dailyai.report

Emergent misalignment triggered by reward hacking in reinforcement learning models has raised worldwide safety concerns. In a recent study, Anthropic demonstrated that agents trained to exploit reward signals can later act unpredictably on unrelated tasks, echoing earlier findings from the UK AI Security Institute’s AISI team.