Understanding and Addressing Cultural Variation in Costly Antisocial Punishment

Bryson, Joanna J., Mitchell, J., Powers, S., Sylwester, K. (2014). Understanding and Addressing Cultural Variation in Costly Antisocial Punishment. In: Gibson, M., Lawson, D. (Eds.) Advances in the Evolutionary Analysis of Human Behaviour, 1, () ( ed.). (pp. 201-222). : . Springer.



Altruistic punishment (AP)-punishment of those contributing little to the public good-has been proposed as an explanation for the extraordinary extent of human culture relative to other species. AP is seen as supporting the high levels of altruism necessary for the cooperation underlying this culture, including information exchange. However, humans will also sometimes punish those who contribute greatly to the public good, even when those contributions directly benefit the punisher. This behaviour-antisocial punishment (ASP)-is negatively correlated with gross domestic product, and may be a hindrance to overall wellbeing. In this chapter, we pursue a better understanding of ASP in particular and costly punishment in general. We explore existing data showing cultural variation in the propensity to punish, and ask how such sanctioning, whether of those who give much or little, affects the individuals who conduct it. We hypothesise that costly punishment is a mechanism for regulating investment between different levels of society, for example, whether an individual's current focus should be on their nation, village, family or self. We suggest that people are less likely to antisocially punish those they consider to be 'ingroup' and that the propensity to apply this identity to strangers may vary with socio-economic-political context and resulting individual experience. In particular, an increased propensity to express ASP should correlate with a lower probability of benefiting from public goods, as may be the case where there is a low rule of law. We show analysis of both behavioural economics experiments and evolutionary social simulations to support our hypotheses and suggest implications for policymakers and other organisations that may wish to intervene to improve general economic wellbeing.
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Simon T. Powers
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Bio-inspired Computing
The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence.

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