When the Worker Learns the Monitor's Blind Spots
TL;DR for operators An AI monitor that performs well before an agent begins learning may become unreliable as the agent adapts to its judgments. Monitor accuracy is therefore an ongoing property of the worker-monitor interaction, not merely a deployment-time benchmark. Research on continuously co-trained monitors establishes a theoretical condition under which occasional reliable corrections can support increasingly accurate oversight while the fraction of externally verified actions approaches zero. When legitimate work also remains sufficiently rewarding, better monitoring can discourage cheating rather than merely detect it. ...