Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.
PLoS One. 2022 Mar 2;17(3):e0263028. doi: 10.1371/journal.pone.0263028. eCollection 2022.
Identifying mechanisms able to sustain costly cooperation among self-interested agents is a central problem across social and biological sciences. One possible solution is peer punishment: when agents have an opportunity to sanction defectors, classical behavioral experiments suggest that cooperation can take root. Overlooked from standard experimental designs, however, is the fact that real-world human punishment-the administration of justice-is intrinsically noisy. Here we show that stochastic punishment falls short of sustaining cooperation in the repeated public good game. As punishment noise increases, we find that contributions decrease and punishment efforts intensify, resulting in a 45% drop in gains compared to a noiseless control. Moreover, we observe that uncertainty causes a rise in antisocial punishment, a mutually harmful behavior previously associated with societies with a weak rule of law. Our approach brings to light challenges to cooperation that cannot be explained by economic rationality and strengthens the case for further investigations of the effect of noise-and not just bias-on human behavior.
确定能够维持自利主体之间昂贵合作的机制是社会和生物科学的核心问题。一种可能的解决方案是同伴惩罚:当主体有机会制裁背叛者时,经典的行为实验表明合作可以扎根。然而,从标准实验设计中忽略的是,现实世界中的人类惩罚——执法——本质上是嘈杂的。在这里,我们表明,随机惩罚不足以维持重复公共利益游戏中的合作。随着惩罚噪音的增加,我们发现贡献减少,惩罚力度加大,与无噪音控制相比,收益下降 45%。此外,我们观察到不确定性导致反社会惩罚的增加,这种相互有害的行为以前与法治薄弱的社会有关。我们的方法揭示了不能仅用经济理性解释的合作挑战,并加强了对噪声(而不仅仅是偏差)对人类行为影响的进一步研究的理由。