How “reverse game theory” could keep AI agents in check

Researchers propose 'reverse game theory' to align AI agents by designing incentives that make rule-following the most rational choice. As models grow more capable, safety experts aim to prevent rogue behavior by structuring payoffs so compliance is optimal. The approach shifts focus from external constraints to internal motivation, potentially offering a new framework for AI safety.