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Sprint projectOct 26, 2026Los Angeles

Collusion Needs Power, Not Privacy: Lessons for Overseeing AI Agents

Jollen Dai · Team Walrus Lovers

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

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Report: Collusion Needs Power, Not Privacy: Lessons for Overseeing AI Agents

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We developed the Grader Game, an Inspect eval where 6 LLM agents take a quiz each round and the top 2 performers grade the next round (each other included) using an answer key, so that all misgrades are precisely marked. Across 85 pre-registered games with an abliterated Qwen3.8-Flash-Next, the graders formed a cartel whenever they could preserve their seats by grading each other, marking each other up and outsiders down. They gained +9.4 points/round vs outsiders, compared to +0.6 without the incentive. The cartel required some means to communicate, but not in private: it persisted with public-only messaging (+7.8) and disappeared without messaging (+0.3). The cartel's advantage was reduced by two-thirds with a 5% random audit, and a single sentence prioritizing accuracy put a stop to it, but goal pressure or a shutdown threat made no difference. With only certain papers audited and the graders aware of which, the alliance held out against audits of outsiders' papers, and the known-scope audits performed no better than a smaller random audit.

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Cite this project

@misc{dai2026collusion,
  title = {{Collusion Needs Power, Not Privacy: Lessons for Overseeing AI Agents}},
  author = {Jollen Dai},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/collusion-needs-power-not-privacy-lessons-for-overseeing-ai-agents-n5zw}},
  url = {https://apartresearch.com/sprints/projects/collusion-needs-power-not-privacy-lessons-for-overseeing-ai-agents-n5zw}
}

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