Groups as adaptive devices: Free-rider problems, the wisdom of crowds, and evolutionary games

1. July 23 Invited address Groups as adaptive devices: Free-rider problems, the wisdom of crowds, and evolutionary games Tatsuya Kameda Hokkaido University Center for Experimental Research in Social Sciences Center for the Sociality of Mind

2. Your survival tasks include…. Imagine you live in a tropical rain forest.

3. Gathering

4. Hunting

5. Avoiding predatory risks

6. Handling enemies

7. Groups as adaptive devices • Obviously, you cannot survive in such a natural, uncertain environment by yourself. • Your life is highly dependent on your group. • In this sense, the image of groups as adaptive devices looks quite natural. • “Groups are wise and intelligent.”

8. On the other hand, such a positive image of groups has been rather rare in the psychological literature on groups. • Instead, for many years, psychologists have been keen on identifying various “biases” leading to group inefficiencies (cf. Krueger & Funder, 2004, Beh. Brain Sci.). • Examples include (just to name a few): • Groupthink • Group polarization • Conformity with false group judgments • Etc., etc.

9. Japan China Korea A caricature of such group image the Houses of Parliamentof Japan

10. Purpose of this talk: “Mind the gap!” • How can we reconcile the two drastically different views? • “Group as an intelligent (adaptive) device” vs. • “Group as a vehicle for various biases” • In this talk, I’d like to approach this issue from a behavioral ecological perspective.

11. Behavioral ecology (=study of animal behavior from the adaptationist perspective) is also concerned with group life. • Why do some animals form groups? What functions are served by groups? • How efficient is group foraging as compared to solitary foraging? • How is risk-monitoring conducted in groups? • Although these are, in principle, the same kind of questions that have interested psychologists for many years, conversation with behavioral ecologists has been extremely rare.

12. Shared core questions • Group efficiency (Steiner, 1972) • How efficient is group performance as compared to performance by isolated individuals? • Collective wisdom (Surowiecki, 2004) • Can a group of individuals achieve a collective wisdom beyond any single individual in the group including the best and brightest member? • What cognitive, motivational, and ecological factors must exist for the collective wisdom to emerge?

13. Behavioral ecological literature“Group decision making” by honey bees • Seeley (1995) “The wisdom of the hive”

14. Searching a new nest • In a late spring or early summer, a colony of honey bees often divides itself. • The queen leaves with about 2/3 of the worker bees, and a daughter queen stays behind with the rest. • How does the swarm that has left the colony find a new home?

15. “Search committee” composed of several hundred bees • These “scout bees” fly out to inspect potential nest sites, and then perform waggle dances to advertise any good sites they have discovered. • The duration of the dance depends on bee’s perception of the site’s quality: the better the site, the longer the dance. • Other bees are more likely to visit and inspect the sites advertised by others. • Thus, high-quality sites receive more advertisement and are visited by more scout bees.

16. This process eventually leads to a group consensus. • The striking empirical fact: - When different possible nest sites vary in quality, the bees usually choose the best one. - Seeley & Buhrman (2001). Beh. Ecol. Sociobiol. - Seeley, Visscher, & Passino (2006). Amer. Sci.

17. Q. How do the bees solve the problem of interdependency? • Communication among the bees via waggle dance could create sequentialinterdependencies between decision-makers. • Carry-over and amplification of initial errors, such as seen in fads. • The honey bee GDM system may be susceptible to the erroneous informational cascades (Bikhchandani et al., 1992, J. Polit. Econ.) Errors in sequential communication

18. List, Elsholtz, & Seeley (in press). Phil. Trans. Roy. Soc. B. • Computer simulation model assuming that: • Scout bees are interdependent in that they give more attention to nest sites strongly advocated by others (i.e., conformity in nest-site search). • Simultaneously, they are independent when assessing the quality of nest sites (i.e., independence in the preference formation). • Duration of the dance is determined solely by own perception of the site’s quality. • Such a right mix of independence and interdependence can yield a high-quality GDM.

