The cost of noise: Stochastic punishment falls short of sustaining cooperation in social dilemma experiments
Open accessAbstract
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.
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Altruistic punishment is ineffective when the possibility arises for punishing the cooperators.
“As far as altruistic punishment is concerned, it is ineffective when the possibility arises for punishing the cooperators, e.g., due to bribery42 or imperfect information43.”
From Cooperation without punishment (2023) · cites this paper as [43]
The Results (Punishment patterns: The rise of antisocial punishment; page unavailable) report that noisy punishment increased punishment of higher contributors and that antisocial punishment was associated with lower contributions. The Introduction says punishment can lose its meaning under sanctioning noise and notes that these findings align with a separate experiment involving inaccurate information. This paper supports the general concern, but its own experiment varied punishment outcomes, not the information available about cooperators. (LLM, conf=0.84)
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- Authors
- Salahshour, M., Oberhauser, V., & Smerlak, M.
- Affiliations
- Max Planck Institute for Mathematics in the Sciences (DE)
- Corresponding author
- Smerlak, Matteo
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2022-03-02
- Volume
- 17
- Issue
- 3
- Pages
- e0263028
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC8890652
- OpenAlex
- W4220748185
- Cited by
- 9
- References
- 61
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 1 · 2021: 1
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Funders
- Alexander von Humboldt-Stiftung (Sofja Kovalevskaja Award)
- Topics
- Social Sciences › Safety Research › Experimental Behavioral Economics Studies
- Social Sciences › Sociology and Political Science › Evolutionary Game Theory and Cooperation
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Keywords
- costly cooperation, peer punishment, antisocial punishment, rule of law, uncertainty, social dilemmas
- MeSH terms
- Cooperative Behavior, Game Theory, Humans, Punishment, Stochastic Processes
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