When the AI Speaks: Nursing, Authority, and Accountability in Algorithmic Explanation
Central question: What happens—ethically and practically—when large language models start explaining clinical findings directly to patients and families, particularly in nursing-led communication?
What this might mean
As LLM-generated explanations seep into daily practice, interpretive authority shifts. Nurses may find themselves relaying or mediating algorithmic outputs, while patients receive clearer but potentially less nuanced communication. The redistribution of explanation risks blurring accountability, especially when uncertainty or error emerges. There is still little empirical anchoring for how patients process, trust, or act on algorithmic explanations in high-stakes, ambiguous cases—especially in geriatrics.