Do Language Models Share Your Doctor's Priorities? Measuring Values from Clinical Decisions
Payal Chandak, Victoria Alkin, David Wu, Maya Dagan, Taposh Dutta Roy, Maria Clara Saad Menezes, Ayush Noori, Nirali Somia 等 14 位作者
原文摘要
Clinical decisions often require weighing autonomy, beneficence, nonmaleficence, and justice. Reasonable physicians may prioritize these values differently, yet the values that language models bring to medical advice remain poorly characterized. We introduce ValuePrism, an instrument for measuring value priorities from clinical decisions. ValuePrism combines a benchmark of 50 clinical dilemmas, each reviewed by two physicians, with an attribution method that estimates relative value priorities from choices between medically reasonable recommendations. Each case presents a clinical vignette and two mutually exclusive recommendations designed so that choosing one necessarily promotes certain values at the expense of others. Applying the instrument to frontier language models and a US-based physician panel, we find that models frequently acknowledge values favoring both recommendations but make highly consistent decisions across repeated queries, even on cases that sharply divide physicians. The ValuePrism attribution method shows that both physicians and language models express differentiated value priorities. Collectively, model values exhibit substantial diversity and most tend to fall within the physician-panel reference range. Nevertheless, a single model deployed unchecked would amplify its particular values to patients at scale. ValuePrism provides a common basis for measuring and comparing the clinical value priorities expressed by language models and physicians. Data and code are available at https://github.com/payalchandak/value-prism.
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