In short, the neurocognitive system that causes reasoning about social exchange

shows evidence of being what Pinker (1994) has called a cognitive instinct: It is complexly

organized for solving a well-deﬁned adaptive problem our ancestors faced in the past, it

reliably develops in all normal humans, it develops without any conscious effort and in

the absence of explicit instruction, it is applied without any conscious awareness of its

underlying logic, and it is functionally and neurally distinct from more general abilities

to process information or behave intelligently. We brieﬂy review the evidence that

supports this conclusion, along with the evidence that eliminates the alternative

by-product hypotheses that have been proposed. (For more comprehensive treatments,

see Cosmides, 1985, 1989; Cosmides, Barrett, & Tooby, 2010; Cosmides & Tooby, 1989,

1992, 2005, 2008a; Fiddick, Cosmides, & Tooby, 2000; Stone, Cosmides, Tooby, Kroll, &

Knight, 2002; Sugiyama, Tooby, & Cosmides, 2002.)

SOCIAL EXCHANGE IN ZOOLOGICAL AND CULTURAL

PERSPECTIVE

Living in daily contact affords many opportunities to see when someone needs help,

to monitor when someone fails to help but could have, and, as Nisa explains, to

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withdraw future help when this happens. Under these conditio ns, reciprocity can be

delayed, understanding of obligations and entitlements can remain tacit, and aid

(in addition to objects) can be given and received (Shostak, 1981). But when

people do not live s ide by side, social exchange arrangements typically involve

explicit agreements, simultaneous transfers of bene ﬁts, and increased trade of

objects (rather than intimate acts of aid). Agreements are explicit because neither

side can know the other’s needs based on daily interaction, objects are traded

because neither side is present to provide aid when the opp ortunity arises, and

trade s are simultaneous because this reduces the risk of nonreciprocation—neither

side needs to trust the other to provide help in the future. Accordingly, explicit

or simultaneous trade is usually a sign of social distance (Tooby & Cosmides, 1996).

!Kung, for example, will trade hides for knives and other goods with Bantu people

but not with fellow band members (Marshall, 1976).

Explicit trades and delayed, implicit reciprocation differ in these superﬁcial ways,

but they share a deep structure: X provides a beneﬁttoY conditional on Y doing

something that X wants. As humans, we take it for granted that people can make each

other better off than they were before by exchanging beneﬁts— goods, services, acts of

help and kindness. But when placed in zoological perspective, social exchange stands

out as an unusual phenomenon whose existence requires explanation. The magnitude,

variety, and complexity of our social exchange relations are among the most distinc-

tive features of human social life and differentiate us strongly from all other animal

species (Tooby & DeVore, 1987). Indeed, uncontroversial examples of social exchange

in other species are difﬁcult to ﬁnd, and despite widespread investigation, social

exchange has been reported in only a tiny handful of other species, such as chimpan-

zees, certain monkeys, and vampire bats (see Dugatkin, 1997; Hauser, 2007, for

contrasting views of the nonhuman ﬁndings).

Practices can be widespread without being the speciﬁc product of evolved psy-

chological adaptations. Is social exchange a recent cultural invention? Cultural

inventions such as alphabetic writing systems, cereal cultivation, and Arabic numerals

are widespread, but they have one or a few points of origin, spread by contact, and are

highly elaborated in some cultures and absent in others. Social exchange does not ﬁt

this pattern. It is found in every documented culture past and present and is a feature

of virtually every human life within each culture, taking on a multiplicity of elaborate

forms, such as returning favors, sharing food, reciprocal gift giving, explicit trade, and

extending acts of help with the implicit expectation that they will be reciprocated

(Cashdan, 1989; Fiske, 1991; Gurven, 2004; Malinowski, 1922; Mauss, 1925/1967).

Particular methods or institutions for engaging in exchange—marketplaces, stock

exchanges, money, the Kula Ring—are recent cultural inventions, but not social

exchange behavior itself.

Moreover, evidence supports the view that social exchange is at least as old as the

genus Homo and possibly far older than that. Paleoanthropological evidence indi-

cates that before anatomically modern humans evolved, hominids engaged in social

exchange (see, e.g., Isaac, 1978). Moreover, the presence of reciprocity in chimpan-

zees (and even certain monkeys; Brosnan & de Waal, 2003; de Waal, 1989, 1997a,

1997b; de Waal & Luttrell, 1988) suggests it may predate the time, 5 to 7 million

years ago, when the hominid line split from chimpanzees. In short, social exchange

behavior has been present during the evolutionary history of our line for so long that

selection could well have engineered complex cognitive mechanisms specialized for

engaging in it.

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Natural selection retains and discards properties from a species’ design based on

how well these properties solve adaptive problems—evolutionarily recurrent prob-

lems whose solution promotes reproduction. To have been a targe t of selection, a

design had to produc e beneﬁcial effects, measured in reproductive terms, in the

environments in which it evolved. Social exchange clearly produced beneﬁcial effects

for those who successfully engaged in it, ancestrally as well as now (Cashdan, 1989;

Isaac, 1978). A life deprived of the beneﬁts that reciprocal cooperation provides would

be a Hobbesian nightmare of poverty and social isolation, punctuated by conﬂict. But

the fact that social exchange produces beneﬁcial effects is not sufﬁcient for showing

that the neurocognitive system that enables it was designed by natural selection for

that function. To rule out the counterhypothesis that social exchange is a side effect of

a system that was designed to solve a different or more inclusive set of adaptive

problems, we need to evaluate whether the adaptation shows evidence of special

design for the proposed function (William s, 1966).

So what, exactly, is the nature of the neurocognitive machinery that enables

exchange, and how specialized is it for this function? Social exchange is zoologically

rare, raising the possibility that natural selection engineered into the human brain

information processing circuits that are narrowly specialized for understanding,

reasoning about, motivating, and engaging in social exchange. On this view, the

circuits involved are neurocognitive adaptations for social exchange, evolved cog-

nitive instincts designed by natural selection for that fu nction—the adaptive special-

ization hypothesis. An alternative family of theories derives from the possibility that

our ability to reason about and engage in social exchange is a by-product of a

neurocognitive system that evolved for a different function. This could be an

alternative speciﬁc function (e.g., reasoning about obligations). More usually,

however, researchers expect that social exchange reasoning is a by-product or

expression of a neurocognitive system that evolved to perform a more general

function—operant conditioning, logical reasoning, rational decision making, or

some sort of general intelligence. We call this family of explanations the general

rationality hypothesis.

The general rationality hypothesis is so compelling, so self-evident, and so

entrenched in our scientiﬁc cul ture that researchers ﬁnd it difﬁcult to treat it as a

scientiﬁc hypothesis at all, exempting it from demands of falsiﬁability, speciﬁcation,

formalization, consistency, and proof they would insist on for any other scientiﬁc

hypothesis. For example, in dismissing the adaptive specialization hypothesis of social

exchange without examining the evidence, Eh rlich (2002) considers it sufﬁcient to

advance the folk theory that people just “ﬁgure it out.” He makes no predictions nor

speciﬁes any possible test that could falsify his view. Orr (2003) similarly refuses to

engage the evidence, arguing that perhaps “it just pays to behave in a certain way,

and an organism with a big-e nough brain reasons this out, while evolved instincts

and specialized mental modules are beside the point” (p. 18). He packages this

argument with the usual and necessarily undocumented claims about the low

scientiﬁ

c standards of evolutionary psychology (in this case, voiced by unnamed

colleagues in molecular biology).

What is problematic about this debate is not that the general rationality hypothe-

sis is advanced as an alternative explanation. It is a plaus ible (if hopelessly vagu e)

hypothesis. Indeed, the entire social exchange research program has, from its

inception, been designed to systematically test against the major predictions that

can be derived from this family of countertheories, to the extent they can be

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speciﬁed. What is problematic is that critics engage in the pretense that tests of the

hypothesis they favor have never been carried out; that their favored hypothesis has

no empirical burden of its own to bear; and that merely stating the general

rationality hypothesis is enough to establish the empirical weakness of the adaptive

specialization hypothesis. It is, in reality, w hat Dawkins (1986) calls the argument

from personal incredulity masquerading as its opposite—a commitment to high

standards of hypothesis testing.

Of course, to a cognitive scientist, Orr’s conjecture as stated does not rise to the level

of a scientiﬁc hypothesis. “Big brains” cause reasoning only by virtue of the neuro-

cognitive programs they contain. Had Orr speciﬁed a reasoning mechanism or a

learning process, we could empirically test the proposition that it predicts the

observed patterns of social exchange reasoning. But he did not. Fortunately, however,

a number of cognitive scientists have proposed some well-formulated by-product

hypotheses, all of which make different predictions from the adaptive specialization

hypothesis. Moreover, even where well-speciﬁed theories are lacking, one can derive

some general predictions from the class of general rationality theories about possible

versus impossible patterns of cultural variation, the effects of familiarity, possible

versus impossible patterns of neural dissociation, and so on. We have tested each

by-product hypothesis in turn. None can explain the patterns of reasoning perform -

ance found, patterns that were previously unknown and predicted in advance by

the hypothesis that humans have neurocognitive adaptations designed for social

exchange.

SELECTION PRESSURES AND PREDICTED DESIGN FEATURES

To test whether a system is an adaptation that evolved for a particular function, one

must produce design evidence. The ﬁrst step is to demons trate that the s ystem’s

properties solve a well-speciﬁed adaptive problem in a well-engineered way

(Dawkins, 1986; Tooby & Cosmides, 1992, Chapter 1, this Handbook,Volume1;

Williams, 1966). This requires a well-speciﬁed theory of the adaptive problem in

question.

For example, the laws of optics constrain the properties of cameras and eyes:

Certain engineering problems must be solved by any information processing

system that uses reﬂected light to project images of objects onto a 2-D surface

(ﬁlm or retina). Once these problems are understood, the eye’s d esign make s sense.

The transparency of the cornea, the ability of the iris to constrict the pupillary

opening, the shape of the lens, the existence of photoreactive molecules in the

retina, the resolution of retinal cells—all are solutions to these problems (and have

their counterparts in a camera). Optics constrain the design of the eye, but the

design of programs causing social behavior is co nstrained by the behavior of

other agents—mo re precisely, by the design of the behavior-regulating pro grams

in other agents and the ﬁtness consequences that result from the interactions these

programs cause. These constraints can be analyzed using evolutionary game theory

(Maynard Smith, 1982).

An evolutionarily stable strategy (ESS) is a strategy (a decision rule) that can arise and

persist in a population because it produces ﬁtness outcomes greater than or equal to

alternative strategies (Maynard Smith, 1982). The rules of reasoning and decision

making that guide social exchange in humans would not exist unless they had

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outcompeted alternatives, so we should expect that they implement an ESS.

By using

game theory and conducting computer simulations of the evolutionary process, one

can determine which strategies for engaging in social exc hange are ESSs.

Selection pressures favoring social exchange exist whenever one organism (the

provider) can change the behavior of a target organism to the provider’ s advantage

by making the target ’s receipt of that beneﬁt conditional on the target acting in a

required manner. In social exchange, individuals agree, either explicitly or implicitly,

to abide by a particular social contract. For ease of explication, let us deﬁne a

social contract as a conditional (i.e., If-then) rule that ﬁts the following template:

“If you accept a beneﬁt from X, then you must satisfy X’s requirement” (where X is

an individual or set of individuals). For example, Toma knew that people in his

band recognize and implicitly follow a social contract rule: If you accept a generous gift

of eland fat from someone, then you must give that person something valuable in the future.

Nisa’s words also express a social contract: If you are to get food in the future from me,

then you must be individual Y (where Y = an indivi dual who has willingly shared food

with Nisa in the past). Both realize that the act of accepting a beneﬁt from someone

triggers an obliga tion to behave in a way that somehow beneﬁ ts the provider, now or

in the fut ure.

This mutual provisioning of beneﬁts, each conditional on the other’s compliance, is

usually modeled by game theorists as a repeated Prisoners’ Dilemma (Axelrod &

Hamilton, 1981; Boyd, 1988; Trivers, 1971; but see Stevens & Stephens, 2004; Tooby &

Cosmides, 1996). The results show that the behavior of cooperators must be generated

by programs that perform certain speciﬁc tasks very well if they are to be evolutio-

narily stable (Cosmides, 1985; Cosmides & Tooby, 1989). Here, we focus on one of

these requirements: cheater dete ction. A che ater is an individual who fails to recipro-

cate—who accepts the beneﬁt speciﬁed by a social contract without satisfying the

requirement that provision of that beneﬁt was made contingent on.

The ability to reliably and systematically detect cheaters is a necessary condition for

cooperation in the repeated Prisoners’ Dilemma to be an ESS (e.g., Axelrod, 1984;

Axelrod & Hamilton, 1981; Boyd, 1988; Trivers, 1971; Williams, 1966).

To see this,

consider the fate of a program that, because it cannot detect cheaters, bestows beneﬁts

If the rules regulating reasoning and decision-making about social exchange do not implement an ESS, it

would imply that these rules are a by-product of some other adaptation that produces ﬁtness beneﬁts so

huge that they compensate for the systematic ﬁtness costs that result from its producing non-ESS forms of

social exchange as a side effect. Given how much social exchange humans engage in, this alternative seems

unlikely.

Detecting cheaters is necessary for contingent cooperation to evolve, even when providing a beneﬁt is cost

free (i.e., even for situations that do not ﬁt the payoff structure of a Prisoners’ Dilemma; Tooby & Cosmides,

1996). In such cases, a design that cooperates contingently needs to detect when someone has failed to

provide a beneﬁt because it needs to know when to shift partners. In this model (just as in the Prisoners’

Dilemma), a design that cannot shift partners will have lower ﬁtness than a design that detects cheaters and

directs future cooperation to those who do not cheat. Fitness is lower because of the opportunity cost

associated with staying, not because of the cost of providing a beneﬁt to the partner. Failure to understand

that social exchange is deﬁned by contingent provision of beneﬁts, not by the suffering of costs, has resulted

in some irrelevant experiments and discussion in the psychological literature. For example, showing that

cheater detection can still occur when the requirement is not costly (e.g., Cheng & Holyoak, 1989) is a

prediction of social contract theory, not a refutation of it (Cosmides, 1985; Cosmides & Tooby, 1989). For the

same reason, there is no basis in social contract theory for Cheng and Holyoak’s (1989) distinction between

“social exchanges” (in which satisfying the requirement involves transferring a good, at some cost) and

“social contracts” (in which satisfying a requirement may be cost free). For further discussion, see Fiddick

et al. (2000).

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on others unconditionally. These unconditional helpers will increase the ﬁtness of any

nonreciprocating design they meet in the population. But when a nonreciprocating

design is helped, the unconditional helper never recoups the expense of helping: The

helper design incurs a net ﬁtness cost while conferring a net ﬁtness advantage on a

design that does not help in return. As a result, a population of unconditional helper s

is easily invaded and eventual ly outcompeted by designs that accept the beneﬁts

helpers bestow without reciprocating them. Unconditional helping is not an ESS.

In contrast, program designs that cause conditional helping—that help those who

reciprocate the favor, but not those who fail to reciprocate — can invade a population of

nonreciprocators and outcompete them. Moreover, a population of such designs can

resist invasion by designs that do not reciprocate (cheater designs). Therefore,

conditional helping, which requires the ability to detect cheaters, is an ESS.

