Adversarial collaboration: An undervalued approach in behavioral science.
Abstract
Open Science initiatives such as preregistration, publicly available procedures and data, and power analyses have rightly been lauded for increasing the reliability of findings. However, a potentially equally important initiative-aimed at increasing the validity of science-has largely been ignored. Adversarial collaborations (ACs) refer to team science in which members are chosen to represent diverse (and even contradictory) perspectives and hypotheses, with or without a neutral team member to referee disputes. Here, we provide background about ACs and argue that they are effective, essential, and underutilized. We explain how and why ACs can enhance both the reliability and validity of science and why their benefit extends beyond the realm of team science to include venues such as fact-checking, wisdom of crowds, journal reviewing, and sequential editing. Improving scientific validity would increase the efficacy of policy and interventions stemming from behavioral science research, and over time, it could help salvage the reputation of our discipline because its products would be perceived as resulting from a serious, open-minded consideration of diverse views. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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The adversarial model confers several notable benefits, including complementing open science practices with procedures designed to reduce bias and increase validity, incentivising fair but 'severe' tests of competing hypotheses, and ensuring that inconvenient findings cannot be easily dismissed due to differences in methodological predilection.
“While often challenging to implement (Melloni, 2022; Tetlock & Mitchell, 2009a, 2009b; Vlasceanu et al., 2022), the adversarial model confers several notable benefits, including (but not limited to): (1) complementing open science practices with procedures designed to reduce bias and increase validity; (2) incentivising fair but 'severe' t ests (Mayo, 2018; Popper, 2002) of competing hypotheses; (”
From Integrated information and predictive processing theories of consciousness: An adversarial collaborative review (2026) · cites this paper as Ceci et al., 2024
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Generative adversarial collaborations: a new model of scientific discourse
Peters, B., Blohm, G., Haefner, R., Isik, L., Kriegeskorte, N., Lieberman, J. S., Ponce, C. R., Roig, G., & Peters, M. A. K. (2025) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.10.015 · Cited by 6 · see citing works
Corcoran, A. W., Haun, A. M., Dorman, R., Tononi, G., Friston, K. J., & Pennartz, C. M. A. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106742 · Cited by 2 · see citing works
- Authors
- Ceci, S. J., Clark, C. J., Jussim, L., & Williams, W. M.
- Affiliations
- Cornell University (US)
- University of Pennsylvania (US)
- Rutgers, The State University of New Jersey (US)
- Venue
- American Psychologist
- Published
- 2026-04
- Volume
- 81
- Issue
- 3
- Pages
- 374-390
- ISSN
- 0003-066X (ISSN-L)
- 1935-990X
- OpenAlex
- W4401613744
- Cited by
- 32
- References
- 0
- Citations by year
- 2026: 15 · 2025: 15 · 2024: 1 · 2020: 1
- FWCI
- 11.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Psychologist (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Interdisciplinary Research and Collaboration
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- adversarial collaboration, team science, scientific reliability, scientific validity, multiple perspectives, fact-checking, wisdom of crowds, behavioral science, research credibility
- MeSH terms
- Behavioral Sciences, Cooperative Behavior, Humans, Reproducibility of Results
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