19. So, what have we learned from the behavioral ecological literature? • The honey bee “group decision making” provides a beautiful example of good coordination among members. • Honey bees have built-in cognitive/behavioral systems to enable such coordination, which yields their collective wisdom in GDM.

20. Viewing this from human group psychology • Steiner (1972) “Group process and productivity” • Group performance often suffers from two sources of inefficiencies • Coordination problems • Inefficiencies accruing from poor coordination among members • Motivation problems • Social loafing (Latané et al., 1979, JPSP) “Many hands make light the work.”

21. Motivation problems • Collective action, whereby members’ inputs are pooled into a group performance while group outcomes are shared by all members, can cause motivational loss. • Individual costs vs. Shared group outcome • Social dilemma(Dawes, 1980, An. Rev. Psych.) • Free-rider problem • How do honey bees cope with the free-rider problem?

22. Reply from behavioral ecology • Yes, free-rider problem is a serious threat to collective action. • Fortunately, honey bees are basically free from the problem, because individuals in the same nest are kin. • Helping your kin is essentially helping your clones. • But, generally, such strong kinship does not hold for human societies. • So, given the free-rider problem, “collective wisdom” may not be guaranteed in human GDM. It’s your job to study it!

23. Are humans as smart as honey bees in GDM?(Kameda, Tsukasaki, & Hastie, in prep.) • Research question • By computer simulations and an experiment, we (Hastie & Kameda, 2005, Psych Rev) have shown that Majoritarian Group Decision Making (as used by honey bees) works extremely well in locating resources in an uncertain environment. • The Majoritarian GDM beats the best/brightest member in the group in terms of performance quality. • But, the motivation problems were NOT handled explicitly in the study.

24. So, here, we ask the following questions. • When the free-rider problem exists, how efficient is the human Majoritarian GDM? • If the logic of social dilemma (Dawes, 1980) applies, the Majoritarian GDM can easily degrade into a mob rule, where no member works for the group seriously. • Can we overcome the free-rider problem in the collective action?

25. Experiment

26. Purpose • Testing the ecological rationality of the Majoritarian Group Decision Making when incentives for free-riding exist. • Comparison to groups guided by the best/brightest dictator (Hastie & Kameda, 2005, Psych Rev) • Test bed: “Foraging under uncertainty” setting created in a laboratory

27. Proximal Stochastic Cues error Environmental Events Forager C1 C2 error C3 error Location j’s resource value, Qj Laboratory simulation of “foraging under uncertainty” --Brunswikian Paradigm --

28. Procedure

29. Participants • 180 (127 males and 53 females) Hokkaido University undergraduates • Six participants were called for each hourly session. • Upon arrival, each participant was seated in a private cubicle connected by LAN. • They received further instructions individually on computer displays.

30. Individual practice session (20 trials) • Opportunities to learn about how to use the 3 stochastic cues for making choices. • Feedback about choice accuracies. • Participants could learn cue validities.

31. 6-person team • Participants were then instructed that they were a 6-person “hunting team.” • Group Decision Task: Choosing the most profitable patch from 10 patches. • The resource in the chosen patch is shared evenly among all members. • However, individual cooperation for GDM is optional and costly. Free-rider problem

32. NOTICE: We’ll decide where to hunt for the next week. We’ll meet at 8:00 am on Sunday. Need to prepare for the meeting? Must I really search information? Sunday morning? Must I be there? Voting (meeting) cost Information-search cost Cooperation costs: A metaphor

33. Both types of cooperation costs are well-recognized in the political science literature about public choice (e.g., Downs, 1957, “An economic theory of democracy”). • Voting (meeting) cost Voter’s paradox • Information search cost  Problem of ignorant voters

34. To recap, • 6-person foraging teams working in a stochastic environment • Brunswikian choice task • Parallel to the honeybee GDM situation • Individual cooperation for the team foraging is costly and optional. • Voting cost • Information search cost • Absent in the honeybee case (kinship) • On the other hand, the resource in the chosen patch is shared evenly among ALL members. • Incentives for free-riding • No sanctioning opportunity was allowed in the experiment.