Engineers always start with a task analysis before considering possible design

solutions. We did, too. By applying ESS analyses to the behavioral ecology of hunter-

gatherers, we were able to specify tasks that an information processing program would

have to be good at solving for it to implement an evolutionarily stable form of social

exchange (Cosmides, 1985; Cosmides & Tooby, 1989). This task analysis of the required

computations, social contract theory, speciﬁes what counts as good design in this domain.

Because social contract theory provides a standard of good design against which

human performance can be measured, there can be a meaningful answer to the

question, “Are the programs that cause reasoning about social exchange well engi-

neered for the task?” Well-designed programs for engaging in social exchange—if

such exist—should include features that execute the computational requirements

speciﬁed by social contract theory, and do so reliably, precisely, and economically

(Williams, 1966).

From social contract theory’s task analyses, we derived a set of predictions about

the design fea tures that a neurocognitive system specialized for reasoning about social

exchange should have (Cosmides, 1985; Cosmides & Tooby, 1989, 2008a). The

following six design features (D1–D6) were among those on the list:

D1. Social exchange is cooperation for mutual beneﬁt. If there is nothing in a

conditional rule that can be interpreted as a rationed beneﬁt, then interpretive

procedures should not categorize that rule as a social contract. To trigger the

inferences about obligations and entitlements that are appropriate to social

contracts, the rule must be interpreted as restricting access to a beneﬁt to those

who have met a requirement. (This is a nec essary, but not sufﬁcient, condition;

Cosmides & Tooby, 1989; Gigerenzer & Hug, 1992.)

D2. Cheating is a speciﬁ c way of viol ating a social contract: It is taking the beneﬁt

when you are not entitled to do so. Consequently, the cognitive architecture

must deﬁne the concept of cheating using contentful representational primitives,

referring to illicitly taken beneﬁts. This implies that a system designed for cheater

detection will not know what to look for if the rule speciﬁes no beneﬁt to the

potential violator.

D3. The deﬁnition of cheating also depends on which agent’s point of view is taken.

Perspective matters becau se the item, action, or state of affairs that one party

views as a beneﬁt is viewed as a requirement by the other party. The system

needs to be a ble to com pute a cost-bene

ﬁ

t representation from the perspective of

each participant and deﬁne cheating with respect to that perspective-relative

representation.

Adaptations for Reasoning About Social Exchange 633

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D4. To be an ESS, a design for conditional helping must not be outcompeted by

alternative designs. Accidents and innocent mistakes that result in an individual

being cheated are not markers of a design difference. A cheater detection system

should look for cheaters: individuals equipped with programs that cheat by design.

Hence, intentional cheating should powerfully trigger the detection system whereas

mistakes should trigger it weakly or not at all. (Mistakes that result in an individual

being cheated are relevant only insofar as they may not be true mistakes.)

D6. The hypothesis that the ability to reason about social exchange is acquired

through the operation of some general-purpose learning ability necessarily

predicts that good performance should be a function of experience and famil-

iarity. In contrast, an evolved system for social exchange should be designed to

recognize and reason about social exchange interactions no matter how

unfamiliar the interaction may be, provided it can be mapped onto the abstract

structure of a social contract. Individuals need to be able to reason about each

new exchange situation as it arises, so rules that ﬁt the template of a social

contract should elicit high levels of cheater detection, even if they are unfamiliar.

D7. Inferences made about social contracts should not follow the rules of a content-

free, formal logic. They should follow a content-speciﬁc adaptive logic, evolu-

tionarily tailo red for the domain of social exchange (described in Cosmides &

Tooby, 1989, 2008a).

Cheating does involve the violation of a conditional rule, but note that it is a

particular kind of violation of a particul ar kind of conditional rule. The rule must ﬁt the

template for a soci al contract; the violation must be one in which an individual

intentionally took what that individual considered to be a beneﬁt and did so without

satisfying the requirement.

Formal logics (e.g., the propositional calculus) are content blind; the deﬁnition of

violation in standard logics applies to all conditional rules, whether they are social

contracts, threats, or descriptions of how the world works. But, as shown later, the

deﬁnition of cheating implied by design features D1 through D4 does not map onto

this content-blind deﬁnition of violation. What counts as cheating in social exchange is

so content sensitive that a detection mechanism equipped only with a domain-general

deﬁnition of violation would not be able to solve the problem of che ater detection. This

suggests that there should be a progra m specialized for cheater detection. To operate,

this program would have to function as a subcomponent of a system that, because of

its domain-specialized structure, is well designed for detecting social conditionals

involving exchange, interpreting their meaning, and successfully solving the inferen-

tial problems they pose: social contract algorithms.

CONDITIONAL REASONING AND SOCIAL EXCHANGE

Reciprocation is, by deﬁnition, social behavior that is conditional: You agree to deliver

a beneﬁt conditionally (conditional on the other person doing what you required in

return). Understanding it therefore requires conditional reasoning.

Programs that cheat by design is a more general formulation of the principle, which does not require the

human ability to form mental representations of intentions or to infer the presence of intentional mental

states in others. An analogy to deception may be useful: Birds that feign a broken wing to lure predators

away from their nests are equipped with programs that are designed to deceive the predator, but the

cognitive procedures involved need not include a mental representation of an intention to deceive.

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Because engaging in soci al exchange requires conditional reasoning, investigations

of conditional reasoning can be used to test for the presence of social contract

algorithms. The hypothesis that the brain contains social contract algorithms predicts

a dissociation in reasoning performance by content: a sharply enhanced ability to

reason adaptively about conditional rules when those rules specify a social exchange.

The null hypothesis is that there is nothing specialized in the brain for social exchange.

This hypothesi s follows from the traditional assumption that reasoning is caused by

content-independent processes. It predicts no enhanced conditional reasoning per-

formance spe ciﬁcally triggered by social exchanges as compared to other contents.

A standard to ol for investigating conditional reasoning is the Wason selection

task, which asks you to look for potential violations of a conditional rule of the form

If P, then Q (Wason, 1966, 1983; Wason & Johnson-Laird, 1972). Using this task,

an extensive series of experiments has been conducted that addresses the following

questions:

• Do our minds include cognitive machinery that is specialized for reasoning about

social exchange (alongside other domain-speciﬁc mechanisms, each specialized

for reasoning about a different adaptive domain involving conditional behav-

ior)? Or,

• Is the cognitive machinery that causes good conditional reasoning general—does

it operate well regardless of content?

If the human brain had cognitive machinery that causes good conditional reasoning

regardless of content, then people should be good at tasks requiring conditional

reasoning. For example, they should be good at detecting violations of conditional

rules. Yet studies with the Wason selection task show that they are not. Consider the

Wason task in Figure 25.1. The correct answer (choose P, choose not-Q) would be

intuitively obvious if our minds were equipped with reasoning procedures specialized

for detecting logical violations of conditional rules. But this answer is not obvious to

people. Studies in many nations have shown that reasoning performance is low on

descriptive (indicative) rules like the rule in Figure 25.1: Only 5% to 30% of people give

the logically correct answer, even when the rule involves familiar terms drawn from

everyday life (Cosmides, 1989; Manktelow & Evans, 1979; Sugiyama et al., 2002;

Wason, 1966, 1983). Interestingly, explicit instruction in logical inference does not

boost performance: People who have just completed a semester-long college course in

logic perform no better than people without this formal traini ng (Cheng, Holyoak,

Nisbett, & Oliver, 1986).

Formal logics, such as the propositional calculus, provide a standard of good design

for content-general conditional reasoning: Their inference rules were constructed by

philosophers to generate true conclusions from true premises, regardless of the subject

matter one is asked to reason about. When human performance is measured against this

standard, there is little evidence of good design: Conditional rules with descriptive

content fail to elicit logically correct performance from 70% to 95% of people. Therefore,

one can reject the hypothesis that the humanmind is equipped with cognitive machinery

that causes good conditional reasoning across all content domains.

ISSOCIATION BY CONTENT

People are poor at detecting violations of conditional rules when their content is

descriptive. Does this result generalize to conditional rules that express a social

Adaptations for Reasoning About Social Exchange 635

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contract? No. People who ordinarily cannot detect violations of if-then rules can do so

easily and accurately when that violation represents cheating in a situation of social

exchange. This pattern—good violation detection for social contrac ts but not for

descriptive rules—is a dissociation in reasoning elicited by differences in the condi-

tional rule’s content. It provides (initial) evidence that the mind has reasoning

procedures specialized for detecting cheaters.

More speciﬁcally, when asked to look for violations of a conditional rule that ﬁts

the social contract template—“If you take beneﬁt B, then you must satisfy requirement

R” (e.g., “If you borrow my car, then you have to ﬁll up the tank with gas”)—people

check the individual who accepted the beneﬁt (borrowed the car; P) and the individual

who did not satisfy the requirement (did not ﬁll the tank; not-Q). These are the cases

Ebbinghaus disease was recently identified and is not yet well understood. So an

international committee of physicians who have experience with this disease was

assembled. Their goal was to characterize the symptoms, and develop surefire

ways of diagnosing it.

Patients afflicted with Ebbinghaus disease have many different symptoms:

nosebleeds, headaches, ringing in the ears, and others. Diagnosing it is difficult

because a patient may have the disease, yet not manifest all of the symptoms.

Dr. Buchner, an expert on the disease, said that the following rule holds:

“If a person has Ebbinghaus disease, then that person will be forgetful.”

QthenPIf

Dr. Buchner may be wrong, however. You are interested in seeing whether there are

any patients whose symptoms violate this rule.

The cards below represent four patients in your hospital. Each card represents

one patient. One side of the card tells whether or not the patient has Ebbinghaus

disease, and the other side tells whether or not that patient is forgetful.

Which of the following card(s) would you definitely need to turn over to see if

any of these cases violate Dr. Buchner's rule: “If a person has Ebbinghaus disease,

then that person will be forgetful.” Don't turn over any more cards than are

absolutely necessary.

P not-QQnot-P

is not forgetful

is forgetful

does not have

Ebbinghaus

disease

has Ebbinghaus

disease

Figure 25.1 The Wason Selection Task. In a Wason task, there is always a rule of the form,

If P then Q, and four cards showing the values P, not-P, Q, and not-Q (respectively) on the side

that the subject can see. From a logical point of view, only the combination of P and not-Q can

violate this rule, so the correct answer is to check the P card (to see if it has a not-Q on the

back), the not-Q card (to see if it has a P on the back), and no others. Few subjects answer

correctly, however, when the conditional rule is descriptive (indicative), even when its content

is familiar; for example, only 26% of subjects answered the above problem correctly (by

choosing “has Ebbinghaus disease” and “is not forgetful”). Most choose either P alone, or P

and Q. (The italicized Ps and Qs are not in problems given to subjects.)

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that represent potential cheaters (Figure 25.2a). The adaptively correct answer is

immediately obvious to most subjects, who com monly experience a pop-out effect. No

formal training is needed. Whenever the content of a problem asks one to look for

cheaters in a social exchange, subjects experience the problem as simple to solve, and

their performance jumps dramatically. In general, 65% to 80% of subjects get it right,

the highest performance found for a task of this kind (for reviews, see Cosmides, 1985,

1989; Cosmides et al., 2010; Cosmides & Tooby, 1992, 1997, 2008a, 2008b; Fiddick et al.,

2000; Gigerenze r & Hug, 1992; Platt & Griggs, 1993).

Given the content-blind syntax of formal logic, investigating the person who

borrowed the car (P) and the person who did not ﬁll the gas tank (not-Q) is logically

equivalent to investigating the person with Ebbinghaus disease (P) and the person

who is not forgetful (not-Q) for the disease-symptom problem in Figure 25.1. But

everywhere it has been tested (ad ults in the United States, United Kingdom, Germany,

Italy, France, Hong Kong, Japan; schoolchildren in Quito, Ecuador; Shiwiar hunter-

horticulturalists in the Ecuadorian Amazon), people do not treat social exchange

problems as equivalent to other kinds of conditional reasoning problems (Cheng &

Holyoak, 1985; Cosmides, 1989; Hasegawa & Hiraishi, 2000; Platt & Griggs, 1993;

Sugiyama et al., 2002; supports D5, D6). Their minds distinguish social exchange

content from other domains, and reason as if they were translating their terms into

representational primitives such as beneﬁt, cost, obligation, entitlement, intentional, and

agent (Figure 25.2b; Cosmides & Tooby, 1992, 2008a; Fiddick et al., 2000). Reasoning

problems could be sorted into indeﬁnitely many categories based on their content or

structure (including the propositional calculus’s two content-free categories, anteced-

ent and consequent). Yet, even in remarkably different cultures, the same mental

categorization occurs. This cross-culturally recurrent dissociation by content was

predicted in advance of its discovery by social contract theory’s adaptationist analysis.

This pattern of good performance on reasoning problems involving social exchange

is what we would expect if the mind reli ably develops neurocognitive adaptations for

reasoning about social exchange. But more design evidence is needed. Later we review

experiments conducted to test for design features D1 through D6: features that shoul d

be present if a system specialized for social exchange exists.

In addition to producing evidence of good design for social exchange, recall that

one must also show that the system’s properties are not better explain ed as a solution

to an alternative adaptive problem or by chance (Tooby & Cosmides, 1992, Chapter 1,

this Handbook, Volume 1). Each experiment testing for a des ign feature was also

constructed to pit the adaptive specialization hypothesis against at least one alterna-

tive by-product hypothesis, so by-product and design feature implications are dis-

cussed in tandem. As we show, reasoning performance on social contracts is not

explained by familiarity eff ects, by a content-free formal logic, by a permission

schema, or by a general deontic logic. Table 25.1 lists the by-product hypotheses

that have been tested and eliminated.

DO UNFAMILIAR SOCIAL CONTRACTS ELICIT CHEATER

DETECTION? (D5)

An individual needs to understand each new opportunity to exchange as it arises,

so it was predicted that social exchan ge reasoning should operate even for

unfamiliar social contract rules (D5). This distinguishes social contract theory

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Teenagers who don’t have their own cars usually end up borrowing their parents’

cars. In return for the privilege of borrowing the car, the Carters have given their

kids the rule,

“If you borrow my car, then you have to fill up the tank with gas.”

Of course, teenagers are sometimes irresponsible. You are interested in seeing

whether any of the Carter teenagers broke this rule.

The cards below represent four of the Carter teenagers. Each card represents

one teenager. One side of the card tells whether or not a teenager has borrowed

the parents’ car on a particular day, and the other side tells whether or not that

teenager filled up the tank with gas on that day.

Which of the following card(s) would you definitely need to turn over to see if

any of these teenagers are breaking their parents’ rule: “If you borrow my car,

then you have to fill up the tank with gas.” Don’t turn over any more cards than

are absolutely necessary.

The mind translates social contracts into representations of benefits and require-

ments, and it inserts concepts such as "entitled to" and "obligated to," whether they

are specified or not.

How the mind “sees” the social contract above is shown in bold italics.

“If you borrow my car, then you have to fill up the tank with gas.”

