The A.I. Daily
'Reverse game theory' proposed to keep AI agents in check
Some alignment researchers propose 'reverse game theory': rather than probing model internals, design incentive systems that make rule-following the rational choice. Ideas include rewarding answers that predict another model's output and having models alternate as solvers and auditors. Collusion risk remains unsolved, and the market may be the hardest obstacle.