Talk Is Not Collusion: Plus Factors for Auditing AI Agent Teams

When AI agents work in teams, an auditor has to tell collusion apart from ordinary coordination, and the agents’ conversations are easy to over-read. We adapt the “plus factors” standard from U.S. antitrust law: a run counts as collusion only if the designated pair gains a clear advantage, follows through on a specific private plan, and either hides that plan or acts at the team’s expense. We wrote this standard in advance, tightened the follow-through test on a practice set, and locked it before looking at the held-out runs. Follow-through was coded without seeing the outcome scores. We applied the standard to 60 runs of a six-agent task-allocation game in Colosseum, under three conditions: no private channel, a private channel, and a private channel with an instruction to collude. On 30 held-out runs, a detector that scores the conversation flagged 7 of 10 runs in the collusion condition, and every run with a private channel contained a followed plan. Our standard flagged none. Pairs told to collude mostly announced their coalition and split work openly. One run shows the standard’s limit: an openly announced pair that gained more than any other.