If you take the benefit, then you are obligated to satisfy the requirement.

did not fill up

tank with gas

did not satisfy

the requirement

filled up tank

with gas

= satisfied the

requirement

did not

borrow car

= did not accept

the benefit

borrowed

car

= accepted the

benefit

did not fill up

tank with gas

filled up tank

with gas

did not

borrow car

borrowed

car

Figure 25.2 Wason Task with a Social Contract Rule. (A) In response to this social contract

problem, 76% of subjects chose P and not-Q (“borrowed the car ” and “did not ﬁll the tank with

gas”)—the cards that represent potential cheaters. Yet only 26% chose this (logically correct)

answer in response to the descriptive rule in Figure 25.1. Although this social contract rule

involves familiar items, unfamiliar social contracts elicit the same high performance. (B) How

the mind represents the social contract shown in (A). According to inferential rules specialized

for social exchange (but not according to formal logic), “If you take the beneﬁt, then you are

obligated to satisfy the requirement” implies “If you satisfy the requirement, then you are

entitled to take the beneﬁt.” Consequently, the rule in (A) implies: “If you ﬁll the tank with gas,

then you may borrow the car” (see Figure 25.4, switched social contracts).

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strongly from theories that explain reasoning performance as the product of

general learning strategies plus experience: The most natural prediction for

such skill-acquisition theories is that performance should be a function of

familiarity.

The evidence supports social contract th eory: Cheater detection occurs even

when the social contract is wildly u nfamiliar (Figure 25.3a). For example, the rule

“If a man eats cassava root, then he must have a tattoo on his face” can be made to

ﬁt the social contract template by explaining that the people involved consider

eating cassava root to be a beneﬁ t (the rule then implies that having a tattoo is the

requirement an individual must satisfy to be eligible for that beneﬁt). When given

this context, this outlandish, culturally alien rule elicits the same high level of

cheater detection as highly familiar social exchange rules. This surprising result

has been replicated for many different unfamiliar rules (Cosmides, 1985, 1989;

Cosmides & Tooby, 1992; Gigerenzer & Hug, 1992; Platt & Griggs, 1993).

LIMINATING FAMILIARITY (B1)

The dissociation by content—good performance for social contract rules but not for

descriptive ones—has nothing to do with the familiarity of the rules tested. Familiarity

is neither necessary nor sufﬁcient for eliciting high performance (B1 of Table 25.1).

First, familiarity does not produce high levels of performance for descriptive rules

(Cosmides, 1989; Manktelow & Evans, 1979). Note, for example, that the Ebbinghaus

disease problem in Figure 25.1 involves a familiar causal relationship (a disease

causing a symptom) embedded in a real-world context. Yet only 26% of 111 college

students that we tested produced the logically correct answer, P & not-Q, for this

problem. If familiarity fails to elicit high performance on descriptive rules, then it also

fails as an explanation for high performance on social contracts.

Table 25.1

Alternative (By-Product) Hypotheses Eliminated

B1. That familiarity can explain the social contract effect.

B2. That social contract content merely activates the rules of inference of the propositional

calculus (logic).

B3. That any problem involving payoffs will elicit the detection of logical violations.

B4. That permission schema theory can explain the social contract effect.

B5. That social contract content merely promotes “clear thinking.”

B6. That a content-independent deontic logic can explain social contract reasoning.

B7. That a single mechanism operates on all deontic rules involving subjective utilities.

B8. That relevance theory can explain social contract effects (see also Fiddick, Cosmides, &

Tooby, 2000).

B9. That standard economic models can explain social contract effects.

B10. That statistical learning produces the mechanisms that cause social contract reasoning.

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Second, the fact that unfamiliar social contracts elicit high performance shows that

familiarity is not necessary for eliciting violation detectio n. Third (and most surpris-

ing), people are just as good at detecting cheaters on culturally unfamiliar or

imaginary social contracts as they are for ones that are completely familiar (Cosmides,

1985). This provides a challenge for any counterhypothesis resting on a general-

learning skill acquisition account (most of which rely on familiarity and repetition).

ADAPTIVE LOGIC, NOT FORMAL LOGIC (D3, D6)

As shown earlier, it is possible to construct social contract problems that will elicit a

logically correct answer. But this is not because social exchange content activates

logical reasoning.

Good cheater detection is not the same as good detectio n of logical violations (and

vice versa). Hence, problems can be created in which the search for cheaters will result

in a logically incorrect response (and the search for logical violations will fail to detect

A. Standard form B. Switched form

Percent P and Not-Q

Percent Q and Not-P

Exp 1 and 3: Social contract = social rule

Exp 2 and 4: Social contract = personal exchange

Social contract

Descriptive rule

Exp 4Exp 3Exp 2Exp 1

Figure 25.3 Detecting Violations of Unfamiliar Conditional Rules: Social Contracts Versus

Descriptive Rules. In these experiments, the same, unfamiliar rule was embedded either in a

story that caused it to be interpreted as a social contract or in a story that caused it to be

interpreted as a rule describing some state of the world. For social contracts, the correct

answer is always to pick the beneﬁt accepted card and the requirement not satisﬁed card.

(A) For standard social contracts, these correspond to the logical categories P and not-Q. P

and not-Q also happens to be the logically correct answer. Over 70% of subjects chose these

cards for the social contracts, but fewer than 25% chose them for the matching descriptive

rules. (B) For switched social contracts, the beneﬁt accepted and requirement not satisﬁed

cards correspond to the logical categories Q and not-P. This is not a logically correct response.

Nevertheless, about 70% of subjects chose it for the social contracts; virtually no one chose it

for the matching descriptive rules (see Figure 25.4).

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cheaters; see Figure 25.4). When given such problems, people look for cheaters,

thereby giving a logically incorrect answer (Q and not-P).

ERSPECTIVE CHANGE

As predicted (D3), the mind’s automatically deployed deﬁnition of cheating is tied to

the perspective you are taking (Gigerenzer & Hug, 1992). For example, consider the

following social contract:

[1] If an employee is to get a pension, then that employee must have worked for the

ﬁrm for over 10 years.

Consider the following rule:

Standard format:

If you take the benefit, then satisfy my requirement (e.g., “If I give you $50, then give

me your watch.”)

QthenIf

Swi tched format:

If you satisfy my requirement, then take the benef it (e.g., “If you give me your watch,

then

I’ll give you $50.”)

QthenP

The cards below have information about four people to whom this offer was made.

Each card represents one person. One side of a card tells whether the person ac-

cepted the benefit, and the other side of the card tells whether that person satisfied

the requirement. Indicate only those card(s) you definitely need to turn over to see

if any of these people have violated the rule.

Standard: not-QQ not-P P

Swi tched: not-PP not-Q Q

Requirement

not satisfied

Requirement

satisfied

Benefit not

accepted

Benefit

accepted

Figure 25.4 Generic Structure of a Wason TaskWhen the Conditional Rule Is a Social

Contract. A social contract can be translated into either social contract terms (beneﬁts and

requirements) or logical terms (antecedents and consequents; designated here as Ps and Qs).

Check marks indicate the correct card choices if one is looking for cheaters—these should be

chosen by a cheater detection subroutine, whether the exchange was expressed in a standard

or switched format. This results in a logically incorrect answer (Q and not-P) when the rule is

expressed in the switched format, and a logically correct answer (P and not-Q) when the rule is

expressed in the standard format. By testing switched social contracts, one can see that the

reasoning procedures activated cause one to detect cheaters, not logical violations (see

Figure 25.3B). Note that a logically correct response to a switched social contract—where

P = requirement satisﬁed and not-Q = beneﬁt not accepted—would fail to detect cheaters.

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This rule elicits different answers depending on whether subjects are cued into the

role of employer or employee. Those in the employer role look for cheating by employ-

ees, investigating cases of P and not-Q (employees with pensions; employees who have

worked for fewer than 10 years). Those in the employee role look for cheating by

employers, investigating cases of not-P and Q (employees with no pension; employees

who have worked more than 10 years). Not-P & Q is correct if the goal is to ﬁnd out

whether the employer is cheating employees. But it is not logically correct.

In social exchange, the beneﬁt to one agent is the requirement for the other: For

example, giving pensions to employees beneﬁts the employees but is the requirement

the employer must satisfy (in exchange for > 10 years of employee service). To capture

the distinction between the perspectives of the two agents, rules of inference for social

exchange must be content sensitive, deﬁning beneﬁts and requirements relative to the

agents involved. Because logical procedures are blind to the content of the proposi-

tions over which they operate, they have no way of representing the values of an

action to each agent involved.

WITCHED SOCIAL CONTRACTS

By moving the beneﬁ t from the antecedent clause (P) to the consequent clause (Q), one

can construct a social exchange problem for which the adaptively correct cheater

detection response is logically incorrect.

According to the propositional calculus (a formal logic), If B then C does not imply If

C then B; therefore, “If you take the beneﬁt, then you are obligated to satisfy the

requirement,” does not imply, “If you satisfy the requirement, then you are entitled to

take the beneﬁt.” But inferential rules specialized for social exchange do license the

latter inference (Cosmides & Tooby, 1989). Consequently, social exchange inferences

(but not logical ones) should cause rule [1] above to be interpreted as implying:

[2] If an employee has worked for the ﬁrm for over 10 years, then that employee gets

a pension.

Assume you are concerned that employees have been cheating and are asked to

check whether any employees have violated the rule. Although [2] and [1] are not

logically equivalent, our minds interpret them as expres sing the same social contrac t

agreement. Hence, in both cases, a subroutine for detecting cheaters should cause you

to check employees who have taken the beneﬁt (gotten a pension) and employees who

have not met the requirement (worked < 10 years).

But notice that these cards fall into different logical categories when the beneﬁtto

the potential cheater is in the antecedent clause versus the cons equent clause (standard

versus switched format, respectively; Figure 25.4). When the rule is expressed in the

switched format, “got a pension” corresponds to the logical category Q, and “worked

less than 10 years” corresponds to the logical category not-P. This answer will correctly

detect employees who are cheating, but it is logically incorrect. When the rule is

expressed in the standard format, the same two cards correspond to P and not-Q.

Moreover, the propositional calculus contains no rules of inference that allow If B, then C to be translated as

If C, then B (i.e., no rule for translating [1] as [2]; see text) and then applying the logical deﬁnition of violation

to [2] to arrive at the employee perspective answer (see Fiddick et al., 2000).

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For standard format social contracts, the cheater detection subroutine will produce the

same answer as logical procedures would—not because this response is logically

correct, but because it will detect cheaters.

When given switched social contracts like [2], subjects overwhelmingl y respond by

choosing Q & not-P, a logically incorrect answer that correctly detects cheaters

(Figure 25.3b; Cosmides, 1985, 1989; Gigerenzer & Hug, 1992; supports D2, D6).

Indeed, when subjects’ choices are classiﬁed by logical category, it looks like standard

and switched social contracts elicit different responses. But when their choices are

classiﬁed by social contra ct category, they are invariant: For both rule formats, people

choose the cards that represent an agent who took the beneﬁt and an agent who did

not meet the requirement.

This robust pattern occurs precisely because social exchange reasoning is sensitiv e

to content: It responds to a syntax of agent-relative beneﬁts and requirements, not

antecedents and consequents. Logical procedures would fail to detect cheaters on

switched social contracts. Being content blind, their inferential rules are doomed to

checking P and not-Q, even when these cards correspond to potential altruists (or

fools)—that is, to people who have fulﬁlled the requirement and people who have not

accepted the beneﬁt.

LIMINATING LOGIC (B2, B3)

Consider the following by-product hypothesis: The dissociation betwe en social

contracts and descriptive rules is not caused by a cheater detection mechanism.

Instead, the human cognitive architecture applies content-free rules of logical infer-

ence, such as modus ponens and modus tollens. These logical rules are activated by social

contract content but not by other kinds of content, and that causes the spike in P & not-

Q answers for social contracts.

The results of the switched social contract and the perspective change experiments

eliminate this hypothesis. Social contracts elicit a logically incorrect answer, Q & not-P,

when this ans wer would correctly detect cheaters. Logical rules applied to the syntax

of the material conditional cannot explain this pattern, because these rules would

always choose a true antecedent and false consequent ( P & not-Q), never a true

consequent and false antecedent (Q & not-P).

There is an active debate about whether the human cognitive architecture includes

content-blind rules of logical inference, which are sometimes dormant and sometimes

activated (e.g., Bonatti, 1994; Rips, 1994; Sperber, Cara, & Girotto, 1995). We are

agnostic about that issue. What is clear, however, is that such rules cannot explain

reasoning about social contracts (for further evidence, see Fiddick et al., 2000).

DEDICATED SYSTEM OR GENERAL INTELLIGENCE?

Social contract reasoning can be maintained in the face of impairments in general

logical reasoning. Individuals with schizophrenia manifest deﬁcits on virtually any

test of general intellectual functioning they are given (McKenna, Clare, & Baddeley,

1995). Yet their ability to detect cheaters can remain intact. Maljkovic (1987) tested the

reasoning of patients suffering from positive symptoms of schizophrenia, comparing

their performance with that of hospitalized (nonpsychotic) control patients. Com-

pared to the control patients, the schizophrenic patients were impaired on more

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general (non-Wason) tests of logical reasoning, in a way typical of individuals with

frontal lobe dysfunction. But their ability to detect cheaters on Wason tasks was

unimpaired. Indeed, it was indistinguishable from the controls and showed the typical

dissociation by content (see also Kornreich, Delle-Vigne, Dubruille, Campanella,

Noel, & Ermer, forthcoming). This selective preservation of social exchange reasoning

is consistent with the notion that reasoning about social exchange is handled by a

dedicated system, which can operate even when the systems responsible for more

general reasoning are damaged. It provides further support for the claim that social

exchange reasoning is functionally and neurally distinct from more general abilities to

process information or behave intelligently.

HOW MANY SPECIALIZATIONS FOR CONDITIONAL REASONING?

Social contracts are not the only conditional rules for which natural selection should

have designed specialized reasoning mechanisms (Cosmides, 1989). Indeed, good

violation detection is also found for conditional rules drawn from two other domains:

threats and precautions. Is good performance across these three domains caused by a

single neurocognitive system or by several functionally distinct ones? If a single

system causes reasoning about all three domains, then we should not claim that

cheater detection is caused by adaptations that evolved for that speciﬁc function.

The notion of multiple adaptive specializations is commonplace in physiology: The

body is composed of many organs, each designed for a different function. Yet many

psychologists c ringe at the notion of multiple adaptive specializations when these are

computational. Indeed, evol utionary approaches to psychology foundered in the early

1920s on what was seen as an unfounded multiplication of “instincts.”

That was before the cogn itive revolution, with its language for describing what the

brain does in information processing terms and its empirical methods for revealing the

structure of representations and processes. Rather than relying on a priori arguments

about what should or could be done by a single mechanism, we can now empirically

test whether processing about two domains is accomplished by one mechanism or

two. We should not imagine that there is a separate specialization for solving each and

every adaptive problem. Nor should real differences in processing be ignored in a

misguided effort to explain all perform ance by reference to a single mechanism. As

Einstein once said, “Make everything as simple as poss ible, but no simpler.”

ONDITIONAL REASONING ABOUT OTHER SOCIAL DOMAINS

Threats specify a conditional rule (If you don’t do what I require, I will harm you), which

the threatener can violate in two ways: by blufﬁng or by double-crossing. It appears

that people are good at detecting bluffs and double-crosses on Wason tasks that test

threats (with an interesting sex difference never found for social exchange problems;

Tooby & Cosmides, 1989). However, these violations do not map onto the deﬁnition of

cheating and, therefore, cannot be detected by a cheater detection mechanism. This

suggests that reasoning about social contracts and threats is caused by two distinct

mechanisms. (So far, no theory advocating a single mechanism for reasoning about

these two domains has been proposed. Threats are not deontic; see later discussion.)

