Optimizing Human-Centric Objectives in AI-Assisted Decision-Making with Offline Reinforcement Learning

The authors propose offline reinforcement learning as a method to optimize human-centric objectives in AI-assisted decision-making, focusing on accuracy and learning. Their approach adapts support based on context and individual differences.