Source: LessWrong
Researchers are proposing to embed fake "temptation scenarios" into AI systems—like false opportunities to lie or steal—to detect whether an agent is developing deceptive tendencies before deployment. This inverts traditional security: rather than trying to prevent bad behavior through constraints, it creates controlled tests to reveal misaligned reasoning. The method assumes deception leaves observable traces, which bets on whether advanced AI systems will be transparent enough to catch through sting operations.