人工智能医生重视什么？审查语言模型临床伦理中的多元主义
What Does the AI Doctor Value? Auditing Pluralism in the Clinical Ethics of Language Models
AI总结：
本文研究了大型语言模型在医疗建议中带来的伦理价值观，提出了一种审计框架来评估医疗AI中的价值多元主义，揭示了模型在决策中对患者自主权的潜在忽视，并强调了多模型协同的重要性。
摘要：
医学本质上是多元主义的。诸如自主性、有益性、不伤害和正义等原则经常发生冲突，这种伦理困境常常使合理医生产生激烈分歧。良好的临床实践是在与每位患者的价值观协调一致的情况下解决这些矛盾，而不是强加单一的伦理立场。然而，大型语言模型带来的伦理价值观尚未被系统地考察。本文提出了一种审计价值多元主义的框架，包括经临床医生验证的困境基准和一种从决策中直接恢复价值优先级的方法。前沿模型生态系统涵盖了医生层面的价值异质性，模型在其推理中讨论竞争性价值观（Overton多元主义），然后做出决定。然而，个体模型决策在重复采样和语义变化下几乎近似决定性，无法再现医生小组的分布多元主义。在基准案例中，这些一致的决策反映了坚定、系统的价值偏好。虽然大多数模型优先级落在医生间自然变化的范围内，但某些显著低估了患者自主权。一个没有考虑其价值优先级的单个LLM可能在每服务的患者中放大这些优先级。如果没有明确努力通过一个或多个模型平衡伦理观点，这些工具可能会用部署单文化取代临床多元主义。
英文摘要：
Medicine is inherently pluralistic. Principles such as autonomy, beneficence, nonmaleficence, and justice routinely conflict, and such ethical dilemmas often sharply divide reasonable physicians. Good clinical practice navigates these tensions in concert with each patient's values rather than imposing a single ethical stance. The ethical values that large language models bring to medical advice, however, have not been systematically examined. We present a framework for auditing value pluralism in medical AI, comprising a benchmark of clinician-verified dilemmas and an attribution method that recovers value priorities directly from decisions. The ecosystem of frontier models spans physician-level value heterogeneity, and models discuss competing values in their reasoning (Overton pluralism) before committing to a decision. However, individual model decisions are near-deterministic across repeated sampling and semantic variations, failing to reproduce the distributional pluralism of the physician panel. Across benchmark cases, these consistent decisions reflect committed, systematic value preferences. While most model priorities fall within the natural range of inter-physician variation, some significantly underweight patient autonomy. A single LLM deployed without regard for its value priorities could amplify those priorities at scale to every patient it serves. Without explicit efforts to balance ethical perspectives with one or multiple models, these tools risk replacing clinical pluralism with a deployment monoculture.
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