How reverse game theory could keep AI agents in check

Alignment researchers are exploring reverse game theory, also called mechanism design, which designs incentive structures that push AI agents toward desired behavior instead of trying to inspect their internal reasoning. An MIT-led preprint proposes rewarding a model for how well its answers predict a second model's output, so sandbagging tests becomes a losing bet, and suggests pitting agents against each other or pairing oppositely biased agents.