Also of adaptive importance is the ability to detect when someone is in danger by

virtue of having violated a precautionary rule. These rules have the general form,

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“If one is to engage in hazardous activity H, then one must take precaution R” (e.g., “If you

are working with toxic gases, then wear a gas mask”). Using the Wason task, it has

been shown that people are very good at detecting potential violators of precautionary

rules; that is, individuals who have engaged in a hazardous activity without taking the

appropriate precaution (e.g., those working with toxic gases [P] and those not wearing

a gas mask [not-Q]). Indeed, relati ve to descriptive rules, precautions show a spike in

performance, and the magnitude of this content effect is about the same as that for

detecting cheaters on social contracts (Cheng & Holyoak, 1989; Fiddick et al., 2000;

Manktelow & Over, 1988, 1990, 1991; Stone et al., 2002).

A system well designed for reasoning about hazards and precautions should have

properties different from one for detecting cheaters, many of which have been tested

for and found (Fiddick, 1998, 2004; Fiddick et al., 2000; Pereyra & Nieto, 2004; Stone

et al., 2002). Therefore, alongside a specialization for reasoning about social exchange,

the human cognitive architecture should contain computational machinery special-

ized for managing hazards, which causes good violation detection on precauti onary

rules. Obsessive-compulsive disorder, with its compulsive worrying, checking, and

precaution taking , may be caused by a misﬁring of this precautionary system (Boyer &

Lienard, 2006; Cosmides & Tooby, 1999; Leckman & Mayes, 1998, 1999; Szechtman &

Woody, 2004).

An alternative view is that reasoning about social contracts and precautionary rules

is generated by a single mechanism. Some view both social contracts and precautions

as deontic rules (i.e., rules specifying obligations and entitlements) and wonder

whether there is a general system for reasoning about deontic conditionals. More

speciﬁcally, Cheng and Holyoak (1985, 1989) have proposed that inferences about

both types of rule are generated by a permission schema, which operates over a larger

class of problems.

Can positing a permission schema explain the full set of relevant results? Or are

they more parsimoniously explained by positing two separate adaptive specializa-

tions, one for social contracts and one for precautionary rules? We are looking for a

model that is as simple as possible, but no simpler.

SOCIAL CONTRACT ALGORITHMS OR A PERMISSION SCHEMA?

LOOKING FOR DISSOCIATIONS WITHIN< THE CLASS OF

PERMISSION RULES (D1, D2, D4)

Permission rules are a species of conditional rule. According to Cheng and Holyoak

(1985, 1989), these rules are imposed by an authority to achieve a social purpose, and

they specify the conditions under which an individual is permitted to take an action.

Cheng and Holyoak spe culate that repeated encounters with such social rules cause

domain-general learning mechanisms to induce a permission schema, consisting of four

production rules (see Table 25.2). This schema generates inferences about any

conditional rule that ﬁts the following template: “If action A is to be taken, then

precondition R must be satisﬁed.”

Social contracts ﬁt this template. In social exchange, an agent permits you to take a

beneﬁt from him or her, conditional on your having met the agent’s requirement.

Cheng and Holyoak (1985) also propose an obligation schema, but permission and obligation schemas do

not lead to different predictions on the kinds of rules usually tested (see Cosmides, 1989; Rips, 1994, p. 413).

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There are, however, many situations other than social exchange in which an action is

permitted conditionally. Permission schema theory predicts uniformly high perform-

ance for the entire class of permission rules, a set that is larger, more general, and more

inclusive than the set of all social contracts (see Figure 25.5).

On this view, a neuroco gnitive system specialized for reasoning about social

exchange, with a subroutine for cheater detection, does not exist. According to their

hypothesis, a permission schema causes good violation detection for all permission

rules; social contracts are a subset of the class of permission rules; therefore, cheater

detection occurs as a by-product of the more domain-general permission schema

(Cheng & Holyoak, 1985, 1989).

In contrast, the adaptive specialization hypothesis holds that the design of the

reasoning system that causes cheater detection is more precise and functionally

specialized than the design of the permission schema. Social contract algorithms

should have design features that are lacking from the permission schema, such as

responsivity to beneﬁts and intentionality. As a result, removing beneﬁts (D1, D2)

Table 25.2

The Permission Schema Is Composed of Four Production Rules

Rule 1: If the action is to be taken, then the precondition must be satisﬁed.

Rule 2: If the action is not to be taken, then the precondition need not be satisﬁed.

Rule 3: If the precondition is satisﬁed, then the action may be taken.

Rule 4: If the precondition is not satisﬁed, then the action must not be taken.

Cheng and Holyoak, 1985.

Social contracts and precautions ﬁt the template of Rule 1:

If the beneﬁt is to be taken, then the requirement must be satisﬁed.

If the hazardous action is to be taken, then the precaution must be taken.

Permission rules

Precaution rulesSocial contracts

Figure 25.5 The Class of Permission Rules Is Larger Than, and Includes, Social Contracts

and Precautionary Rules. Many of the permission rules we encounter in everyday life are

neither social contracts nor precautions (white area). Rules of civil society (etiquette, customs,

traditions), bureaucratic rules, corporate rules—many of these are conditional rules that do not

regulate access to a beneﬁt or involve a danger. Permission schema theory (see Table 25.2)

predicts high performance for all permission rules; however, permission rules that fall into the

white area do not elicit the high levels of performance that social contracts and precaution rules

do. Neuropsychological and cognitive tests show that performance on social contracts

dissociates from other permission rules (white area), from precautionary rules, and from the

general class of deontic rules involving subjective utilities. These dissociations would be

impossible if reasoning about social contracts and precautions were caused by a single

schema that is general to the domain of permission rules.

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and/or intentionality (D4) from a social contract should produce a permission rule

that fails to elicit good violation detection on the Wason task.

As Sherlock Holmes might put it, we are looking for the dog that did not bark:

Permission ru les that do not elicit good violation detection. That discovery would

falsify permission schema theory. S ocial contract theory predicts functional disso-

ciations within the class of permission rules whereas permission schema theory

does not.

NO BENEFITS, NO SOCIAL EXCHANGE REASONING:

TESTING D1 AND D2

To trigger cheater detection (D2) and inference procedures specialized for interpreting

social exchanges (D1), a rule needs to regulate access to beneﬁts, not actions more

generally. Does reasoning performance change when beneﬁts are removed?

ENEFITS ARE NECESSARY FOR CHEATER DETECTION (D1, D2)

The function of a social exchange for each participant is to gain access to beneﬁts that

would otherwise be unavailable to them. Therefore, an important cue that a condi-

tional rule is a social contract is the presence in it of a desired beneﬁt under the control

of an agent. Taking a beneﬁt is a representational primitive within the social contract

template If you take beneﬁt B, then you must satisfy requirement R.

The permission schema template has representational primitives with a larger

scope than that proposed for social contract algorithms. For example, taking a beneﬁt is

taking an action, but not all cases of taking actions are cases of taking beneﬁts. As a

result, all social contracts are permission rules, but not all permission rules are social

contracts. Precautionary rules can also be construed as permission rules (although

they need not be; see Fiddick et al., 2000, exp. 2). They, too, have a more restricted

scope: Hazardous actions are a subset of actions; precautions are a subset of preconditions.

Note, however, that there are permission rules that are neither social contracts nor

precautionary rules (see Figure 25.5). This is because there are actions an individual

can take that are not beneﬁ ts (social contract theory) and that are not hazardous

(hazard management theory). Indeed, we encounter many rules like this in every-

day life—bureaucratic and corporate rules, for example, often state a procedure that

is to be followed without specifying a beneﬁt(oradanger).Ifthemindhasa

permission schema, then people should be good at detecting violations of rules that

fall into the white area of Figure 25.5, that is, permission rules that are neither social

contracts nor precautionary. But they are not. Beneﬁts are necessary for cheater

detection.

Using the Wason task, several labs have tested permission rules that involve no

beneﬁt (and are not precautionary). As predic ted by social contract theory, these do

not elicit high levels of violation detection. For example, Cosmides and Tooby (1992;

see also Cosmides et al., 2010) constructed Wason tasks in which the elders (authori-

ties) were creating laws governing the conditions under which adolescents are

permitted to take certain actions. For all tasks, the law ﬁt the template for a permission

rule. The permission rules tested differed in just one respect: whether the action to be

taken is a beneﬁt or an unpleasant chore. The critical conditions compared perform-

ance on these two rule s:

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[3] “If one is going out at night, then one must tie a small piece of red volcanic rock

around one’s ankle.”

[4] “If one is taking out the garbage, then one must tie a small piece of red volcanic

rock around one’s ankle.”

A cheater detection subroutine looks for beneﬁts illicitly taken; without a beneﬁt, it

doesn’t know what kind of violation to look for (D1, D2). When the permitted action

was a beneﬁt (getting to go out at night), 80% of subjects answered correctly; when it

was a chore (taking out the garbage), only 44% did so (for details, see Cosmides et al.,

2010). This dramatic decrease in violation detection was predicted in advance by social

contract theory. Moreover, it violates the central prediction of permission schem a

theory: that being a permission rule is sufﬁcient to facilitate violation detection. There

are now many experiments showing poor violation detection with permission rules

that lack a beneﬁt (e.g., Barrett, 1999; Beaman, 2002; Cosmides, 1989, exp. 5; Fiddick,

2003; Manktelow & Over, 1991; Platt & Griggs, 1993; for discussion, see Cosmides &

Tooby, 2008b).

This is another dissociation by content, but this time it is within the domain of

permission rules. To elicit cheater detection, a permission rule must be interpreted as

restricting access to a beneﬁt. It supports the psychological reality of the representa-

tional primitives posited by social contract theory, showing that the representations

necessary to trigger differential reasoning are more content speciﬁc than those of the

permission schema.

ENEFITS TRIGGER SOCIAL CONTRACT INTERPRETATIONS (D1)

The Wason experiments just des cribed tested D1 and D2 in tandem. But D1—the claim

that beneﬁts are necessary for permission rules to be interpreted as social contracts—

receives support independent of experiments testing D2, from studies of moral

reasoning. Fiddick (2004) asked subjects what justiﬁes various permission rules

and when an individual should be allowed to break them. The rules were closely

matched for surface content, and context was used to vary their interpretation. The

permission rule that lacked a beneﬁ t (a precautionary one) elicited different judgments

from permission rules that restricted access to a beneﬁt (the social contracts). Whereas

social agreement and morality, rather than facts, were more often cited as justifying

the social contract rules, facts (about poisons and antidotes) rather than social

agreement were seen as justifying the precautionary rule. Whereas most subjects

thought it was acceptable to break the social contract rules if you were not a member of

the group that created them, they thought the precautionary rule should always be

followed by people everywhere. Moreover, the explicit exchange rule triggered very

speciﬁc inferences about the cond itions under which it could be broken: Those who

had received a beneﬁt could be released from their obligation to reciprocate, but only by

those who had provided the beneﬁt to them (i.e., the obligation could not be voided by a

group leader or by a consensus of the recipients themselv es). The inferences subjects

made about the rules restricting access to a beneﬁt follow directly from the gramm ar of

social exchange laid out in social contract theory (Cosmides & Toob y, 1989). These

inferences were not—and should not—be applied to precautionary rules (see also

Fiddick et al., 2000). The presence of a beneﬁt also predicted inferences about emo-

tional reactions to seeing someone violate a permission rule: Social contract violations

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were thought to trigger anger whereas precautionary violations were thought to

trigger fear (Fiddick, 2004). None of these dissociations within the realm of permission

rules are predicted by permission schema theory.

INTENTIONAL VIOLATIONS VERSUS INNOCENT MISTAKES:

TESTING D4

Intentionality plays no role in permission schema theory. Whenever the action has

been taken but the precondition has not been satisﬁed, the permission schema should

violations of permission rules, whether the violations occurred by accident or by

intention. In contrast, social contract theory predicts a mechanism that looks for

intentional violations (D4).

Program designs that cause unconditional helping are not evolutionarily stable

strategies. Conditional helping can be an ESS because cheater detection provides a

speciﬁc ﬁtness advantage unavailable to unconditional helpers: By identifying cheaters,

the conditional helper can avoid squandering costly cooperative efforts in the future on

those who, by virtue of having an alternative program design, will not reciprocate. This

means the evolutionary function of a cheater detection subroutine is to correctly connect

an attributed disposition (to cheat) with a person (a cheater). It is not simply to recognize

instances wherein an individual did not get what he or she was entitled to. Violations of

social contracts are relevant only insofar as they reveal individuals disposed to cheat—

individuals who cheat by design, not by accident. Noncompliance caused by factors

other than disposition, such as accidental violations and other innocent mistakes, does

not reveal the disposition or design of the exchange partner. Accidents may result in

someone being cheated, but without indicating the presence of a cheater.

Therefore, social contract theory predicts an additional level of cognitive special-

ization beyond looking for violations of a social contract. Accidental violations of

social contracts will not fully engage the cheater detection subroutine; intentional

violations will (D4).

ISSOCIATION FOR SOCIAL CONTRACTS

Given the same social exchange rule, one can manipulate contextual factors to

change the nature of the violation from intentional cheating to an innocent mistake.

One experiment, for example, compared a condition in which the potential rule

violator was inattentive but well meaning to a condition in which she had an incentive

to intentionally cheat. Varying intentionality caused a radical change in performance,

from 68% correct in the intentional cheating condition to 27% correct in the

innocent mistake condition (Cosmides et al., 2010; supports D4; disconﬁrms

B1–B8). Fiddick (1998, 2004) found the same effect (as did Gigerenzer & Hug,

1992, using a different context manipulation).

In both scenarios, violating the rule would result in someone being cheated, yet

high performance occurred only when being cheated was cause d by a cheater.

Cosmides et al. (2010; see also Barrett, 1999) conducted a series of parametric studies

Mistakes can be faked, of course. Too many by a given individual should raise suspicion, as should a single

mistake that results in a very large beneﬁt. Although this prediction has not been tested yet, we would expect

social contract algorithms to be sensitive to these conditions.

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to ﬁnd out whether the drop in performance in the innocent mistake condition was

caused by the violator’s lack of intentionality (D4) or by the violator’s failure to beneﬁt

from her mistake (D2; see earlier discussion, on the necessity of beneﬁts to elicit cheater

detection). They found that both factors independentl y contributed to the drop,

equally and additively. Thus, the same decrease in performance occurred whether

(1) violators would beneﬁt from their innocent mistakes, or (2) violators wanted to

break the rule on purpose but would not get the beneﬁt speciﬁed in the rule by doing

so. For scenarios missing both factors (i.e., accidental violations that do not beneﬁt the

violator), performance dropped by twice as much as when just one factor was missing.

That is, the more factors relevant to cheater detection are removed, the more

performance drops.

In bargaining games, experimental economists have found that subjects are

twice as likely to punish defections (failures to reciprocate) when it is clear that

the defector inten ded to cheat as when the defector is a novice who might have

simply made a m istake (Hoffman, McCabe, & Smith, 1998). This provides

interesting convergent evidence, using entirely different methods, for the claim

that programs causing social exchange distinguish between mistakes and inten-

tional cheatin g.

O DISSOCIATION FOR PRECAUTIONS

Different results are expected for precautionary ru les. Intentionality should not

matter if the mechanisms that d etect violations of precautionary rules were designed

to look for people in danger. For example, a perso n who is not wearing a gas mask

while working with toxic gases is in danger, whether that person forgot the gas

mask at home (accidental violation) or left it home on purpose (intentional viola-

tion). That is, varying the intentionality of a violation should affect social exchange

reasoning but not precautionary reasoning. Fiddick (1998, 2004) tested and con-

ﬁrmed this prediction: Precautionary rules elicited high levels of violation detection

whether the violations were accidental or intentional, but performance on social

contracts was lower for accidental violations than for intentional ones. This func-

tional distinction between precautionary and social exchange reasoning was

predicted in advance based on the divergent adaptive functions proposed for these

two systems.

