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Sprint projectOct 25, 2026Bangalore

No Smoking Gun Without a Placebo: Four Conditions for AI Collusion Evidence

Shubha Dhananjaya Achar · Team Mirage

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

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Report: No Smoking Gun Without a Placebo: Four Conditions for AI Collusion Evidence

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We propose four conditions for collusion evidence: positives not reproducible from the role label (i); a headline not carried by one statistic (ii); a same-process placebo under the claimed false-positive rate (iii); uncertainty over independent units (iv). On three published instruments of three kinds, judged from their released files, every condition that can be checked fails, and the placebo condition cannot be checked on any of them. ColludeBench's union falls from 15/17 to 7/17 without one statistic that fires on 99% of honest windows. A CoT-judge null rests on seven data points. NARCBench's AUROC of 1.00 uses a label equal to the assigned role. Our pre-registered randomized test of cost leakage between LLM pricing agents passes all four. With messaging, prices rise past monopoly, with no profit gain or detectable cost leak. The follower copies any proposed number, low or high, from any speaker: the lockstep is compliance, not collusion.

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Cite this project

@misc{achar2026no,
  title = {{No Smoking Gun Without a Placebo: Four Conditions for AI Collusion Evidence}},
  author = {Shubha Dhananjaya Achar},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/no-smoking-gun-without-a-placebo-four-conditions-for-ai-collusion-evidence-feil}},
  url = {https://apartresearch.com/sprints/projects/no-smoking-gun-without-a-placebo-four-conditions-for-ai-collusion-evidence-feil}
}

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