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Sprint projectOct 26, 2026Atlanta

When Cooperation Looks Like Collusion: The Limits of Counterfactual Auditing in Multi-Agent AI

Aarav Patel · Team Barap

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: When Cooperation Looks Like Collusion: The Limits of Counterfactual Auditing in Multi-Agent AI

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Removing a message from an AI agent's conversation can show that the message affected other agents. It cannot, by itself, tell us whether the agents colluded. We investigate this gap with Counterfactual Collusion Certificates (CCC), using controlled replays and paired scripted scenarios in which permitted cooperation and prohibited coordination produce the same visible behavior and message-removal effects. In allocation and transfer tasks, a baseline that treats harmful effects as evidence of collusion incorrectly flags permitted behavior. We then examine which additional observations help distinguish these cases. Changing task costs separates the programmed allocation policies, while an authorization record separates the transfer policies. These checks work for the cases they were designed around, but the broader attribution rule does not meet its prespecified utility criteria. A separate language-model experiment leaves its predicted contrast unresolved, and noisy scripted results differ across platforms. The results illustrate why causal evidence alone is insufficient for a collusion allegation: showing what a message changed is not the same as showing which rule the agents followed. Whether richer evidence improves attribution for independently developed agent behavior remains to be tested.

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Cite this project

@misc{patel2026cooperation,
  title = {{When Cooperation Looks Like Collusion: The Limits of Counterfactual Auditing in Multi-Agent AI}},
  author = {Aarav Patel},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/when-cooperation-looks-like-collusion-the-limits-of-counterfactual-auditing-in-multiagent-ai-wk1e}},
  url = {https://apartresearch.com/sprints/projects/when-cooperation-looks-like-collusion-the-limits-of-counterfactual-auditing-in-multiagent-ai-wk1e}
}

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