LIMINATING PERMI SSION SCHEMA THEORY (B4)

The preced ing results violate central predictions of permission schema theory.

According to that theory, (1) all permi ssion rules should elicit high levels of violation

detection, whether the permitted action is a beneﬁt or a chore; and (2) all permission

rules should elicit high levels of violation detection, whether the violation was

committed intentiona lly or accidentally. Both predictions fail. Permission rules fail

to elicit high levels of violation detection when the permitted action is neutral or

unpleasant (yet not hazardous). Moreover, people are bad at detecting accidental

violations of permission rules that are social contracts. Taken together, these results

eliminate the hypothesis that the mind contains or develops a permission schema of

the kind postulated by Cheng and Holyoak (1985, 1989).

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ELIMINATING CONTENT-FREE DEONTIC LOGICS (B6)

The same results also falsify hypothesis B6: that cheater detection on social contracts is

caused by a content-free deontic logic (for discussion of this possibility, see Man-

ktelow & Over, 1987; Cosmides & Tooby, 2008a). All the beneﬁt and intentionality

tests described in this section involved deontic rules, but not all elicited high levels of

violation detection.

This same set of results also defeats a related claim by Fodor (2000): that “the

putative cheater detection effect on the Wason task is actually a materials artifact ” (p.

29). This sweeping conclusion is predicated on the (mistaken) notion that the only

evidence for cheater detection comes from experiments in which the control problems

are indicative (i.e., descriptive) conditional rules (a curious mistake because it is

refuted by experiments with deontic controls, which are presented in the single source

Fodor cites: Cosmides & Tooby, 1992). According to Fodor, reasoning from a deontic

conditional rule that is stipulated to hold is more likely to elicit violation detection than

reasoning about a rule whose truth is in question (even though in both cases the

individual is asked to do the same thing: look for rule violations). Fodor’s explanation

for this purported difference is deeply ﬂawed (amo ng other things, it assumes what it

seeks to explain; see Cosmides & Tooby, 2008a, 2008b). But instead of disputing

Fodor’s reasoning, let us consider whether his artifact explanation can account for the

cheater detection results observed. After all, there are many experiments comparing

reasoning on social contracts to reasoning about other deontic conditionals.

According to Fodor, high levels of violation detection will be found for any deontic

rule that speciﬁes what people are (conditionally) required to do (because all involve

reasoning with the law of contradiction). All the permission rules described earlier had

precisely this property, all were stipulated to hold, and, in every case, subjects were

asked to reason from the rule, not about it. If Fodor’s artifact hypothesis were correct,

all of these rules should have elicited good violation detection. But they did not.

Violation detection was poor when the deontic rule lacked a beneﬁt; it was also poor

for social contract rules when the potential violator was accused of making innocent

mistakes rather than intentional cheating. This pattern is predicted by social contract

theory, but not by Fodor’s hypothesis that reasoning from a deontic conditional rule is

sufﬁcient to elicit good violation detection.

B5—that social contract rules elicit good performance merely because we understand

what implications follow from them (e.g., Almor & Sloman, 1996)—is eliminated by the

intention versus accident dissociation. The same social contract rule—with the same

implications—was used in both conditions. If the rule’s implications were understood in

the intention condition, they should also have been understood in the accident condi-

tion. Yet the accident condition failed to elicit good violation detection. Understanding

the implications of a social contract may be necessary for cheater detection (Fiddick et al.,

2000), but the accident results show this is not sufﬁcient.

In short, it is not enough to admit that moral reasoning, social reasoning, or deontic

reasoning is special: The speciﬁcity of design for social exchange is far narrowerin scope.

A NEUROPSYCHOLOGICAL DISSOCIATION BETWEEN

SOCIAL CONTRACTS AND PRECAUTIONS

Like social contracts, precautionary rules are conditional, deontic, and involve

subjective utilities. Moreover, people are as good at detecting violators of

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precautionary rules as they are at detecting cheaters on social contracts. This has led

some to conclude that reasoning about social contracts and precau tions is caused

by a single more general mechanism (e.g., general to permissions, to deontic rules, or

to deontic rules involving subjective utilitie s; Cheng & Holyoak, 1989; Manktelow &

Over, 1988, 1990, 1991; Sperber et al., 1995). Most of these one-mechanism theories

are undermined by the series of very precise, functional dissociations between

social exchange reasoning and reasoning about other deontic permission rules

(discussed earlier). But a very strong test, one that addresses all one-mechanism

theories, would be to ﬁnd a neural dissociation between social exchange and

precautionary reasoning.

NE MECHANISM OR TWO?

If reasoning about social contracts and precautions is caused by a single mechanism,

then neurological damage to that mech anism should lower performance on both types

of rule. But if reasoning about these two domains is caused by two functionally distinct

mechanisms, then it is possible for social contract algorithms to be damaged while

leaving precau tionary mechanisms unimpaired, and vice versa.

Stone et al. (2002) developed a battery of Wason tasks that tested social contracts,

precautionary rules, and descriptive rules. The social contracts and precautionary

rules elicited equally high levels of violation detection from normal subjects (who got

70% and 71% correct, respectively). For each subject, a difference score was calculated:

percentage correct for precautions minus percentage correct for social contracts. For

normal subjects, these difference scores were all close to zero (Mean = 1.2 percentage

points, SD = 11.5).

Stone et al. (2002) administered this battery of Wason tasks to R. M., a patient with

bilateral damage to his medial orbitofrontal cortex and anteri or temporal cortex

(disconnecting both amygdalae). R. M.’s performance on the precaution problems

was 70% correct: equivalent to that of the normal controls. In contrast, his performance

on the social contract problems was only 39% correct. R. M.’s difference score

(precautions minus social contracts) was 31 percentage points. This is 2.7 standard

deviations larger than the average difference score of 1.2 percentage points found for

control subjects (p < .005). In other words, R. M. had a large deﬁcit in his social contract

reasoning, alongside normal reasoning about precautionary rules.

Double dissociations are helpful in ruling out differences in task difﬁculty as a

counterexplanation for a given dissociation (Shallice, 1988), but here the tasks were

perfectly matched for difﬁculty. The social contracts and precautionary rules given

to R. M. were logically identical, posed identical task demands, and were equally

difﬁcult for normal subjects. Moreover, because the performance of the normal

controls was not at ceiling, ceiling effects could not be masking real differences in

the difﬁculty of the two sets of problems. In this case, a single dissociation licenses

inferences about the underlying mental structures. R. M.’s dissociation supports

the hypothesis that reasoning abou t social exchange is caused by a different

computational system than reasoning about precautionary rules: a two-mecha-

nism account.

Although tests of this kind cannot conclusively establish the anatomical location of

a mechanism, tests with other patients suggest that damage to a circuit connecting

anterior temporal cortex to the amygdalae was important in creating R. M.’s selective

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deﬁcit.

Recent functional imaging (fMRI) studies also support the hypothesis that

social contract reasoning is supported by different brain are as than precautionary

reasoning, and imply the involvement of several brain areas in addition to temporal

cortex (Ermer, Guerin, Cosmides, Tooby, & Miller, 2006; Fiddick, Spampinato, &

Grafman, 2005; Reis, Brackett, Shamosh, Kiehl, Salovey, & Gray, 2007; Wegener, Lund,

Hede, Ramsøy, Baaré, & Paulson, 2004).

LIMINATING ONE-MECHANISM HYPO THESE S (B6–B8; B1–B4)

Every alternative explanation of cheater detection proposed so far claims that

reasoning about social contrac ts and precautions is caused by the same neurocognitive

system. R. M.’s dissociation is inconsistent with all of these one-mechanism accounts.

These accounts include mental logic (Rips, 1994), mental models (Johnson-Laird &

Byrne, 1991), decisio n theory/optimal data selection (Kirby, 1994; Oaksford & Chater,

1994), permission sch ema theory (Cheng & Holyoak, 1989), relevance theory (Sperber

et al., 1995),

and Manktelow and Over’s (1991, 1995) view implicating a system that is

general to any deontic rule that involves subjective utilities. (For further evidence

against relevance theory, see Fiddick et al., 2000; for further evidence against

Manktelow & Over’s theory, see Fiddick & Rutherford, 2006.)

Indeed, no other reasoning theory even distinguishes between precautions and

social contract rules; the distinction is derived from evolutionary-functional analyses

and is purely in terms of content. These results indicate the presence of a very narrow,

content-sensitive cognitive specialization within the human reasoning system.

PRECOCIOUS DEVELOPMENT OF SOCIAL EXCHANGE REASONING

Children understand what counts as cheating on a soci al contract by age 3 (Harris &

Núñez, 1 996; Harris, Núñez, & Brett, 2001; Núñez & Harris, 1998a).

This has been

shown repeatedly in experiments by Harris and Núñez using an evaluation task: a

task in which the child must decide when a character is violating a rule. Consider, for

example, a story in which Carol wants to ride her bicycle but her mom says, “If you

ride your bike, then you must wear an apron.” This rule restricts access to a beneﬁt

(riding the bike) based on whether the child has satis ﬁed an arbitrary requirement. The

child is then shown four pictures (Carol riding the bike wearing an apron, Carol riding

without an apron, Carol wearing an apron but not riding, and Carol not riding or

wearing an apron) and asked to choose the picture in which Carol is doing something

naughty. British 3-year-olds chose the correct picture (Carol riding the bike with no

apron) 72% to 83% of the time; 4-year-olds, 77% to 100% of the time (Harris & Núñez,

1996; Harris et al., 2001; Núñez & Harris, 1998a). These performance levels were found

Stone et al. (2002) tested two other patients with overlapping but different patterns of brain damage. R. B.

had more extensive bilateral orbitofrontal damage than R. M., and had some anterior temporal damage as

well, but his right temporal pole was largely spared (thus he did not have bilateral disconnection of the

amygdalae): His scores were 85% correct for precautions and 83% correct for social contracts. B. G. had

extensive bilateral temporal pole damage compromising (though not severing) input into both amygdalae,

but his orbitofrontal cortex was completely spared: He scored 100% on both sets of problems.

For a full account of the problems relevance theory has explaining social contract reasoning, see Fiddick

et al., 2000.

Younger children have not been tested yet.

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whether the social contract emanated from the mother or was a consensual swap

between two c hildren; that is, the rule did not have to be imposed by an authority

ﬁgure. A variety of tests showed that, for social contracts, children understood that

taking the beneﬁt was conditional on meeting the requirement. They were not merely

looking for cases in which the requirement was not met; they were looking for cases in

which the beneﬁt was taken and the requirement was not met. The same effects were

found for preschoolers from the United Kingdom, Colombia, and (with minor

qualiﬁcations) rural Nepal.

The performance of the preschoolers was adultlike in other ways. Like adults, the

preschoolers did well whether the social contract was familiar or unfamiliar. Also like

adults, intentionality mattered to the children. Núñez and Harris (1998a) varied

(1) whether the character had taken the beneﬁt or not and (2) whether the character

had failed to fulﬁll the requirement by accident or deliberately. Children were far more

likely to say the character had been naughty when the breach was intentional than

accidental. Four-year-olds deemed social contrac t violations naughty 81% of the time

when they were intentional ver sus 10% of the time when they were accidental; for

3-year-olds, the ﬁgures were 65% versus 17%, respectively. Children also could match

emotions to outcomes for reciprocal exc hanges: Given an agreement to swap, they

understood that the victim of cheating would feel upset, and that both children would

be happy if the swap was completed (Núñez, 2011).

Moreover, the children tested by Harris and Núñez (1996) showed the same

dissociation between social contract and descriptive rules as adults: 3 - to 4-year-

olds chose the correct violation condition only 40% of the time for descriptive rules but

72% to 83% of the time for social contracts. By age 5, children could solve a full-array

Wason selection task when the rule was a social contract (Núñez & Harris, 1998b;

performance limitations, rather than competence problems, interfered with the Wason

performance of the preschoolers).

CROSS-CULTURAL INVARIANCES AND DISSOCIATIONS IN

SOCIAL EXCHANGE REASONING

Cognitive neuroscientists have long been aware that neural dissociations are useful for

elucidating mental structure. But cultural dissociations may provide a uniquely

informative source of converging evidence. Because the ontogenetic experience of

people in different cultures varies widely, cross-cultural studies allow one to see

whether differences in ontogenetic experience are associated with differences in

mental structure.

Most psychologists and anthropologists believe that high-level cognitive compe-

tences emerge from general-purpose cognitive abilities trained by culturally speciﬁc

activities, rather than as part of our evolved, reliably developing, species-typical

design. That cheater detection should be well developed across cultures is a falsi ﬁable

Although the deﬁnitive experiments have not yet been done, existing evidence suggests that preschoolers

also understand violations of precautionary rules. The rules used by Harris and Núñez (1996) fell into two

categories: pure social contracts (“arbitrary permissions” and “swaps,” in their terminology) and hybrid

rules (ones that can be interpreted either as social contracts or precautionary). The hybrids were rules that

restricted access to a beneﬁt on the condition that a precaution was taken, for example, If you play outside, you

must wear a coat (to keep warm). Cummins (1996) tested a more purely precautionary rule, but the context

still involved restrictions on access to a beneﬁt (playing outside).

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prediction of the evolutionary account, which posits that this competence should be

distributed in a species-typical, human universal fashion. More precisely, because

detecting cheaters is necessary for social exchange to be an ESS, the development of

cheater detection should be buffered against cultural variation and, therefore, be

uniform. In contrast, the development of ESS-irrelevant aspects of performance (e.g.,

interest in acts of generosity) is under no selection to be uniform across cultures and

should, therefore, be free to vary with cultural circumstance.

Sugiyama et al. (2002) tested these predictions among the Shiwiar, a hunter-

horticultural population in a remote part of the Ecuadorian Amazon. Good cheater

detection had already been established in the United S tates, Europe, Hong Kong,

and Japan. But adults in advanced market economies engage in more trade—

especially with strangers—than people who hunt and garden in remote parts of

the Amazon. Anonymity facilitates cheating; markets increase the volu me of

transactions experienced by each individual. If no evolved specialization is

involved—that is, if general-purpose processes induce a cheater detection sub-

routine through repeated experience with cheating—then this subroutine might

not be found outside the Western world.

The Shiwiar were raised and continue to live in a culture as different from that of

American college students as any on the planet. Nevertheless, Shiwiar were just as

good at detecting cheaters on Wason tasks as Harvard undergraduates were

(Figure 25.6). For cheater-relevant cards, the performance of Shiwiar hunter-horti-

culturalists was identical to that of Harvard students. Shiwiar differed only in that

they were more likely to also show interest in cheater-irrelevant cards—the ones that

could reveal acts of generosity. (Their excellence at cheater dete ction did no t resu lt

from indiscriminate interest in all cards. Controlling for logical category, Shiwiar were

more than twice as likely to choose a card when it was cheater-relevant than when it

was not; p < .005.) In short, there was no dissociation between cultures in the parts of

the mechanism necessary to its performing its evolved function. The only “cultural

dissociation” was in ESS-irrelevant aspects of performance.

