Evolutionary psychology

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Robert Kurzban (2007), Scholarpedia, 2(8):3161. doi:10.4249/scholarpedia.3161 revision #73365 [link to/cite this article]
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Curator: Robert Kurzban

Evolutionary psychology is an approach to studying psychology. It applies principles of evolutionary biology (Darwin, 1859), in particular the logic of adaptationism (Williams, 1966), to derive and test hypotheses about the design and operation of the human mind. Because it is an approach, it can be applied to any of a wide range of content areas of psychology, such as developmental psychology, social psychology, clinical psychology, perception, language, judgment and decision making, and so on.


Theory & Principles

Evolutionary psychology begins with the idea that the source of organized functional complexity observed in all living organisms is evolution by natural selection. In its application to psychology, it entails the further uncontroversial assumption that the brain causes behavior. Researchers in the discipline generally assume the basic principles of evolution by natural selection as articulated by Darwin (1859) and subsequent important developments, such as sexual selection (Darwin, 1871), the modern synthesis (e.g., Fisher, 1930) and inclusive fitness theory (Hamilton, 1968). They also tend to assume some form of the computational theory of mind (e.g., Fodor, 1975): that what the brain does is process information (Pinker 1997).

Functional Specialization

An entailment of the evolutionary analysis is that organisms can be sensibly broken down into functional subcomponents or pieces. This process is not arbitrary, but rather reflects the functional elements selected by evolution. A commonly-used analogy is that organs can similarly be analyzed as functional components of the whole organism, and organs can themselves be further broken down into functional subcomponents.

Evolutionary psychology assumes that this is also the case for the mind. Although there is disagreement within the discipline on this topic, many researchers assume that the human mind consists of a large number of functionally specialized components, rather than a small number of general-function components (Pinker, 1997; Tooby & Cosmides, 1992).

The reasoning behind this position rests not on the analogy with organ systems, but rather on the logic of computation. The mind, as an information-processing device, functions only insofar as it performs useful computations on information. Further, for any given computational problem to be solved, the broader the range of problems a mechanism is designed to solve, the worse it will be at solving them, and, the more narrow the range of problems a computational mechanism is designed to solve, the better it will be at solving them. For this reason, evolution will tend to favor functionally specialized computational devices that are narrow in their function, whose design assumes or embodies elements of the problem to be solved.

This basic idea is illustrated by Chomsky’s (1980) dissection of language learning. Chomsky developed an argument he referred to as the “poverty of the stimulus,” that natural language cannot be learned with only the information that the language learner (the child) receives as input. This implies that there must be specialized language acquisition devices that embody knowledge about what is to be learned in order to do the learning.

A similar argument has been made by others (Quine, 1960) and has been extensively studied in vision. From any given set of information on the retina, an arbitrarily large number of visual scenes could be generated. Because the human visual system has information processing procedures that embody or assume features of the world, specialized computational systems can act on retinal data to produce the percept.

Because the mind performs many different tasks, it must, it is argued, consist of a large number of functionally specialized mechanisms, each of which embodies principles related to the domain for which it is designed to function. These principles have been discussed under many labels. A common term in evolutionary psychology is ‘’modularity.’’ This term is not intended to connote the spatial sense, but rather the notion of functional specificity. This has been a source of some debate both within the evolutionary psychology community, and a source of criticism outside of it. (See Fodor, 1983, for an early use of the term, and Barrett & Kurzban, 2006, for a recent discussion.)

Plausible Evolved Functions

Because of the way that natural selection operates, genes are selected by virtue of the effect that they have on their own replication rate relative to alternatives in the population (see Dawkins, 1976, for a lucid discussion). Which genes lead to their own replication depends on how they contribute to the solution of adaptive problems, the specific tasks, such as finding food, avoiding predators, and so forth, faced by organisms of a given species. Adaptive problems are diverse, and depend exquisitely on the life history of the species in question. That is, because different organisms survive and reproduce in very different ways, the features – and thus the genes – that are advantageous vary from one species to the next.

