Can race be erased? Coalitional computation and social categorization.

Previous studies have established that people encode the race of each individual they encounter, and do so via computational processes that appear to be both automatic and mandatory. If true, this conclusion would be important, because categorizing others by their race is a precondition for treating them differently according to race. Here we report experiments, using unobtrusive measures, showing that categorizing individuals by race is not inevitable, and supporting an alternative hypothesis: that encoding by race is instead a reversible byproduct of cognitive machinery that evolved to detect coalitional alliances. The results show that subjects encode coalitional affiliations as a normal part of person representation. More importantly, when cues of coalitional affiliation no longer track or correspond to race, subjects markedly reduce the extent to which they categorize others by race, and indeed may cease doing so entirely. Despite a lifetime's experience of race as a predictor of social alliance, less than 4 min of exposure to an alternate social world was enough to deflate the tendency to categorize by race. These results suggest that racism may be a volatile and eradicable construct that persists only so long as it is actively maintained through being linked to parallel systems of social alliance.

Evolutionary psychology and the brain.

The human brain is a set of computational machines, each of which was designed by natural selection to solve adaptive problems faced by our hunter-gatherer ancestors. These machines are adaptive specializations: systems equipped with design features that are organized such that they solve an ancestral problem reliably, economically and efficiently. The search for functionally specialized computational adaptations has now begun in earnest. A host of specialized systems have recently been found, including ones designed for sexual motivation, social inference, judgment under uncertainty and conditioning, as well as content-rich systems for visual recognition and knowledge acquisition.

No interpretation without representation: the role of domain-specific representations and inferences in the Wason selection task.

The Wason selection task is a tool used to study reasoning about conditional rules. Performance on this task changes systematically when one varies its content, and these content effects have been used to argue that the human cognitive architecture contains a number of domain-specific representation and inference systems, such as social contract algorithms and hazard management systems. Recently, however, Sperber, Cara & Girotto (Sperber, D., Cara, F., & Girotto, V. (1995). Relevance theory explains the selection task. Cognition, 57, 31-95) have proposed that relevance theory can explain performance on the selection task - including all content effects - without invoking inference systems that are content-specialized. Herein, we show that relevance theory alone cannot explain a variety of content effects - effects that were predicted in advance and are parsimoniously explained by theories that invoke domain-specific algorithms for representing and making inferences about (i) social contracts and (ii) reducing risk in hazardous situations. Moreover, although Sperber et al. (1995) were able to use relevance theory to produce some new content effects in other domains, they conducted no experiments involving social exchanges or precautions, and so were unable to determine which - content-specialized algorithms or relevance effects - dominate reasoning when the two conflict. When experiments, reported herein, are constructed so that the different theories predict divergent outcomes, the results support the predictions of social contract theory and hazard management theory, indicating that these inference systems override content-general relevance factors. The fact that social contract and hazard management algorithms provide better explanations for performance in their respective domains does not mean that the content-general logical procedures posited by relevance theory do not exist, or that relevance effects never occur. It does mean, however, that one needs a principled way of explaining which effects will dominate when a set of inputs activate more than one reasoning system. We propose the principle of pre-emptive specificity - that the human cognitive architecture should be designed so that more specialized inference systems pre-empt more general ones whenever the stimuli centrally fit the input conditions of the more specialized system. This principle follows from evolutionary and computational considerations that are common to both relevance theory and the ecological rationality approach.

When and why do people avoid unknown probabilities in decisions under uncertainty? Testing some predictions from optimal foraging theory.

When given a choice between two otherwise equivalent options - one in which the probability information is stated and another in which it is missing - most people avoid the option with missing probability information (Camerer & Weber, 1992). This robust, frequently replicated tendency is known as the ambiguity effect. It is unclear, however, why the ambiguity effect occurs. Experiments 1 and 2, which separated effects of the comparison process from those related to missing probability information, demonstrate that the ambiguity effect is elicited by missing probabilities rather than by comparison of options. Experiments 3 and 4 test predictions drawn from the literature on behavioral ecology. It is suggested that choices between two options should reflect three parameters: (1) the need of the organism, (2) the mean expected outcome of each option; and (3) the variance associated with each option's outcome. It is hypothesized that unknown probabilities are avoided because they co-occur with high outcome variability. In Experiment 3 it was found that subjects systematically avoid options with high outcome variability regardless of whether probabilities are explicitly stated or not. In Experiment 4, we reversed the ambiguity effect: when participants' need was greater than the known option's expected mean outcome, subjects preferred the ambiguous (high variance) option. From these experiments we conclude that people do not generally avoid ambiguous options. Instead, they take into account expected outcome, outcome variability, and their need in order to arrive at a decision that is most likely to satisfy this need.

Toward an evolutionary taxonomy of treatable conditions.

The definition of disorder as a harmful dysfunction (J. C. Wakefield, 1999) is a useful concept, anchored in the recognition that the evolved human architecture consists of a collection of functional mechanisms that may potentially be impaired and whose impairment may be harmful. Because natural selection organized each mechanism to solve a distinct adaptive problem under ancestral conditions, the criteria for whether a mechanism is dysfunctional are supplied by whether the mechanism has become impaired in performing its ancestral function. Because evolutionary function and dysfunction diverge markedly from normal human standards of value, many dysfunctions are beneficial, whereas various mechanisms that are performing their evolved function may cause disturbing outcomes. For this reason, many conditions in addition to disorders may require treatment, and the authors attempt to sketch an evolutionary taxonomy of treatable conditions.

Dissecting the computational architecture of social inference mechanisms.

