Reinforcement Learning with Human Feedback (RLHF) in AI Safety: Mechanisms, Risks, and Evaluation Approaches
Reinforcement learning with human feedback (RLHF) is a machine-learning paradigm used to align AI behavior with human preferences by training models through iterative interaction and reward shaping. Although RLHF is often discussed in safety contexts, its “clinical” relevance is best understood in terms of decision-making under constraints: RLHF changes how an agent selects actions, predicts… Read More »