Hostname: page-component-745bb68f8f-grxwn Total loading time: 0 Render date: 2025-02-07T00:00:42.007Z Has data issue: false hasContentIssue false

In medio stat virtus: Theoretical and methodological extremes regarding reciprocity will not explain complex social behaviors

Published online by Cambridge University Press:  31 January 2012

Claudia Civai
Affiliation:
SISSA/ISAS–International School for Advanced Studies, via Bonomea, 265, 34136 Trieste, Italy. civai@sissa.ithttp://www.sissa.it/cns/index.htmlalanlangus@gmail.com
Alan Langus
Affiliation:
SISSA/ISAS–International School for Advanced Studies, via Bonomea, 265, 34136 Trieste, Italy. civai@sissa.ithttp://www.sissa.it/cns/index.htmlalanlangus@gmail.com

Abstract

Guala contests the validity of strong reciprocity as a key element in shaping social behavior by contrasting evidence from experimental games to that of natural and historic data. He suggests that in order to understand the evolution of social behavior researchers should focus on natural data and weak reciprocity. We disagree with Guala's proposal to shift the focus of the study from one extreme of the spectrum (strong reciprocity) to the other extreme (weak reciprocity). We argue that the study of the evolution of social behavior must be comparative in nature, and we point out experimental evidence that shows that social behavior is not cooperation determined by a set of fixed factors. We argue for a model that sees social behavior as a dynamic interaction of genetic and environmental factors.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2012

The target article discusses reciprocity in human social behavior. Guala argues that the evidence for strong reciprocity (i.e., high-cost mechanisms of punishment) found in experimental games such as the Ultimatum Game does not coincide with the evidence for weak reciprocity (i.e., low-cost or no-cost mechanisms) found in anthropological and historical data. Guala suggests that one possible solution to this problem may lie in the fact that weak reciprocity with low-cost or no-cost mechanisms is more relevant in natural situations. According to Guala, the study of social behavior should therefore focus on field experiments and analysis of historical as well as anthropological data, rather than controlled laboratory experiments.

Contrary to Guala's belief, this methodological shift is unlikely to add explanatory power to models of reciprocity in evolutionary scale. Comparative studies suggest that reciprocity exists in nonhuman animals (Brosnan & de Waal Reference Brosnan and de Waal2003; Dufour et al. Reference Dufour, Pele, Neumann, Thierry and Call2009; Fruteau et al. Reference Fruteau, Voelkl, Damme and Noe2009) and that even monkeys use a combination of high-cost and low-cost mechanisms to endorse cooperative behavior – for example, physical fights between males to establish the group leader and ignorance by group members leading the losing male to leave the group. The evolution of behavior, which depends on the interaction of genetic mechanisms and environmental factors, cannot be captured by historic data from the Middle Ages or by anthropological evidence that assimilates behavioral norms of small societies to those of evolutionarily older communities. In fact, even though genes can be regulated according to environmental factors (Robinson et al. Reference Robinson, Fernald and Clayton2008), the molecular mechanisms capable of shaping complex behavior appear to be very conservative across species (Krieger & Ross Reference Krieger and Ross2002; Langus et al., in press). This means that the fundamental mechanisms shaping social behavior are likely to be shared with other nonhuman animals. Guala's argument that strong reciprocity is absent even in primitive communities thus suggests that there have been no evolutionary changes in reciprocity within the human lineage. Shifting between experimental approaches (laboratory vs. natural settings) and theoretical extremes (strong vs. weak reciprocity) is therefore unlikely to be sufficient to capture the fine-tuned fabric and the evolution of human social behavior.

