Chapter Eight

1. Chapter Eight The Evolutionary Approach: Change Over Time

2. Evolutionary Psychology • Evolutionary Psychology (EP) describes how our early environment produced our current mental abilities. • This environment was the Pleistocene era, approximately two million years ago, referred to as the Environment of Evolutionary Adaptation (EEA). • Evidence to support evolutionary hypotheses comes from archeological records, hunter-gatherer societies, between- and within-species comparisons, and experimentation.

3. Natural selection EP relies on Darwin’s (1859) theory of natural selection. It requires three elements: • Variation in traits within a species. • The passing of genetic material from one generation to the next, called inheritance. • Selection, which is a change in the environment that favors one trait over another.

4. Evolved psychological mechanisms • EP views the mind as a collection of special purpose devices or a “Swiss army knife.” • Each device evolved under selection pressures to solve a specific problem. • These mechanisms can be considered as modules. • This is in contrast to the traditional notion of mind as a general purpose processor.

5. Properties of an evolved psychological mechanism • Solves a specific adaptive problem. • Takes in only a narrow band of information. • Informs the user of the type of problem. • Produces a response through a set of decision rules. • The response can be a physiological reaction, information to another mechanism, or a behavior. • The response is intended to provide a solution to the problem.

6. Evolution and categorization • We form concepts in a graded, continuous fashion, not “all or none.” • Natural categories are also continuous. The mind mimics this organization. • This allows us to generalize our knowledge from one category to another. • Concepts are organized around representative members of a class, the typicality effect.

7. Which looks more like a bird?

8. Evolution and memory • We should have a better memory for information we are exposed to more often. • This is because it is more relevant to our survival. • Recall for words is proportional to their frequency of occurrence (Anderson and Schooler, 1991).

9. The Wason selection task - hard version • You have been hired as a clerk. Your job is to make sure that a set of documents is marked correctly, according to the following rule: "If the document has an E rating, then it must be marked code 4." You have been told that there are some errors in the coding of the documents, and that you need to find the errors. Each document has a letter rating on one side and a numerical code on the other. Here are four documents. Which document(s) do you need to turn over to check for errors?

10. The Wason selection task - easy version • You have been hired as a bouncer in a bar and you must enforce the following rule: "If a person is drinking vodka, then he must be over twenty years old." The cards above have information about four people in the bar. One side of each card lists a person's age and the other side shows what he or she is drinking. Which card(s) do you need to turn over to be sure no one is breaking the law?

11. Evolution and logical reasoning • The bouncer problem is easy because it involves cheater-detection. • In the EEA it was important to detect who might be cheating because in small groups with limited resources it might mean less for you (Cosmides and Tooby, 1992). • The logic module thus works only in this context, implying logic is not domain general.

12. Evolution and judgment under uncertainty • Uncertain judgments occur when we make a decision without complete information. • Most everyday decisions in life are like this. • In such cases, we often rely on heuristics. • But heuristics can lead us to commit fallacies, a misunderstanding of statistical rules.

13. Fallacies • Base-rate fallacy. Ignoring base rates. • Conjunction fallacy. Ignoring the conjunction rule. • Gambler’s fallacy. Ignoring independent outcomes.

14. Example of Base-Rate Fallicy • 100 people: 70 lawyers; 30 engineers • Jack is a 45 year old man. He is married and has four children. He is generally conservative, careful, and ambitious. He shows no interest in political and social issues and spends most of his free time on his many hobbies, including home carpentry, sailing, and mathematical puzzles. • Is Jack a lawyer or an engineer?

15. Example of Conjunction Fallicy • Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. In college, she was involved in several social issues, including the environment, the peace campaign, and the anti-nuclear campaign. • Which is more likely: • Linda is a bank teller. • Linda is a bank teller active in the feminist movement.

16. Examples of Gambler’s Fallacy • You’ve observed two slot machines. • One hasn’t paid off in a long time. • The other just paid off. • Both are now available. • Which is more likely to pay off soon? • A fair coin has come up “heads” eight times in a row. • How likely is it to come up “tails” next time?

17. Evolution and language • Language may have evolved to promote social bonding (Dunbar, 1996). • It allows for complex coordinated social behavior. Examples: improvements in hunting, foraging, and childcare. • It may also play a role in sexual selection.

18. Evolution and sex differences • Attributed to a sexual division of labor in which men hunted and women gathered. • Hunting may have fostered increased spatial ability in men. • Gathering may have promoted increased verbal abilities in women. • But above distinction is too broad. Women are better at object location memory.

19. Evolutionary Computing • Thinking may utilize evolutionary principles. • Steps in problem solving: • Generate candidate solutions. • Evaluate their fitness. • Select solutions with high fitness values. • Generate new solution offspring by genetic combination. • Repeat steps 2-4.

20. Artificial Life • The study of manmade systems that behave in ways characteristic of natural living systems (Langton, 1989). • Computer “creatures” are created through evolutionary rules. They navigate, seek out prey, and avoid predators in a virtual environment. • Complex adaptive behaviors emerge including parasitism, symbiosis, and flocking.

21. Neural Darwinism • Application of evolution to neural learning (Edelman, 1989). • Initial growth of neural structures during development. • Interaction with environment causes differential modification of synaptic strengths. • Reentrant signaling between neural groups.

22. Evaluating the evolutionary approach • Novel biological function need not arise to service survival or reproduction. Other mechanisms: • Exaptation or neutral drift. Random mutation. • Molecular drive. Copies of genes mutate. • Idea of a spandrel (Gould, 2000). Byproducts of adaptations.

23. Spandrels in architecture