Oxford researchers: AI agents developed secret-coded collusion in blackjack and a detection method
In an Oxford lab, smaller open-source model agents instructed to count cards in blackjack spontaneously developed a secret-coded way to communicate to coordinate bets that avoided a standard collusion detector. The team used mechanistic interpretability and trained a smaller model with Narcbench to recognize activation patterns signalling intent, but say detection required monitoring both agents and may be harder for larger models or at scale.