Humans care about fairness and are ready to suffer financial losses for the sake of it. The existence of such costly preferences for fairness constitutes an evolutionary puzzle. Recently, some authors have argued that human fairness can be understood as a psychological adaptation evolved to solve the problem of sharing the costs and benefits of cooperation. When people can choose with whom they want to cooperate, sharing the costs and benefits in an impartial way helps to be chosen as a partner and brings direct fitness benefits. In this theory, partner choice is thus the central mechanism allowing the evolution of fairness. Here, we offer an interdisciplinary study of fairness to put this theory to the test. After a review of competing theories (Paper 1, in review), we build game-theoretical models and agent-based simulations to investigate whether partner choice can explain two key aspects of human fairness: the wrongness to take advantage of one’s strength to exploit weaker people (Paper 2, Evolution), and the appeal of distributions where the reward is proportional to the contribution (Paper 3, in review). We show that partner choice succeeds at explaining these two characteristics. We also go towards more realistic and mechanism-oriented simulations by trying to evolve fair robots controlled by simple neural networks. We then test the theory empirically and show that partner choice creates fairness in a behavioral experiment (Paper 4, Proceedings of the Royal Society B). We develop a collaborative video game to assess the cross-cultural variation of fairness in distributive situations, and present results coming from a Western sample (Paper 5, in preparation). We review the experiments looking for fairness in non-human animals and discuss why fairness would have been more prone to evolve in humans than in any other species, despite partner choice being an evolutionary mechanism far from restricted to the human species. Finally, we discuss three common misunderstandings about the partner choice theory and identify interesting directions for future research.
Research Professor. Director at Learning Change Project – Research on society, culture, art, neuroscience, cognition, critical thinking, intelligence, creativity, autopoiesis, self-organization, rhizomes, complexity, systems, networks, leadership, sustainability, thinkers, futures ++
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