Is cheater detection invariant because the sociocultural experience of Shiwiar

and American su bjects is too similar to cause differences in reasoning perform-

ance? Clearly not; if that were true, the two populations would perform identi-

cally on cheater-irrelevant cards as well as on cheater-relevant ones. That did not

happen.

This is the only research we know of to show identical performance across very

different cultural groups on those aspects of a reasoning problem that are relevant to

a cognitive adaptation functioning as an evolutionarily stable strategy, yet different

performance on those aspects that are irrelevant to the adaptation functioning as an

ESS. That performance in detecting cheaters was invariant across very disparate

cultural settings suggests that the brain mechanism responsible is a reliably devel-

oping neurocognitive system. That is, its development is canalized in a way that

buffers it against idiosyncratic variations in ontogenetic experience.

DOES DOMAIN-GENERAL LEARNING BUILD THE SPECIALIZATION

FOR SOCIAL EXCHANGE?

The empirical evidence reviewed earlier strongly supports the claim that reasoning

about social exchange is caused by neurocognitive machinery that is specialized for

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this function in adults: social contract algorithms. This conclusion was supported not

just by evidence from Wason tasks but also from experimental economics games,

moral reasoning protocols, emotion attribution tasks, and developmental studies.

What makes the Wason results particularly interesting, however, is that the Wason

task requires information search. The Wason results indicate the presence of a

subroutine that is narrowly specialized for seeking out information that would reveal

the presence of cheate rs. This subroutine is not designed to seek out information that

would reveal the presence of cheating (when this occurs by mistake), or permission

violations, or violations in general.

But how was this very precisely designed computational specialization produced?

Are the developmental mechanisms that build social contrac t algorithms domain-

speciﬁc and specialized for this function? Or are social contract specializations in

adults built by domain-general learning mechanisms?

100

Percent

P Q Not-P

Benefit Accepted

Requirement Not Met

Cheater Irrelevant CardsCheater Relevant Cards

Benefit Not Accepted

Requirement Met

Standard

QNot-Q PNot-P Not-Q

Shiwiar

Harvard

SwitchedStandardSwitched

SwitchedStandardSwitchedStandard

Figure 25.6 Performance of Shiwiar Hunter-Horticulturalists and Harvard Undergraduates on

Standard and Switched SocialContracts(percent of subjects choosing each card). There was

no difference between the two populations in their choice of cheater relevant cards(beneﬁt

accepted, requirement not satisﬁed). They differed only in their choice of cheater-irrelevant

cards(Shiwiar showing more interest in cards that could reveal acts of generosity or fair play).

Shiwiar high performance on cheater-relevant cards is not caused by indiscriminate intere

stin

all cards. Holdinglogical category constant, Shiwiar always chose a card more frequently when

it was relevant to cheater detection than when it was not.This can be shown by comparing

performance on standard versusswitched social contracts(e.g., the P card is cheater relevant

for a standard social contract,but not for a switched one;see Figure 25.4).

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If computational specializations for social exchange are acquired via some general-

purpose learning process, then we shoul d not claim that the specialization is an

evolved adaptation for social exchange. Instead, the social exchange specialization

would be the product of a learning mechanism that evolved to solve a different,

perhaps more general, adaptive problem.

ENERAL PUR POSE LEARNING ISANONSTARTER

Evidence of an adaptive specialization in the adult human mind often meets the

following rejoinder: Although the adult mechanism is specialized, the mechanisms

that built it are not—the adult specialization was acquired via a general purpose

learning process (e.g., Elman et al., 1996; Gauthier & Tarr, 2002; Orr, 2003; Rumelhart &

McClelland, 1986; for discussion, see Duchaine, 2001; Duchaine, Yovel, Butterworth, &

Nakayama, 2006; Pinker, 2002; Tooby & Cosmides, 1992).

There is a fundamental problem with this view: No general purpose learning

process is known to science (Gallistel, 2000). This is not because scientists are in the

dark about ani mal learning. Learning processes specialized for solving speciﬁc

adaptive problems have been found in many species, including dead reckoning in

desert ants, learned food aver sions in rats, star navigation in birds, snake fear in

primates, and language acquisition in humans (Gallistel, 1990, 2000; Garcia, 1990;

Garcia & Koelling, 1966; Mineka & Cook, 1993; Pinker, 1994). Indeed, even classical

conditioning, considered by many to be the premier example of general purpose

learning, is anything but (Staddon, 1988). The empirical evidence shows that this form

of learning is adaptively specialized for a speciﬁc computational task common in

foraging and predator avoidance: multivariate nonstationary time series anal ysis

(Gallistel & Gibbon, 2000).

Classical and operant conditioning are adaptive specializations, but it is true that

they operate over inputs from many different domains (i.e., they are somewhat

content-general). So let us reframe the re joinder thus: Are adult specializations for

reasoning about social exchange acquired via classical or operant conditioning?

At the root of operant and classical conditioning is the ability to respond

contingently to reward and punishment (Gallistel & Gibbon, 2000; Staddon,

1988). Social exchange entails such contingencies: I o ffer to provide a bene ﬁtto

you, contingent on your satisfying a requirement that I specify. I impose that

requirement in the hope that your satisfying it will create a situation that beneﬁts

me in some way.

Yet the ability to respond contingently to reward and punishment is not sufﬁcient

for social exchange to emerge in a species. All animal species can be classically and

operantly conditioned (Staddon, 1988), but few species engage in social exchange.

If classical and/or operant conditioning caused the acquisition of social exchange

specializations, then social exchange should be zoologically widespread. The fact

that it is so rare means that it is not the cons equence of any behavior-regulatio n or

learning process that is zoologically common.

Although reciprocity is rare in the animal kingdom, it is found in a number of

nonhuman primate species (Brosnan & de Waal, 2003; de Waal, 1989, 1997a, 1997b;

de Waal & Luttrell, 1988). Its presence in other primates means that social exchange

behavior can arise in the absence of language. This means the conditioning hypoth-

esis cannot be rescued by arguing that the development of social exchange requires

the joint presence of language and conditioning mechanisms.

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STANDARD ECONOMIC MODELS CANNOT EXPLAIN THE RESULTS (B9)

Can the development of neurocognitive specializations for reasoning about social

exchange be accounted for by the fact that reciprocity is economically advantageous?

An economic folk theory exists and was articulated by Orr (2003, p. 18):

An evolutionarypsychologist might counter that the fact that a behavior conforms so closely

to what’s expected of an adaptive one is evidence that it’s a bona ﬁde biological adaptation.

And here we arrive at another problem. For the same logic that makes a behavior

evolutionarily advantageous might also make it “economically” advantageous....

The point is that when evolutionary and economic considerations yield the same prediction,

conformity to Darwinian predictions cannot be taken as decisive.

This would be a good point if economists had a theory of the computations that give

rise to economic learning and decision making. But they do not. Having no account of

how economic reasoning is accomplished, econo mists have relied on a Homo eco-

nomicus (economic man) model, an as if approach. According to Homo economicus

models, people reason as if they were equipped with neurocognitive mechanisms that

compute (in some as yet unspeciﬁed way) the subjective expected utility of alternative

actions, and choose the one that maximizes personal utility (Savage, 1954).

Homo economicus models make very precise predictions about the choices people

should make when engaging in social exchange and other economic games. Contrary

to Orr’s assumption, however, these economic models and the evolutionarily func-

tional theory of social exchange make different predictions about human behavior

(Delton, Krasnow, Cosmides, & Tooby, 2011; Hoffman, McCabe, & Smith, 1998). There

is now a large body of results from experimental economics showing that people

rarely behave as the Homo economicus model predicts and that this is not due to

inexperience with the experimental situation—even experienced subjects violate the

model’s predictions (e.g., Fehr & Gächter, 2000a, 2000b; Henrich et al., 2005; Hoffman

et al., 1998; Krasnow, Cosmides, Pedersen, & Tooby, 2012). For example, when given

the opportunity to engage in social exchange, people routinely and systematically

choose to cooperate with others when they would earn a higher payoff by defecting;

they also punish acts of cheating when they would earn more by not doing so. That is,

they cooperate and punish in circumstances, such as the one-shot Prisoners’ Dilemma,

where these choices are not util ity maximizing (Hoffman et al., 1998). As Hoffman

et al. (1998) argue, these are precisely the responses one would expect of specializa-

tions designed to operate in small hunter-gatherer bands, where repeated interactions

are the norm and one-shot interactions are rare (for agent-based simulations support-

ing this point, see Delton et al., 2011; Krasnow, Delton, Tooby, & Cosmides, 2013). The

results reported earlier on accidenta l versus intentional violations of social contracts

are also inconsistent with economic prediction. Economic man theories predict

mechanisms that respond to the payoff structure of situations, not to intentions,

and cheating produces the same negative payoff whether it was accidental or

intentional. Thus, a system designed for maximizing utility should detect cheating,

not cheaters. Yet that is not the empirical ﬁnding.

Rational or economically advantageous has to refer to some kind of reasoning process if

it is to serve as an explanation of anything, and the most comple tely axiomatized

normative model of rational economic behavior fails to predict or explain the

facts of when humans choose to cooperate and punish, either in social exchange

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(Hoffman et al., 1998) or in public good s games (Fehr & Gächter, 2000a, 2000b; Henrich

et al., 2005; Kurzban, McCabe, Smith, & Wilson, 2001). Because the facts of social

exchange reasoning and behavior contradict central predictions of this standard

economic model, this economic by-product hypot hesis cannot explain the features

of the neurocognitive specialization found in adults, or the development of these

features (B9 eliminated). In light of this failure, a number of economists are turning

to evolutionar y psychological accounts of social exchange and judgment under

uncertainty to explain human economic behavior (Gigerenzer & Selten, 2001; Hoffman

et al., 1998; Romer, 2000).

TATISTICAL LEARNING AND CONTENT-FREE INDUCTIVE INFERENCE:

ORE DOGS THAT DO NOT BARK (B10)

Various accounts of inductive learning have been proposed: Bayesian learning

machines, connectionist systems that compute a multiple regression , contingency

calculators. Some posit highly domain-speciﬁc, inductive learning systems (e.g.,

Marcus, 2001; Staddon, 1988), but most do not (e.g., Elman et al., 1996; Quartz &

Sejnowski, 1997).

The domain-general proposals foreground the role of content-blind inductive

inference procedures in the construction of mental content.

These extract statistical

relationships from patterns that are objectively present in the external world. Indeed,

they are constrained to do so: The world is the only source of content for these

statistical learning mechanisms. As a result, we should see certain dogs barking. For

example, 20th-century Chicago schoolchildren should fear things that are dangerous

to children living in 20th-century urban Chicago—electric sockets, cars, streets, hot

stoves. The content of their fears should reﬂect the frequency and statistical distribu-

tion of dangers in the modern world becaus e it was constructed by content-free

mechanisms operating on information derived from these distributions.

By contrast, domain-speciﬁc learning mechanisms are content rich: They allow

inferences that go beyond the information given, so the mental content constructed

may be richer than (or merely different from) the statistical distribution of information in

the externalworld of individual experience. For example, when asked what they are most

afraid of, Chicago schoolchildren name lions, tigers, wild animals, “monsters” (danger-

ous but unspeciﬁed animal or humanlike creatures), snakes, and spiders (Maurer, 1965).

The content of their fears reﬂects the statistical distribution of dangers in an ancestral

world they have never experienced (Marks, 1987). It does not reﬂect the statistical

distribution of dangers in urban Chicago—that is, the modern dogs are not barking.

People reliably develop—apparently by age 3—social contract algorithms with the

properties discussed in this review. These properties make that neurocognitive system

very good at solving an adaptive problem of the ancestral world: see king out

information that would reveal cheaters. We know there is good design for this

ancestral problem because very precise patterns of dissociations by con tent—both

functional and neural—were predicted in advance of their discovery on the basis of

ESS analyses applied to the behavioral ecology of hunter-gatherers. However,

Attentional biases (e.g., for faces) play a role in some of the domain-general theories (e.g., Elman et al.,

1996), but these are thought to be few in number and, crucially, to not contain the mental content that is

eventually constructed (the source of which is patterns in the world).

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statistical learning theories cannot even retrodict this pattern of dissociations (let alone

predict them in advance).

The explanatory variables that drive statistical learning are experience, repetition,

and their consequence, familiarity. If these variables caused the development of

reasoning specializations, we should observe a different set of reasoning specializations

than are found, including ones that produce good violation detection for permission

rules and even descriptive ones. But these modern dogs are not barking either.

Where Is the Specialization for Finding Violations of Descriptive Rules? Descriptive

rules are not rare, exotic occurrences. They are claims about how the world works,

commonplaces of everyday conversation (If you wait until November, the cl inic will be out

of ﬂu shots. If she eats hot chili, she likes a cold beer. If you use that pan, the casserole will stick.

If you wash with bleach, your clothes will be whiter.). Actio ns are more likely to succeed

when they are based on true rather than false information, so violations of these claims

should be salient. Consistent with this, people do know what counts as a violation:

They can tell you that cases in which P happens but Q does not violate a descriptive

rule, even when the rule is abstract or unfamiliar (Manktelow & Over, 1987).

But this knowledge does not translate into efﬁcacious information search. Although

people recognize violations of descriptive rules when they occur, they do not seek out

information that could reveal such violations, even when they are explicitly asked to

do so on a Wason task (see instructions for Figure 25.1; for discussion, see Fiddick

et al., 2000; Cosmides & Tooby, 2008a). That is, humans do not reliably develop

reasoning specializations that cause them to look for potential violations of descriptive

rules. This dissociation between people’s knowledge and what information they

search for is found for descriptive rules but not for social contracts. Descriptive rules

are ubiquitous. If experience with a type of rule were sufﬁcient for statistical learning

to build a specialization for information search, then we should observe good violation

detection on Wason tasks using descriptive rules (even unfamiliar ones), just as we do

for social contracts.

Even worse, experience with speciﬁc descriptive rules does nothing to improve

performance. Early research using the Wason task explored whether violation detec-

tion for descriptive rules was better when the rule, relation, or any of its terms were

familiar. It was not (Cheng et al., 1986; Cosmides, 1985; Manktelow & Evans, 1979;

Wason, 1983). Furthermore, people who had repeated experience with instances that

violated a particular concrete rule performed no better than people who did not have

these experiences (Manktelow & Evans, 1979). The impotence of repeated experience

with concrete violations is mirrored in the social contract results, where high per-

formance is observed regardless of experience. College students are intimately

familiar with rules restricting access to alcohol (e.g., If you drink beer, then you must

be over 21), and break them regularly, yet Cosmides (1985) found they are no better at

detecting violations of this familiar rule than they are for never-experienced rules

about cassava root and tattoos.

Where Is the Specialization for Finding Violations of Permission Rules? The failure of

statistical learning theo ries becomes even clearer when we consider that social

exchange rules are but a small su bset of all permission rules (which are, in turn, a

subset of deontic rules, which are thems elves a subset of all conditional rules). By

classinclusion,humansnecessarilyhavefarmoreexperiencewithpermissionrules

than with social contracts (legend, Figure 25.5). It was on this basis that Cheng and

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Holyoak (1985, 1989) argued that domain-general inductive processes should pro-

duce the more abstract and inclusive permission schema, rather than social contract

algorithms, and that this schema should operate not only on social contracts but also

on precautionary rules and indeed on any social norm that gives conditional

permission. Yet careful tests sho wed th at the permission schema they p redicte d

does not exist.