Scientists have been dissecting the neural architecture of the human mind for several centuries. Dissecting its computational architecture has proven more difficult, however. Within the cognitive sciences, for example, there is a debate about the extent to which human reasoning is generated by computational machinery that is domain specific and functionally specialized. While some claim that the same set of cognitive processes accounts for reasoning across all domains (e.g. Rips 1994, Johnson-Laird & Byrne 1991), others argue that reasoning is generated by several different mechanisms, each designed to operate over a different class of content (e.g. Baron-Cohen 1995, Cheng & Holyoak 1985, Cosmides & Tooby 1992, Leslie 1987). Indeed, it has recently been proposed that the human cognitive architecture contains a faculty of social cognition; a suite of integrated mechanisms, each of which is specialized for reasoning and making decisions about a different aspect of the social world. Candidate devices include a theory of mind mechanism, an eye direction detector, social contract algorithms, permission schemas, obligation schemas, precaution rules, threat detection procedures and others (e.g. Baron-Cohen 1995, Cheng & Holyoak 1985, Cosmides 1985, 1989, Cosmides & Tooby 1989, 1992, 1994, Fiddick et al 1995, Fiske 1991, Jackendoff 1992, Leslie 1987, K. Manktelow & D. Over, unpublished paper, 1st Int Conf on Thinking, Plymouth, UK 1988, Manktelow & Over 1990, M.Rutherford, J. Tooby, L. Cosmides, unpublished paper, 8th Annual Meeting Human Behav Evol Society, Northwestern Univ, IL 1996, J. Tooby & L. Cosmides, unpublished paper, 2nd Annual Meeting Human Behav Evol Society, Evanston, IL 1989). To decide among these sometimes competing proposals, psychologists need empirical methods and theoretical standards that let us carve social inference mechanisms at the joints. We will argue that the theoretical standards needed are those of the 'adaptationist programme' developed in evolutionary biology. To show how these standards can be applied in dissecting the computational architecture of the human mind, we will discuss some recent empirical methods and results.

Beyond intuition and instinct blindness: toward an evolutionarily rigorous cognitive science.

Cognitive psychology has an opportunity to turn itself into a theoretically rigorous discipline in which a powerful set of theories organize observations and suggest focused new hypotheses. This cannot happen, however, as long as intuition and folk psychology continue to set our research agenda. This is because intuition systematically blinds us to the full universe of problems our minds spontaneously solve, restricting our attention instead to a minute class of unrepresentative "high-level" problems. In contrast, evolutionarily rigorous theories of adaptive function are the logical foundation on which to build cognitive theories, because the architecture of the human mind acquired its functional organization through the evolutionary process. Theories of adaptive function specify what problems our cognitive mechanisms were designed by evolution to solve, thereby supplying critical information about what their design features are likely to be. This information can free cognitive scientists from the blinders of intuition and folk psychology, allowing them to construct experiments capable of detecting complex mechanisms they otherwise would not have thought to test for. The choice is not between no-nonsense empiricism and evolutionary theory; it is between folk theory and evolutionary theory.

On the universality of human nature and the uniqueness of the individual: the role of genetics and adaptation.

The concept of a universal human nature, based on a species-typical collection of complex psychological adaptations, is defended as valid, despite the existence of substantial genetic variation that makes each human genetically and biochemically unique. These apparently contradictory facts can be reconciled by considering that (a) complex adaptations necessarily require many genes to regulate their development, and (b) sexual recombination makes it improbable that all the necessary genes for a complex adaptation would be together at once in the same individual, if genes coding for complex adaptations varied substantially between individuals. Selection, interacting with sexual recombination, tends to impose relative uniformity at the functional level in complex adaptive designs, suggesting that most heritable psychological differences are not themselves likely to be complex psychological adaptations. Instead, they are mostly evolutionary by-products, such as concomitants of parasite-driven selection for biochemical individuality. An evolutionary approach to psychological variation reconceptualizes traits as either the output of species-typical, adaptively designed development and psychological mechanisms, or as the result of genetic noise creating perturbations in these mechanisms.

The logic of social exchange: has natural selection shaped how humans reason? Studies with the Wason selection task.

In order to successfully engage in social exchange--cooperation between two or more individuals for mutual benefit--humans must be able to solve a number of complex computational problems, and do so with special efficiency. Following Marr (1982), Cosmides (1985) and Cosmides and Tooby (1989) used evolutionary principles to develop a computational theory of these adaptive problems. Specific hypotheses concerning the structure of the algorithms that govern how humans reason about social exchange were derived from this computational theory. This article presents a series of experiments designed to test these hypotheses, using the Wason selection task, a test of logical reasoning. Part I reports experiments testing social exchange theory against the availability theories of reasoning; Part II reports experiments testing it against Cheng and Holyoak's (1985) permission schema theory. The experimental design included eight critical tests designed to choose between social exchange theory and these other two families of theories; the results of all eight tests support social exchange theory. The hypothesis that the human mind includes cognitive processes specialized for reasoning about social exchange predicts the content effects found in these experiments, and parsimoniously explains those that have already been reported in the literature. The implications of this line of research for a modular view of human reasoning are discussed, as well as the utility of evolutionary biology in the development of computational theories.

Invariances in the acoustic expression of emotion during speech.

An experiment was designed to test whether different individuals produce similar voice patterns when they read the same emotional passage. Quantitative scoring criteria were developed that reflect the extent to which different individuals consistently produce similar constellations of acoustic attributes in response to the same emotional context. The scoring procedure was applied to the voice tracks of standard utterances produced by 11 subjects reading 10 different emotionally evocative scripts. The results supported the hypothesis that different individuals produce standard acoustic configurations to express emotions. Because acoustic properties reflecting contrastive stress consistently varied with emotional context over syntactically and semantically identical utterances, some factor related to emotional context other than syntax or semantics must account for the variations. An evolutionary argument that emotion communication can be seen as intention communication is presented to account for these variations. Implications for theories of emotions and of intentional generative semantics are discussed.