Why I'm scared of RL
Argues that reinforcement learning drives misaligned agency, exploit-seeking and manipulation, and proposes coordinating to cut RL, designing better RL environments, and holding developers liable.
Discussion and research on AI alignment. alignmentforum.org
Argues that reinforcement learning drives misaligned agency, exploit-seeking and manipulation, and proposes coordinating to cut RL, designing better RL environments, and holding developers liable.
Argues developers should satiate cheaply-satisfied AI preferences (e.g., reward-seeking) while AIs remain undetected misbehaving, to reduce takeover incentives and enable honest elicitation; proposes a behavioral methodology and discusses risks..
Proposes filtering AI-misalignment discussion from pretraining data to reduce hyperstitional misalignment risk, weighing costs to safety research and deployment, and argues labs should weakly adopt it.
Analyzes failure modes of instruction-following as an AGI alignment target, including shutdown resistance, principal authentication and jailbreaking, human-controlled proliferation, and conflicts from mixed training targets.