Whose doctor does the AI recommend? An algorithm audit of reputation and demographic signals in large language model-assisted physician choice
Critical research on algorithmic bias detection methods that challenges reliance on model self-explanations for transparency.
AI Summary
AI audit study finds LLM physician recommendations show demographic bias favoring female and minority doctors despite models' explanations not mentioning these factors.
Excerpt
Patients increasingly ask large language model (LLM) assistants which doctor to see, making these systems AI infomediaries: algorithms that intermediate one person's choice among other people and thereby decide, silently and at scale, which physicians become visible. We report a prespecified randomized algorithm audit of what causally moves those recommendations. Seven models (six open-weight; gpt-4o-mini) each chose among five synthetic family-medicine physician cards whose attributes were inde