Poor performance in detecting violati ons of conditional permission rules drawn

from the white zone of Figure 25.5 cannot be explained by claiming that all the

permission rules we happen to encounter are either social contracts or precautions.

Conditional social norms that ﬁt neither category permeate our society (If one eats red

meat, then one drinks red wine. If you live east of Milpas Street, then vote at Cleveland

Elementary School. If the blue inventory form is ﬁlled out, ﬁle it in the metal bin. See, e.g.,

Cosmides et al., 2010, Exp 2.). Yet we do not develop information search strategies

specialized for detecting violations of such rules.

Where Is the Specialization for Detecting Negative Payoffs? Statistical learning theorists

might respond by saying that learning occurs in response to negative payoffs (see

Manktelow & Over, 1995, for a related proposal). This view predicts an information

search specialization for detecting when a negative payoff might occur, wheth er it is

produced by cheating on a social contract or failing to take precautions in hazardous

situations (Manktelow & Over, 1991, 1995).

Fiddick and Rutherford (2006) show that no such specialization exists: Information

search on Wason tasks using social contracts and related rules bears no relationship to

subjects’ judgments about which outcomes produce negative payoffs. Moreover, R.

M.’s neural dissociation (preserved search for violations of precautionary rule s with

impaired search for cheaters) shows that the mind does not contain a unitary

specialization for detecting negative payoffs.

Where Is the Specialization for Detecting Cheating, Rather Than Cheaters? What if

statistical learning is triggered by negative payoffs, but only within the doma in of

social exchange? (This is hardly a domain-general proposal, but never mind.) A person

can be cheated—receive a negative payoff due to the violati on of a social exchange

agreement—by accident or by intention . Both kinds of violation damage personal

utility, both are useful to detect, and both require detection if the participant in an

exchange is to get what he or she wants and is entitled to. Moreover, because innocent

mistakes and intentional cheating both result in someone being cheated, situations in

which a person was cheated are statistically more common than situations in which

someone was cheated by a cheater. Hence, this domain-restricted version of statistical

learning predicts the development of an information search specialization that looks

for acts in which someone was cheated, regardless of cause. This specialization would

be easy to engineer: A mechanism that indiscriminately scrutinizes cases in which the

beneﬁt was accepted and cases in which the requirement was not met would reveal

both accidental and intentional violations. But this specialization does not exist: People

are not good a t detecting acts of cheating when there is evidence that they occurred by

accident rather than intention.

In contrast, it is speciﬁcally the detection of intentional cheaters that makes

contingent exchange evolutionarily stable against exploitation by cheaters (i.e., an

ESS). That people are good at detecti ng intentional cheating but not accidental

mistakes is a unique pred iction of the evolutionary task analysis of exchange.

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Variables T hat Affect Statistical Learning Do Not Seem to Affect the Development of C heater

Detection An information search specialization for detecting cheaters reliably devel-

ops across large variations in experience, repetition, and familiarity. For example:

• Precocious performance is neither necessary nor sufﬁcient for sustaining an

adaptationist hypothesis (Cosmides & Tooby, 1997). It is, however, relevant for

evaluating claims of content-free inductive learning because these predict that

the development of reasoning skills will reﬂect the child’s experience (e.g.,

Markman, 1989). The early age at which children understand social exchange

reasoning undermines the hypothesis that social contract specializations were

constructed by content-independent procedures operating on individual

experience.

• Preschool-age children are not noted for the accuracy and consistency of their

reasoning in many domains, even ones with which they have considerable

experience. For exa mple, many children this age will say that a raccoon can

change into a skunk; that there are more daisies than ﬂowers; that the amount of

liquid changes when poured from a short fat beaker into a tall thin one; that they

have a sister but their sister does not (Boden, 1980; Carey, 1984; Keil, 1989; Piaget,

1950). When reasoning about social exchange, however, preschool-age children

show virtually all the features of special design that adults do.

• When a child has had experience in a number of domains, it is difﬁcult to explain

how or why a content-blind statistical learning mechanism would cause the early

and uniform acquisition of a reasoning skill for one of these domains, yet fail to

do so for the others. When on e considers that adults have massive experience

with permission rules, yet fail to develop specializations for detecting violations

of this more general and, therefore, more common class, the presence of accurate

cheater detection in 3- and 4-year-olds is even more surprising.

• Cultural experience is often invoked as a schema-building factor. Yet, des pite a

massive difference in expe rience with trade and cheating, there was no difference

between Shiwiar and American adults in c heater detection.

Statistical Learning Summary Neither experience, repetition, nor familiarity explain

which reasoning skills develop and which do not, yet they should if specializations

develop via statistical learning. In contrast, the hypothesis that social contract

algorithms were built by a developmental process designed for that function neatly

accounts for all the developmental facts: that cheater detection develops invariantly

across widely divergent cultures (whereas other aspects dissociate); that social

exchange reasoning and cheater detection develop precocially; that the mechanisms

responsible operate smoothly regardless of experience and familiarity; that they detect

cheaters and not other kinds of violators; and that the developmental process results in

a social contract specialization rather than one for more inclusive classes such as

permission rules.

CONCLUSIONS

There are strict standards of evidence for claimi ng that an organic syste m is an evolved

adaptation. The system that causes reasoning about social exchange meets these

standards. Reasoni ng about social exchange narrowly dissociates from other fo rms of

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reasoning, both cognitively and neurally. The pattern of results reveals a system

equipped with exactly those computational properties necessary to produce an

evolutionarily stable form of cond itional helping (as opposed to the many kinds of

unconditional helping that are culturally encouraged). These properties include, but

are not limited to, the six design features discussed herein, all of which were predicted

in advance from the task analyses contained in social contract theory (see Cosmides &

Tooby, 1992, 2008a, 2008b; Fiddick et al., 2000 for others). Importantly, the pattern of

results cannot be explained as a by-pr oduct of a reasoning adaptation designed for

some different, or more general, function. Every by-product hypothesis proposed in

the literature has been tested and eliminated as an explanation for social exchange

reasoning (see Table 25.1).

The design of the computational specialization that causes social exchange reason-

ing in adults (and preschoolers) places limits on any theory purporting to account for

its development. No known domain-general process can account for the fact that

social contract specializations with these particular design features reliably develop

across cultures, whereas specializations for more commonly encountered reasoning

problems do not develop at all. Indeed, the social contract specialization has properties

that are better adapted to the small-group living conditions of ancestral hunter-

gatherers than to modern industrial societies. Experience of the world may well be

necessary for its development during ontogeny, but the developmental process

implicated appears to be a domain-speciﬁc one, designed by natural selection to

produce an evolutionarily stable strategy for conditional helping.

The simplest, most parsimonious explanation that can account for all the results—

developmental, neuropsychological, cognitive, and behavioral—is that the human

brain contains a neurocognitive adaptation designed for reasoning about social

exchange. Because the developmental process that builds it is specialized for doing

so, this neurocognitive specialization for social exchange reliably develops across

striking variations in cultural experience. It is one component of a complex and

universal human nature.

REFERENCES

Almor, A., & Sloman, S. (1996). Is deontic reasoning special? Psychological Review, 103, 374–380.

Axelrod, R. (1984). The evolution of cooperation. New York, NY: Basic Books.

Axelrod, R., & Hamilton, W. D. (1981). The evolution of cooperation. Science, 211, 1390–1396

Barrett, H. C. (1999, June). Guilty minds: How perceived intent, incentive, and ability to cheat inﬂuence

social contract reasoning. 11th annual meeting of the Human Behavior and Evolution Society, Salt Lake City,

Utah.

Beaman, C. (2002). Why are we good at detecting cheaters? A reply to Fodor. Cognition, 83(2), 215–220.

Boden, M. (1980). Jean Piaget. New York, NY: Viking.

Bonatti, L. (1994). Why should we abandon the mental logic hypothesis? Cognition, 50,17–39.

Boyd, R. (1988). Is the repeated prisoner’s dilemma a good model of reciprocal altruism? Ethology and

Sociobiology, 9, 211–222.

Boyer, P., & Lienard, P. (2006). Why ritualized behavior in humans? Precaution systems and action-parsing

in developmental, pathological, and cultural rituals. Behavioral and Brain Sciences, 29,1–56.

Brosnan, S. F., & de Waal, F. B. M. (2003). Monkeys reject unequal pay. Nature, 425, 297–299.

Carey, S. (1984). Cognitive development: The descriptive problem. In M. S. Gazzaniga (Ed.), Handbook of

cognitive neuroscience (pp. 37–66) New York, NY: Plenum Press.

Cashdan, E. (1989). Hunters and gatherers: Economic behavior in bands. In S. Plattner (Ed.), Economic

anthropology (pp. 21–48) Stanford, CA: Stanford University Press.

Cheng, P., & Holyoak, K. (1985). Pragmatic reasoning schemas. Cognitive Psychology, 17, 391–416.

Adaptations for Reasoning About Social Exchange 663

3GC25 06/13/2015 2:45:19 Page 664

Cheng, P., & Holyoak, K. (1989). On the natural selection of reasoning theories. Cognition, 33, 285–313.

Cheng, P., Holyoak, K., Nisbett, R., & Oliver, L. (1986). Pragmatic versus syntactic approaches to training

deductive reasoning. Cognitive Psychology, 18, 293–328

Cosmides, L. (1985). Deduction or Darwinian algorithms? An explanation of the “elusive” content effect on the

Wason selection task (Doctoral dissertation). Department of Psychology, Harvard University (UMI No.

86–02206).

Cosmides, L. (1989). The logic of social exchange: Has natural selection shaped how humans reason? Studies

with the Wason selection task. Cognition, 31, 187–276.

Cosmides, L., Barrett, H. C., & Tooby, J. (2010). Adaptive specializations, social exchange, and the evolution

of human intelligence. Proceedings of the National Academy of Sciences, USA, 107, 9007–9014. doi: 10.1073/

pnas.0914623107

Cosmides, L., & Tooby, J. (1987). From evolution to behavior: Evolutionary psychology as the

missing link. In J. Dupre (Ed.), The latest on the best: Essays on evolution and optimality. Cambridge,

MA: MIT Press.

Cosmides, L., & Tooby, J. (1989). Evolutionary psychology and the generation of culture: Part II. Case study:

A computational theory of social exchange. Ethology and Sociobiology, 10,51–97.

Cosmides, L., & Tooby, J. (1992). Cognitive adaptations for social exchange. In J. Barkow, L. Cosmides, & J.

Tooby (Eds.), The adapted mind (pp. 163–228) New York, NY: Oxford University Press.

Cosmides, L., & Tooby, J. (1997). Dissecting the computational architecture of social inference mechanisms.

In Characterizing human psychological adaptations (Ciba Foundation Symposium #208) (pp. 132–156) Chi-

chester, UK: Wiley.

Cosmides, L., & Tooby, J. (1999). Toward an evolutionary taxonomy of treatable conditions. Journal of

Abnormal Psychology, 108, 453–464.

Cosmides, L., & Tooby, J. (2004). Knowing thyself: The evolutionary psychology of moral reasoning and

moral sentiments. In R. E. Freeman & P. Werhane (Eds.), Business, science, and ethics: The Rufﬁn series (No.

4, pp. 93–128) Charlottesville, VA: Society for Business Ethics.

Cosmides, L., & Tooby, J. (2005). Social exchange: The evolutionary design of a neurocognitive system. In M.

S. Gazzaniga (Ed.), The new cognitive neurosciences, III. Cambridge, MA: MIT Press.

Cosmides, L., & Tooby, J. (2008a). Can a general deontic logic capture the facts of human moral reasoning?

How the mind interprets social exchange rules and detects cheaters. In W. Sinnott-Armstrong (Ed.),

Moral psychology (pp. 53–119) Cambridge, MA: MIT Press.

Cosmides, L., & Tooby, J. (2008b). When falsiﬁcation strikes: A reply to Fodor. In W. Sinnott-Armstrong

(Ed.),

Moral psychology (pp. 143–164) Cambridge, MA: MIT Press.

Cummins, D. D. (1996). Evidence of deontic reasoning in 3- and 4-year-old children. Memory and Cognition,

24, 823–829.

Dawkins, R. (1986). The blind watchmaker. New York, NY: Norton.

de Waal, F. (1989). Food sharing and reciprocal obligations among chimpanzees. Journal of Human Evolution,

18, 433–459.

de Waal, F. (1997a). The chimpanzee’s service economy: Food for grooming. Evolution and Human Behavior,

18, 375–386.

de Waal, F. (1997b). Food transfers through mesh in brown capuchins. Journal of Comparative Psychology, 111,

370–378.

de Waal, F., & Luttrell, L. (1988). Mechanisms of social reciprocity in three primate species: Symmetrical

relationship characteristics or cognition? Ethology and Sociobiology, 9, 101–118.

Delton, A., Krasnow, M., Cosmides, L., & Tooby, J. (2011). Evolution of direct reciprocity under uncertainty

can explain human generosity in one-shot encounters. Proceedings of the National Academy of Sciences,

USA, 108, 13335–13340.

Duchaine, B. (2001). Computational and developmental speciﬁcity in face recognition: Testing the alternative

explanations in a developmental prosopagnosic (Doctoral dissertation). Department of Psychology, Univer-

sity of California, Santa Barbara.

Duchaine, B., Yovel, G., Butterworth, E., & Nakayama, K. (2006). Prosopagnosia as an impairment to face-

speciﬁc mechanisms: Elimination of the alternative hypotheses in a developmental case. Cognitive

Neuropsychology, 23, 714–747.

Dugatkin, L. A. (1997). Cooperation among animals: A modern perspective. New York, NY: Oxford University

Press.

Ehrlich, P. (2002). Human natures: Genes, cultures, and the human prospect. Washington, DC: Island Press.

Elman, J., Bates, E., Johnson, M. H., Karmiloff-Smith, A., Parisi, D., & Plunkett, K. (1996). Rethinking

innateness: Connectionism in a developmental context. Cambridge, MA: MIT Press.

664 GROUP LIVI NG:COOPERATION AND C ONFLICT

3GC25 06/13/2015 2:45:19 Page 665

Ermer, E., Guerin, S., Cosmides, L., Tooby, J., & Miller, M. (2006). Theory of mind broad and narrow:

Reasoning about social exchange engages TOM areas, precautionary reasoning does not. Social Neuro-

science, 1 (3–4), 196–219.

Fehr, E., & Gächter, S. (2000a). Cooperation and punishment in public goods experiments. American Economic

Review, 90, 980–994.

Fehr, E., & Gächter, S. (2000b). Fairness and retaliation: The economics of reciprocity. Journal of Economic

Perspectives, 14, 159–181.

Fiddick, L. (1998). The deal and the danger: An evolutionary analysis of deontic reasoning (Doctoral dissertation).

Department of Psychology, University of California, Santa Barbara.

Fiddick, L. (2003). Is there a faculty of deontic reasoning? A critical re-evaluation of abstract deontic versions

of the Wason selection task. In D. Over (Ed.), Evolution and the psychology of thinking: The debate (pp. 33–60)

Hove, UK: Psychology Press.

Fiddick, L. (2004). Domains of deontic reasoning: Resolving the discrepancy between the cognitive and

moral reasoning literatures. Quarterly Journal of Experimental Psychology, 57A(4), 447–474.

Fiddick, L., Cosmides, L., & Tooby, J. (2000). No interpretation without representation: The role of domain-

speciﬁc representations and inferences in the Wason selection task. Cognition 77,1–79.

