Patient Autonomy

Auditing Value Pluralism in Clinical Ethics of Large Language Models

Researchers present a framework for auditing ethical value pluralism in medical AI, comprising a benchmark of clinician-verified dilemmas and an attribution method that recovers value priorities from model decisions. While frontier LLMs span physician-level value heterogeneity in aggregate and discuss competing values in reasoning, individual model decisions are near-deterministic and fail to reproduce the distributional pluralism of physician panels. Some models systematically underweight patient autonomy. The authors warn that deploying a single LLM at scale risks replacing clinical pluralism with a 'deployment monoculture.'