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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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How much would this matter for the field if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

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  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

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  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
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  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

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  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
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  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.
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  1. While understandably narrow in scope given the time constraints, this submission is solid! I really like the research direction of measuring agents against each other. Games like these, applied to models trained using differing algorithms, seem promising for empirical agent foundations research!

    One thing I might add is that the game itself could have been explained more clearly, perhaps using a graphic.

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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