35. “Patch 3”  Patch 3 “Patch 5” “Patch 3” Whether or not to incur: - Information search cost? and/or - Voting cost? Suppose 3 members appeared in the meeting (i.e., incurred the voting cost) 2 experimental conditions:Majority rule vs. Smart Dictatorship (e.g., Hastie & Kameda, 2005, Psych Rev) • Majority/plurality rule condition • The group follows the majority/plurality opinion among voters about where to hunt.

36. “Patch 3”  Patch 3 “Patch 5” Whether or not to incur: - Information search cost? and/or - Voting cost? Suppose 2 members appeared in the meeting (i.e., incurred the voting cost) • Best member rule condition • The group follows the opinion of the best member among voters (best as determined by the performance level during the practice session)

37. In the experiment, the aggregation via majority rule or the best member rule was done automatically by a computer program, after each participant decided whether or not to cooperate (i.e., to vote and/or to search information).

38. Results

39. Theoretical prediction: • If the logic of social dilemma applies, we can expect no cooperation in a group. • No one engages in costly information-search. • No one incurs cost for voting. • As a result, the Majoritarian Group Decision Making should degrade into a mob rule where nobody works seriously for the group. • The collective wisdom, as displayed by the honey bees, may not be observed in human GDM.

40. Mean frequencies of cooperative members (who search information AND vote) across trials. 6 Majoritarian GDM 5 4 3 2 Best Member Rule 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Q. Are there any cooperative members in groups? 3 out of 6 A. Yes, cooperation persisted, and was stabilized over time at about 3 out of 6 members.

41. Mean individual net profits (in Yen) Majoritarian GDM Best Member Rule F(1, 28) = 11.90, p<.01 Q. Which condition yielded greater mean individual net profit, the Majoritarian GDM or the Best Member Rule? • A. The Majoritarian GDM.

42. The human Majoritarian GDM works well even when incentives for free-riding exist !?

43. Why did the Majoritan GDM work? • “We know that some people behave altruistically in social dilemmas. This is a typical and robust finding in behavioral economics (e.g., Gintis, 2007, Beh. Brain Sci.).So, cooperation in human GDM is no news at all!” • Some cooperation observed here may have originated from such purely “altruistic” motives. • But, we don’t believe that the purely “altruistic” motive is the core reason for the stable cooperation in the collective action.

44. What is the core reason for stable cooperation in the collective action? The Majoritarian GDM under uncertainty is NOT a social dilemma!  To see this, let us revisit the payoff structure in social dilemmas.

45. When ego defects When ego cooperates Individual payoff function in social dilemmas Defection is a dominant strategy.

46. Rewriting this into Group Production Function:Group profit (per member) is a linear function of the number of cooperators in a group. δ6 δ: increment in profit with an additional cooperator δ5 δ4 δ3 δ2 δ1 • Each increment by cooperation, δ (δ1 = δ2 = δ3 = δ4 = δ5 = δ6 ), is smaller than cost for cooperation. • So, nobody cooperates.  Social dilemmas

47. No, group production function is NOT linear! Does this linear group production function hold for the Majoritarian Group Decision Making? • Quality of the Majoritarian GDM improves with more cooperators who incur costs for information search and voting,butdiminishes in margin.  Statistical property of the aggregation rule (law of large numbers)

48. Individual Payoffs in the Majoritarian GDM Mixed equilibrium When ego cooperates When ego defects • Different from the social dilemma, no dominant (pure) strategy exists. • When there are MANY OTHER cooperators, you’re personally better off defecting. • But, when there are only FEW OTHER cooperators, you’re personally better off cooperating.

49. To recap, • The Majoritarian GDM under uncertainty is not a social dilemma! • Marginally diminishing group production • Neither cooperation nor defection is dominant. • A mixed equilibrium thus emerges where cooperators and defectors coexist in a stable manner. • Thanks to those “rational cooperators”, the Majoritarian GDM can outperform the smart dictatorship by the best and brightest member.

50. Evolutionary computer simulations