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Sprint projectOct 26, 2026Hong Kong

Many Agents, Partial Views: Auditing AI Collusion at Scale with Limited Information

Sergei Kudriashov, Sergey Volkov · Team SLAI

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

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AI agents may have different owners, share a model, and reveal only part of their activity. Auditing them is costly: similar actions may be independent, but reading every record is impractical. We study two steps toward a practical audit. First, a population screen uses actions and shared market context to select interactions for review. Second, a selective audit reveals chosen records and checks for agreement, prohibited actions, and missing permission. In controlled experiments, the screen handles millions of simulated agents, while structured selection finds evidence from only part of a log. The steps have not yet been combined, and language-model readers can miss evidence or falsely support a claim. Our next priority is to connect screening with careful evidence review, then test the full process across owners and tasks using independent labels. Similarity should guide where to look; it is not proof of collusion. False alarms matter when true cases are rare.

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Cite this project

@misc{kudriashov2026many,
  title = {{Many Agents, Partial Views: Auditing AI Collusion at Scale with Limited Information}},
  author = {Sergei Kudriashov and Sergey Volkov},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/many-agents-partial-views-auditing-ai-collusion-at-scale-with-limited-information-jyj9}},
  url = {https://apartresearch.com/sprints/projects/many-agents-partial-views-auditing-ai-collusion-at-scale-with-limited-information-jyj9}
}

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