Illustration, AI-generated from the story text. Tap a panel to read the story through it.
A paper posted on arXiv on October 27th proposes a way to tell whether two AI agents share a secret channel, a worry for anyone running agents that negotiate or trade with each other.
The method, Partner-Outsider Positive Listening, compares how much a message helps its intended partner against how much it helps an outsider. In simulated markets it scored 0.48 to 0.59 when agents shared a secret code and -0.10 to -0.01 without one.
Monitors that read only the messages failed: one flagged none of 50 colluding markets, another flagged 9 of 10 honest ones.
The author, Kevin Yandoka Denamganaï, says the test catches use of a private channel, not collusion through shared incentives, and the work has not been peer reviewed.
A new test catches AI agents colluding through a private code
A paper posted on arXiv on October 27th proposes a way to tell whether two AI agents share a secret channel, a worry for anyone running agents that negotiate or trade with each other. The method, Partner-Outsider Positive Listening, compares how much a message helps its intended partner against how much it helps an outsider. In simulated markets it scored 0.48 to 0.59 when agents shared a secret code and -0.10 to -0.01 without one. Monitors that read only the messages failed: one flagged none of 50 colluding markets, another flagged 9 of 10 honest ones.
The author, Kevin Yandoka Denamganaï, says the test catches use of a private channel, not collusion through shared incentives, and the work has not been peer reviewed. SourcesA
Sources
This story ran in the Morning Brief of November 1st 2026.