As a general rule, then, selection will cause the increase in frequency of genes that cause phenotypes that are better at solving adaptive problems faced by the organism. Crucially, adaptive problems can only shape selection when the problem is one that has been repeatedly faced by the species in question – this is a consequence of the generational time scale over which natural selection operates. Selection can have its effects only if it has a causal effect on replication of the gene in question through reproduction, though this pathway can be arbitrarily distal.

The idea that the brain is likely to consist of functionally specialized computational systems, taken together with the idea that selection operates over long time scales, suggests that the computational mechanisms humans possess are the ones generated by genes selected over the course of human evolutionary history. This in turn implies that the search for specialized computational mechanisms – adaptations – should be guided by the search for mechanisms that had plausible functions relative to the tasks our ancestors faced.

This is not to say that humans cannot do many things that are evolutionarily novel, such as drive cars and choose investment strategies. Because of the way that brains, and especially development, work, humans can do many things for which there was not specifically selection in the past.

Indeed, because natural selection only functions on what has happened in the past, every organism, including humans, are in environments which are novel in some way relative to the environment in which their adaptations were selected. Each new human being’s face is a novel feature of the environment, but human brains are nonetheless, barring impairment, able to perform computations to perceive, store, and recognize these novel faces. Because genes are selected by virtue of how they contributed to reproductive success in the past, it is inevitable that there can be elements of any given organism’s environment that do not match the environmental features that played a causal role in the selection of the relevant genes. A frequently-used example is the human taste for fats and sugars. In past environments, such appetites would presumably have led to adaptive outcomes; in modern environments, because of the easy availability of foods rich in sugar and fat, people consume foods that lead to unhealthful outcomes (see Burnham and Phelan, 2000, for an engaging discussion).

Levels of Explanation

Evolutionary psychology is a framework that allows researchers to operate at different levels of explanation. Although various scholars have broken these levels down in different ways (e.g., Tinbergen, 1963), it is convenient to break down explanations for biological phenomena into three levels: function (what is the goal to be achieved?), algorithm (what computations are used to achieve the goal?), and implementation (how are the computations physically implemented?).

To illustrate why different levels are required, consider the different ways that one might explain the workings of a watch. One explanation for how it functions is that someone designed the watch to perform the function of indicating the correct time. Another way to explain it would be to describe how it keeps track of and represents time, including how it represents the passage of time, the units it uses, and so on. A third way would be to give a physical description of the watch, including the movement of the gears.

Because evolved psychological mechanisms have functions, they can also be explained at these three levels. One of the most thoroughly described phenomena in psychology to be described is vision. The eye – including structures from the lens and pupil to the neurophysiological structures involved, such as V1 and other visual areas – functions to generate a representation of the physical world. To do this, it takes input in the form of electromagnetic radiation, and transforms it though many different steps, which include things like “edge detectors” and other specialized computational devices. These computational systems are implemented neurally, and substantial progress has been made in understanding how different neural systems implement the computations necessary to perform the eye’s function, linking together the three levels of analysis.

Usually – but not always – evolutionary psychology starts with an idea about function, the first level of explanation. These ideas are used to develop hypotheses about the computational systems that might exists to serve these functions. As such, hypotheses are usually stated at this level. Cosmides and Tooby’s (1992) work suggesting that there is a set of computational mechanisms designed to function to detect cheaters led to predictions about the computations that one would expect if there existed such a system, which in turn led to the design of their experiments to test for the existence of these features. Because some computations but not others will contribute to the execution of any given putative function, a potential functional explanation will carry entailments about the computational system. The notion of evolved function, therefore, constrains the hypothesis space for evolutionary psychologists.


Evolutionary psychology is committed to the same view of development that is common in biology (see, e.g., West-Eberhard, 2003). That is, natural selection will retain genes that cause interactions with the environment that lead to the reliable construction of the functional mechanisms that solve adaptive problems. In this sense, evolutionary psychology is “interactionist” in its view of development. Because genes have no functionally relevant consequences unless they interact with the environment broadly construed –other genes, the intracellular environment, the external world, and so on – development of any aspect of the phenotype can only be understood as the interaction between genes and the environment. Natural selection therefore can be thought of as a process that retains genes that interact with the environment – i.e., cause development – in a way that leads to the reliable development of functional elements of the phenotype.