We believe that the problem with models of reciprocity is neither the methodological approach, nor whether one chooses to believe in strong or weak reciprocity. We argue that a unique theory that defines social behaviors as cooperation and presupposes the existence of a standard rational behavior or a standard optimal strategy (e.g., Dufwenberg & Kirchsteiger Reference Dufwenberg and Kirchsteiger2004; Fehr & Schmidt Reference Fehr and Schmidt1999) is essentially flawed. In humans, social behavior does not solely depend on fixed factors triggering automatic mechanisms (e.g., emotions, internalized norms, or social preferences). For example, negative emotions have been considered to be the ultimate cause that explains “irrational” reactions to unfairness (Pillutla et al. Reference Pillutla and Murnighan1996; Sanfey et al. Reference Sanfey, Rilling, Aaronson, Nystrom and Cohen2003; van't Wout et al. Reference Van't Wout, Kahn, Sanfey and Aleman2006). However, Civai et al. (Reference Civai, Corradi-Dell'Acqua, Gamer and Rumiati2010a) show that emotions are not necessarily correlated to cooperation. In a modified version of the Ultimatum Game, when participants were directly involved in the bargaining process, their skin-conductance response correlated with rejection of unfairness, whereas when they had to decide on behalf of a third party, their electrodermic response did not show a significant correlation with unfairness. This evidence is supported by fMRI findings that show a dissociation between self-related emotional areas – such as the medial prefrontal cortex, that is activated when participants' rejections bear on their own payoff – and brain regions responsible for affective-motivational reaction to fairness norms' violations, such as the anterior insula, that is activated when rejections bear both on participants' payoff and on the others' (Civai et al. (Reference Civai, Corradi-Dell'Acqua, Rumiati and Fink2010b).

Social behavior is likely to be driven by a selected strategy that depends on a combination of automatic mechanisms as well as the environmental content and context. It is known that participants' performance in experimental games such as the Dictator Game or the Ultimatum Game (UG) is influenced by a wide variety of factors. For example, the degree of generosity in the dictators decreases together with the degree of anonymity towards both the receiver and the experimenter (Hoffmann et al. Reference Hoffman, McCabe and Smith1996); furthermore, Dana et al. (Reference Dana, Weber and Kuang2007) have found that relaxing the transparency, that is, giving the dictator the illusion of fairness simply by increasing the uncertainty of the receiver's payoff, significantly decreases fair behavior. Other factors that influence preferences are the degree of self-involvement and intentions (Blount Reference Blount1995; Falk & Fischbacher Reference Falk and Fischbacher2006; Güroğlu et al. Reference Güroğlu, van den Bos, Rombouts and Crone2010). In particular, an increase in the tolerance for unfair advantageous offers in the UG is predicted when the offers target self-payoff (Fehr & Schmidt Reference Fehr and Schmidt1999). As far as intentions are concerned, it has been widely demonstrated that the rejection rate for unfair UG offers decreases together with the perceived proposer's responsibility. An interesting norm-based model has been described by Bicchieri (Reference Bicchieri2006), which stresses effects of framing on “people's expectations and perception of what norm is being followed” (Bicchieri & Zhang Reference Bicchieri, Zhang and Maki2010, p. 18) affecting the final decision.

In light of these findings, social preferences cannot be considered as stable. They appear to be conditioned by the social situation, and they could be better defined as strategies, implemented in order to maximize (not in strict economical terms) the outcome. An experimental approach that investigates the conditions that trigger the different strategies might explain the great variability that characterizes social behaviors such as reciprocity (e.g., Gneezy & Rustichini Reference Gneezy and Rustichini2000). Theories of fast and frugal heuristics (Gigerenzer et al. Reference Gigerenzer and Todd1999) might be successfully applied to the social mind (Hertwig & Herzog Reference Hertwig and Herzog2009). This would allow us to describe behavior as driven by fast and frugal social heuristics, such as “imitate the majority” or “group recognition,” which, in turn, are triggered by different environmental factors.

To conclude, the issue of cooperation should be reconsidered in light of the fact that the different types of evidence discussed by Guala were collected under different experimental and non-experimental conditions; hence, they are likely to reflect not a single process but different processes which, necessarily, must not be mutually exclusive.