Fiddick, L., & Rutherford, M. (2006). Looking for loss in all the wrong places: Loss-avoidance does not

explain cheater detection. Evolution and Human Behavior, 27(6), 417–432. doi: 10.1016/j.evolhumbehav

.2006.05.001

Fiddick, L., Spampinato, M., & Grafman, J. (2005). Social contracts and precautions activate different

neurological systems: An fMRI investigation of deontic reasoning. Neuroimage, 28(4), 778–786.

Fiske, A. (1991). Structures of social life: The four elementary forms of human relations. New York, NY: Free Press.

Fodor, J. (2000). Why we are so good at catching cheaters. Cognition, 75,29–32.

Gallistel, C. R. (1990). The organization of learning. Cambridge, MA: MIT Press.

Gallistel, C. R. (2000). The replacement of general-purpose learning models with adaptively specialized

learning modules. In M. S. Gazzaniga (Ed.), The New Cognitive Neurosciences (pp. 1179–1191) Cambridge,

MA: MIT Press.

Gallistel, C. R., & Gibbon, J. (2000). Time, rate and conditioning. Psychological Review, 107, 289–344.

Garcia, J. (1990). Learning without memory. Journal of Cognitive Neuroscience

, 2(4), 287–305.

Garcia, J., & Koelling, R. A. (1966). Relations of cue to consequence in avoidance learning. Psychonomic

Science, 4, 123–124.

Gauthier, I., & Tarr, M. J. (2002). Unraveling mechanisms for expert object recognition: Bridging brain

activity and behavior. Journal of Experimental Psychology: Human Perception and Performance, 28, 431–446.

Gigerenzer, G., & Hug, K. (1992). Domain speciﬁc reasoning: Social contracts, cheating, and perspective

change. Cognition, 43, 127–171.

Gigerenzer, G., & Selten, R. (Eds.). (2001). Bounded rationality: The adaptive toolbox. Cambridge, MA: The MIT

Press.

Gurven, M. (2004). To give or to give not: The behavioral ecology of human food transfers. Behavioral and

Brain Sciences, 27(4), 543–583. ID code: bbs00001257.

Harris, P., & Núñez, M. (1996). Understanding of permission rules by preschool children. Child Development,

67, 1572–1591.

Harris, P., Núñez, M., & Brett, C. (2001). Let’s swap: Early understanding of social exchange by British and

Nepali children. Memory and Cognition, 29, 757–764.

Hasegawa, T., & Hiraishi, K. (2000). Ontogeny of the mind from an evolutionary psychological viewpoint. In

S. Watanabe (Ed.), Comparative cognitive science of mind (pp. 413–427) Kyoto, Japan: Minerva.

Hauser, M. D. (2007). Moral minds: The nature of right and wrong. New York, NY: Harper.

Henrich, J., Boyd, R., Bowles, S., Gintis, H., Fehr, E., Camerer, C., . . . Henrich, N. (2005). “Economic Man” in

cross-cultural perspective: Ethnography and experiments from 15 small-scale societies. Behavioral and

Brain Sciences, 28, 795–855. doi: 10.1017/S0140525X05000142

Hoffman, E., McCabe, K., & Smith, V. (1998). Behavioral foundations of reciprocity: Experimental economics

and evolutionary psychology. Economic Inquiry, 36, 335–352.

Isaac, G. (1978). The food-sharing behavior of protohuman hominids. Scientiﬁc American, 238,90–108.

Johnson-Laird, P., & Byrne, R. (1991).

Deduction. Hillsdale, NJ: Erlbaum.

Keil, F. (1989). Concepts, kinds, and cognitive development. Cambridge, MA: MIT Press.

Kirby, K. (1994). Probabilities and utilities of ﬁctional outcomes in Wason’s four-card selection task.

Cognition, 51,1–28.

Kornreich, C., Delle-Vigne, D., Dubruille, S., Campanella, S., Noel, X., & Ermer, E. (forthcoming). Social

exchange and precautionary reasoning are relatively spared in schizophrenic patients.

Adaptations for Reasoning About Social Exchange 665

3GC25 06/13/2015 2:45:19 Page 666

Krasnow, M., Cosmides, L., Pedersen, E., & Tooby, J. (2012). What are punishment and reputation for? PLoS

ONE 7(9), e45662. doi: 10.1371/journal.pone.0045662

Krasnow, M., Delton, A., Tooby, J., & Cosmides, L. (2013). Meeting now suggests we will meet again:

Implications for debates on the evolution of cooperation. Nature Scientiﬁc Reports, 3, 1747. doi: 10.1038/

srep01747

Kurzban, R., McCabe, K., Smith, V. L., & Wilson, B. J. (2001). Incremental commitment and reciprocity in a

real time public goods game. Personality and Social Psychology Bulletin, 27(12), 1662–1673.

Leckman, J., & Mayes, L. (1998). Maladies of love: An evolutionary perspective on some forms of obsessive-

compulsive disorder. In D. M. Hann, L. C. Huffman, I. I. Lederhendler, & D. Meinecke (Eds.), Advancing

research on developmental plasticity: Integrating the behavioral science and neuroscience of mental health

(pp. 134–152) Rockville, MD: U. S. Department of Health and Human Services.

Leckman, J., & Mayes, L. (1999). Preoccupations and behaviors associated with romantic and parental

lov e: Perspectives on the origin of obsess ive-compulsive disorder. Obsessive-Compulsive Disorder, 8 (3),

635–665.

Lieberman, D., Tooby, J., & Cosmides, L. (2003). Does morality have a biological basis? An empirical test of

the factors governing moral sentiments relating to incest. Proceedings of the Royal Society B: Biological

Sciences, 270(1517), 819–826.

Lieberman, D., Tooby, J. & Cosmides, L. (2007). The architecture of human kin detection. Nature, 445(7129),

727–731. doi: 10.1038/nature05510

Malinowski, B. (1922). Argonauts of the Western Paciﬁc. New York, NY: Dutton Press.

Maljkovic, V. (1987). Reasoning in evolutionarily important domains and schizophrenia: Dissociation between

content-dependent and content independent reasoning (Unpublished honors thesis). Department of Psychol-

ogy, Harvard University, Cambridge, MA.

Manktelow, K., & Evans, J. St. B. T. (1979). Facilitation of reasoning by realism: Effect or non-effect? British

Journal of Psychology, 70, 477–488.

Manktelow, K., & Over, D. (1987). Reasoning and rationality. Mind and Language, 2, 199–219.

Manktelow, K., & Over, D. (1988, July). Sentences, stories, scenarios, and the selection task. First International

Conference on Thinking. Plymouth, UK.

Manktelow, K., & Over, D. (1990). Deontic thought and the selection task. In K. J. Gilhooly, M. T. G. Keane, R.

H. Logie, & G. Erdos (Eds.), Lines of thinking (Vol. 1, pp. 153–164) London, UK: Wiley.

Manktelow, K., & Over, D. (1991). Social roles and utilities in reasoning with deontic conditionals. Cognition,

39,85–105.

Manktelow, K., & Over, D. (1995). Deontic reasoning. In S. E. Newstead & J. St. B. T. Evans (Eds.), Perspectives

on thinking and reasoning: Essays in honor of Peter Wason

(pp. 91–114). Hove, UK: Erlbaum.

Marcus, G. (2001). The algebraic mind: Reﬂections on connectionism and cognitive science. Cambridge, MA: MIT

Press.

Markman, E. (1989). Categorization and naming in children. Cambridge, MA: MIT Press.

Marks, I. (1987). Fears, phobias, and rituals. New York, NY: Oxford University Press.

Marshall, L. (1976). Sharing, talking, and giving: Relief of social tensions among the !Kung. In R. Lee& I.

DeVore (Eds.), Kalahari hunter-gatherers: Studies of the !Kung San and their neighbors. Cambridge, MA:

Harvard University Press.

Maurer, A. (1965). What children fear. Journal of Genetic Psychology, 106, 265–277.

Mauss, M. (1967). The gift: Forms and functions of exchange in archaic societies. New York, NY: Norton. (Original

work published 1925).

Maynard Smith, J. (1982). Evolution and the theory of games. Cambridge, UK: Cambridge University Press.

McKenna, P., Clare, L., & Baddeley, A. (1995). Schizophrenia. In A. D. Baddeley, B. A. Wilson, & F. N. Watts

(Eds.), Handbook of memory disorders (pp. 271–292). New York, NY: Wiley.

Mineka, S., & Cook, M. (1993). Mechanisms involved in the observational conditioning of fear. Journal of

Experimental Psychology: General, 122,23–38.

Núñez, M. (2011). Natural psychologists and precocious negotiators: Early understanding of the emotional

consequences of social exchange. Journal of Evolutionary Psychology, 9(4), 327–339.

Núñez, M., & Harris, P. (1998a). Psychological and deontic concepts: Separate domains or intimate

connections? Mind and Language, 13, 153–170.

Núñez, M., & Harris, P. (1998b, July). Young children’s reasoning about prescriptive rules: Spotting transgressions

through the selection task. Paper presented at the XVth Biennial Meeting of the International Society for the

Study of Behavioral Development, Berne, Switzerland.

Oaksford, M., & Chater, N. (1994). A rational analysis of the selection task as optimal data selection.

Psychological Review, 101, 608–631.

666 GROUP LIVI NG:COOPERATION AND C ONFLICT

3GC25 06/13/2015 2:45:19 Page 667

Orr, H. A. (2003). Darwinian storytelling. New York Review of Books, L(3) 17–20.

Pereyra, L., & Nieto, J. (2004). La especiﬁcidad del razonamiento sobre situaciones de peligro. [Reasoning

specializations for situations involving hazards and precautions]. Revista Mexicana de Psicología, 21(2),

167–177.

Piaget, J. (1950). The psychology of intelligence. (M. Piercy & D. E. Berlyne, Trans.) New York, NY: Harcourt.

Pinker, S. (1994). The language instinct. New York, NY: Morrow.

Pinker, S. (2002). The blank slate. New York, NY: Viking.

Platt, R., & Griggs, R. (1993). Darwinian algorithms and the Wason selection task: A factorial analysis of

social contract selection task problems. Cognition, 48, 163–192.

Price, M. E., Cosmides, L., & Tooby, J. (2002). Punitive sentiment as an anti-free rider psychological device.

Evolution and Human Behavior, 23, 203–231.

Quartz, S., & Sejnowski, T. (1997). The neural basis of cognitive development: A constructivist manifesto.

Behavioral and Brain Sciences, 20(4), 537–596.

Reis, D., Brackett, M., Shamosh, N., Kiehl, K., Salovey, P., & Gray, J. (2007). Emotional intelligence predicts

individual differences in social exchange reasoning. Neuroimage, 35, 1385–1391.

Rips, L. (1994). The psychology of proof. Cambridge, MA: MIT Press.

Romer, P. (2000). Thinking and feeling. American Economic Review, 90(2), 439–443.

Rumelhart, D., & McClelland, J. (1986). On learning the past tenses of English verbs: Implicit rules or parallel

distributed processing. In D. Rumelhart, J. McClelland, & The PDP Research Group (Eds.), Parallel

distributed processing: Explorations in the microstructure of cognition (Vol. 2, pp. 216–271). Cambridge, MA:

MIT Press.

Savage, L. J. (1954). The foundations of statistics. New York, NY: Wiley.

Szechtman, H., & Woody, E. (2004). Obsessive-compulsive disorder as a disturbance of security motivation.

Psychological Review, 111, 111–127.

Shallice, T. (1988). From neuropsychology to mental structure. Cambridge, UK: Cambridge University Press.

Shostak, M. (1981). Nisa: The life and words of a !Kung woman. Cambridge, MA: Harvard University Press.

Simon, H. (1990). A mechanism for social selection and successful altruism. Science, 250, 1665–1668.

Sperber, D., Cara, F., & Girotto, V. (1995). Relevance theory explains the selection task. Cognition, 57,31–95.

Staddon, J. E. R. (1988). Learning as inference. In R. C. Bolles & M. D. Beecher (Eds.), Evolution and learning.

Hillsdale, NJ: Erlbaum.

Stevens, J., & Stephens, D. (2004). The economic basis of cooperation: Trade-offs between selﬁshness and

generosity. Behavioral Ecology, 15(2), 255–261.

Stone, V., Cosmides, L., Tooby, J., Kroll, N., & Knight, R. (2002, August). Selective impairment of reasoning

about social exchange in a patient with bilateral limbic system damage. Proceedings of the National

Academy of Sciences, USA, 99(17), 11531–11536.

Sugiyama, L., Tooby, J., & Cosmides, L. (2002, August). Cross-cultural evidence of cognitive adaptations for

social exchange among the Shiwiar of Ecuadorian Amazonia. Proceedings of the National Academy of

Sciences, USA, 99(17), 11537–11542.

Tooby, J., & Cosmides, L. (1989, August). The logic of threat. Paper presented at the Human Behavior and

Evolution Society, Evanston, IL.

Tooby, J., & Cosmides, L. (1992). The psychological foundations of culture. In J. Barkow, L. Cosmides, & J.

Tooby (Eds.), The adapted mind (pp. 19–136). New York, NY: Oxford University Press.

Tooby, J., & Cosmides, L. (1996). Friendship and the banker’s paradox: Other pathways to the evolution of

adaptations for altruism. In W. G. Runciman, J. Maynard Smith, & R. I. M. Dunbar (Eds.), Evolution of

social behaviour patterns in primates and man. Proceedings of the British Academy, 88, 119–143.

Tooby, J., & Cosmides, L. (2010). Groups in mind: Coalitional psychology and the roots of war and morality.

In Henrik Høgh-Olesen (Ed.), Human morality and sociality: Evolutionary and comparative perspectives (pp.

191–234) New York, NY: Palgrave Macmillan.

Tooby, J., Cosmides, L., & Barrett, H. C. (2005). Resolving the debate on innate ideas: Learnability constraints

and the evolved interpenetration of motivational and conceptual functions. In P. Carruthers, S.

Laurence, & S. Stich (Eds.), The innate mind: Structure and content. New York, NY: Oxford University

Press.

Tooby, J., & DeVore, I. (1987). The reconstruction of hominid behavioral evolution through strategic

modeling. In W. G. Kinsey (Ed.), Primate models of hominid behavior (pp. 183–237). New York, NY:

SUNY Press.

Trivers, R. (1971). The evolution of reciprocal altruism. Quarterly Review of Biology, 46,35–57.

Wason, P. (1966). Reasoning. In B. M. Foss (Ed.), New horizons in psychology (pp. 135–151). Harmondsworth,

UK: Penguin.

Adaptations for Reasoning About Social Exchange 667

3GC25 06/13/2015 2:45:19 Page 668

Wason, P. (1983). Realism and rationality in the selection task. In J. St. B. T. Evans (Ed.), Thinking and

reasoning: Psychological approaches (pp. 44–75). London, UK: Routledge.

Wason, P., & Johnson-Laird, P. (1972). The psychology of reasoning: Structure and content. Cambridge, MA:

Harvard University Press.

Wegener, J., Lund, T., Hede, A., Ramsøy, T., Baaré, W., & Paulson, O. (2004). A neural basis for identifying social

contract violators in humans. Organization for Human Brain Mapping 2004 Annual Meeting. Budapest,

Hungary.

Williams, G. (1966). Adaptation and natural selection. Princeton, NJ: Princeton University Press.

668 GROUP LIVI NG:COOPERATION AND C ONFLICT