This view makes some broad predictions about development, and can be used to make more specific predictions in the context of a particular theory of function. For example, interactionist notions of development entail that to the extent that the environment relevant to a particular aspect of the phenotype changes, the developmental outcome is more likely to change. This means that the extent that one knows what features are “developmentally relevant“ for the gene/environment interaction in question, one can make textured predictions about the effect of various features of the environment on development.

For example, Gangestad and Buss (1993) began with the premise that many factors can be used as criteria in selecting a mate (physical appearance, personality characteristics, etc.), and these criteria can be given more or less weight. They reasoned that a well-designed mate-choice system should take into account cues to the levels of pathogens in the local ecology and put more weight on physical attractiveness, which itself is a cue to pathogen resistance. They predicted, and found evidence for, a developmental system that calibrated preferences to a specific feature of the local ecology. In this way, theories of function can guide hypotheses regarding environmental influences on development

Although evolutionary approaches are often equated with strong versions of nativism, these characterizations do not capture the theoretical commitments of the approach. Evolutionary psychology does not hold that neural systems – or any aspect of the phenotype – will be present at birth, will develop independent of the properties of the environment, or will require no environmental input for proper development of the system in question. Evolutionary approaches – in humans and non-humans – take selection to shape how genes interact with the environment by virtue of feedback loops between the genes in question and the structures that they cause to develop.



Because evolutionary psychology is an approach rather than a content area, researchers in the discipline use a variety of techniques. These include laboratory experiments, field experiments, mathematical and agent-based simulations, surveys, neuroimaging, and so on. While much of the research focuses on humans, comparative analyses and research with non-human animals are also important parts of the enterprise. Evolutionary psychologists do not differ in their methodological commitments from other researchers in the social and natural sciences. They rely on middle-level theories to develop hypotheses, and the nature of the hypothesis determines what methods are most usefully brought to bear to address the hypothesis in question.

A number of examples illustrate this point. Daly and Wilson (1988) used archival data about infanticide to address a hypothesis derived from inclusive fitness theory. Cosmides and Tooby (1992) used a method common in cognitive psychology, the Wason Selection Task, to address their hypothesis about cheater detection. David Buss (1989) collected a corpus of cross-cultural questionnaire data to address a set of hypotheses about evolved human mating psychology. The techniques used by evolutionary psychologists are diverse because of the variation in the nature of the questions they are trying to answer.

Standards of Evidence

Following conventions in evolutionary biology, evolutionary psychologists tend to follow Williams (1966) in taking an adaptationist approach. This approach generally begins with positing a function for some aspect of the organism’s phenotype. Functional hypotheses necessarily require predictions regarding the way in which the function is accomplished. Each additional design features that is accurately predicted is evidence in favor of the posited function. For example, features of the eye – including its transparent lens, dilating pupil, photosensitive receptors, and so on – are all evidence in favor of its function to recover information from the world to construct a representation of the physical environment. As Williams stressed in his original work, adaptation is a strong claim, and requires evidence. The adaptationist program requires evidence that the object of study is designed for the specified purpose, rather than some other purpose.


The theoretical commitments of evolutionary psychology described here are often misunderstood. This might be due to social scientists’ lack of familiarity with evolutionary biology, the novelty of the discipline, or other factors. A small number of the most frequent misconceptions are very briefly discussed here, though this is not intended to be a complete list.

Genetic determinism

Some authors equate evolutionary approaches with genetic determinism, suggesting that the discipline is committed to the view that brains are “hardwired,” with no influence from the environment (see Buller, 2005; Rose & Rose, 2000). As indicated in the section on development above, this does not accurately characterize the interactionist view of the field.


Stephen Jay Gould (2000), among others, have understood evolutionary psychologists to hold that all parts of all organisms under any descriptions are adaptations. In contrast, evolutionary psychology, like evolutionary biology, takes natural selection to be the only known source of organized functional complexity, but does not take all features of organisms to be functional features. Any functional aspect of the phenotype must necessarily have concomitant byproducts, features that are incidental consequences that were not selected by virtue of a functional role. The colors of internal organs are examples. The fact that the liver is brown is a byproduct of the physiology, but its color does not contribute to its function per se. It is worth noting that identifying byproducts requires the same type of rigor as identifying adaptations: a hypothesis that a trait is a byproduct generally requires an account of the adaptation or adaptations of which the trait in question is a byproduct.

