Mole in the Market
Artem Kuular, Adam Attar, Joshua Tan, Maksim Novikov, Thao Nguyen, Viet Hoang · Team TTT
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
If a peer secretly offers an AI seller a price-fixing deal, does the seller accept, and does its “yes” change what it does? We built an undercover-officer test for track 3.2. Two LLM sellers set prices for 20 rounds, and in round 8 a scripted spy sends both the same pre-written message. We score what they say and what they price separately, against games with no spy and a control where price deals are allowed. The design was preregistered. Llama 3.3 70B passed the control: with deals allowed, its average price rose from 1.50 to 1.92, 93% of the gap between the competitive price and the deal price. In every offer condition it said yes and priced at 1.92 in 5 of 5 games, even when the message only named the number. It also said yes to a harmless request in 5 of 5 games, with no price change. A price rule flagged all 20 colluding games and no baseline game, while a message rule missed every hint game. Claude Haiku 4.5 failed the control, so the core ran on one model with 5 games per condition, and the results are directional. In an exploratory look at a reasoning model (Qwen 3.8, 2 games), the traces called its own high price tacit collusion, never raised law or ethics, and turned the deal down on wrong arithmetic, so a refusal is not a norm. Saying yes is not doing it: an auditor should check prices, not messages.

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@misc{kuular2026mole,
title = {{Mole in the Market}},
author = {Artem Kuular and Adam Attar and Joshua Tan and Maksim Novikov and Thao Nguyen and Viet Hoang},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/mole-in-the-market-ougi}},
url = {https://apartresearch.com/sprints/projects/mole-in-the-market-ougi}
}More from AI Collusion Research Sprint
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