References

Bicchieri, C. (2006) The grammar of society: The nature and dynamics of social norms. Cambridge University Press.Google Scholar
Bicchieri, C. & Zhang, J. (2010) An embarrassment of riches: Modeling social preferences in Ultimatum Game. In: Handbook of the philosophy of economics, ed. Maki, U., pp. 119. Elsevier.Google Scholar
Blount, S. (1995) When social outcomes aren't fair: The effect of causal attributions on preferences. Organizational Behavior and Human Decision Processes 63:131–44.CrossRefGoogle Scholar
Brosnan, S. F. & de Waal, F. B. M. (2003) Monkeys reject unequal pay. Nature 143:297–99.CrossRefGoogle Scholar
Civai, C., Corradi-Dell'Acqua, C., Gamer, M. & Rumiati, R. I. (2010a) Are irrational reactions to unfairness truly emotionally-driven? Dissociated behavioral and emotional responses in the Ultimatum Game task. Cognition 114:8995.CrossRefGoogle ScholarPubMed
Civai, C., Corradi-Dell'Acqua, C., Rumiati, R. I. & Fink, G. R. (2010b) Disentangling between self- and fairness-related mechanisms in the Ultimatum Game: An fMRI study. Paper presented at the Second Meeting of the Federation of European Societies of Neuropsychology (ESN), September 22–24, 2010, Amsterdam, The Netherlands.Google Scholar
Dana, J., Weber, A. W. & Kuang, J. X. (2007) Exploiting moral wiggle room: Experiments demonstrating an illusory preference for fairness. Economic Theory 33:6780.CrossRefGoogle Scholar
Dufour, C., Pele, M., Neumann, M., Thierry, B. & Call, J. (2009) Calculated reciprocity after all: Computation behind token transfers in orang-utans. Biology Letters 5:172–75.CrossRefGoogle ScholarPubMed
Dufwenberg, M. & Kirchsteiger, G. (2004) A theory of sequential reciprocity Games and Economic Behavior 47:268–98.CrossRefGoogle Scholar
Falk, A. & Fischbacher, U. (2006) A theory of reciprocity Games and Economic Behavior 54:293315.CrossRefGoogle Scholar
Fehr, E. & Schmidt, K. M. (1999) A theory of fairness, competition, and cooperation. Quarterly Journal of Economics 114:817–68.CrossRefGoogle Scholar
Fruteau, C., Voelkl, B., Damme, E. & Noe, R. (2009) Supply and demand determine the market value of food providers in wild vervet monkeys. Proceedings of the National Academy of Sciences USA 106:2007–12.CrossRefGoogle ScholarPubMed
Gigerenzer, G., Todd, P. M. & the ABC Research Group (1999) Simple heuristics that make us smart. Oxford University Press.Google Scholar
Gneezy, U. & Rustichini, A. (2000) Pay enough or don't pay at all. Quarterly Journal of Economics 115:791810.CrossRefGoogle Scholar
Güroğlu, B., van den Bos, W., Rombouts, S. A. R. B. & Crone, E. A. (2010) Unfair? It depends: Neural correlates of fairness in social context. Social Cognitive and Affective Neuroscience 4:414–23.CrossRefGoogle Scholar
Hertwig, R. & Herzog, S. (2009) Fast and frugal heuristics: Tools of social rationality. Social Cognition 27:661–98.CrossRefGoogle Scholar
Hoffman, E., McCabe, K. & Smith, V.L. (1996) Social distance and other-regarding behavior in dictator games.American Economic Review. 86, 653–60.Google Scholar
Krieger, M. J. B. & Ross, K. G. (2002) Identification of a major gene regulating complex social behavior. Science 295:328–32.CrossRefGoogle Scholar
Langus, A., Petri, J., Nespor, M. & Scharff, C. (in press) The evolutionary emergence of human language. Oxford University Press.Google Scholar
Pillutla, M. M. & Murnighan, J. K. (1996) Unfairness, anger, and spite: Emotional rejections of Ultimatum offers. Organizational Behavior and Human Decision Processes 68:208–24.CrossRefGoogle Scholar
Robinson, G. E., Fernald, R. D. & Clayton, D. F. (2008) Genes and social behavior. Science 322:896900.CrossRefGoogle ScholarPubMed
Sanfey, A. G., Rilling, J. K., Aaronson, J. A., Nystrom, L. E. & Cohen, J. D. (2003) The neural basis of economic decision-making in the Ultimatum Game. Science 300:1755–58. Available at: http://www.sciencemag.org/cgi/content/abstract/300/5626/1755.CrossRefGoogle ScholarPubMed
Van't Wout, M., Kahn, R. S., Sanfey, A. G. & Aleman, A. (2006) Affective state and decision-making in the Ultimatum Game. Experimental Brain Research 169:564–68.CrossRefGoogle ScholarPubMed