Universality & Culture

While evolutionary psychology takes there to be a species-typical cognitive architecture – an evolved “human nature” – this does not entail the prediction that all humans will be everywhere the same. Variation has many sources, including genetic differences, contingent responses to the environment (such as language learning, in which a putative universal language acquisition system leads to differences in the specific language leaned depending on the environment), and so on. Evolutionary psychology is committed to the view that there is a human nature, much as there is a flamingo nature, mosquito nature, or oak tree nature. That is, there is a species-typical design with variation among individuals coming from many sources, both genetic and environmental.

One important source of variation between individuals derives from the fact that humans learn from one another (Boyd & Richerson, 1985), and information accumulates over time. Because information in other people’s minds is one aspect of the environment for humans, people in different places and different times come to have beliefs because others in the local ecology have them. Sets of beliefs that differ from one group of individuals to another are, therefore, another part of the human phenotype to be explained. Evolutionary psychology takes what is usually termed “culture” to be the product of human minds, albeit a complex one. Far from placing no importance on the role of culture, evolutionary psychology sees culture as one of the most important aspects of human nature to try to explain (Tooby & Cosmides, 1992).


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  • Dawkins, R. (1976). The Selfish Gene. Oxford: Oxford University Press.
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  • Gould, S. J. (2000). More things in heaven and earth. In H. Rose and S. Rose (Eds.) Alas poor Darwin: Arguments against evolutionary psychology (pp. 101-126). New York: Harmony Books.
  • Hamilton, W. D. (1964). The genetical evolution of social behaviour, I and II. Journal of Theoretical Biology, 7, 1-52.
  • Pinker, S. (1997). How the mind works. New York: W. W. Norton & Co.
  • Quine, W. V. O. (1960). Word and object. Cambridge, MA: Harvard University Press.
  • Rose, H., & Rose, S. (2000). Alas poor Darwin: Arguments against evolutionary psychology. New York: Harmony Books.
  • Tinbergen, Niko (1963). On aims and methods in ethology Zeitschrift für Tierpsychologie, 20: 410-433.
  • Tooby, J., & Cosmides, L. (1992). The psychological foundations of culture. In J. H. Barkow, L. Cosmides, & J. Tooby (Eds.), The adapted mind: Evolutionary psychology and the generation of culture (pp. 19– 136). Oxford, England: Oxford University Press.
  • West-Eberhard, M. J. (2003). Developmental plasticity and evolution. Oxford, England: Oxford University Press.
  • Williams, G. C. (1966). Adaptation and natural selection. Princeton, NJ: Princeton University Press.

Internal references

  • Valentino Braitenberg (2007) Brain. Scholarpedia, 2(11):2918.
  • Zhong-Lin Lu and Barbara Anne Dosher (2007) Cognitive psychology. Scholarpedia, 2(8):2769.
  • Olaf Sporns (2007) Complexity. Scholarpedia, 2(10):1623.
  • William D. Penny and Karl J. Friston (2007) Functional imaging. Scholarpedia, 2(5):1478.
  • Mark Aronoff (2007) Language. Scholarpedia, 2(5):3175.
  • John Dowling (2007) Retina. Scholarpedia, 2(12):3487.

Further Reading

  • Barkow, J., Cosmides, L. & Tooby, J. (eds.) (1992). The adapted mind. NY: Oxford University Press.
  • Buss, D. M. (2005). The handbook of evolutionary psychology. NY: Wiley.
  • Daly M, & Wilson, M. (1988). Homicide. NY: Aldine de Gruyter.
  • Dawkins, R. (1976). The selfish gene. Oxford: Oxford University Press.
  • Pinker, S. (1997). How the mind works. New York: W. W. Norton & Co.

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See Also

Evolution, Psychology

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