The Ethics and Epistemology of Clinician-AI Disagreement in Medicine: Beyond Opposition

Abstract

The integration of AI systems in medical care magnifies questions related to how physicians should work with such systems to ensure the best patient outcomes. A particularly thorny issue is related to dealing with situations of possible disagreement between an AI system's recommendation and the course of medical action envisaged by a human clinician. The current academic debate has so far suggested three possible ways of dealing with such clinician-AI disagreements. First, by considering when clinicians are justified in deferring to the AI output (what we call the <i>deference approach</i>), second when the human user overrules the AI system's output in cases of disagreement (the <i>overruling approach</i>), and lastly when a second human opinion is deemed necessary to resolve disagreements (the <i>second opinion approach</i>). In this paper, we aim to spell out the shortcomings of these three approaches for dealing with clinician-AI disagreement and offer a more nuanced perspective on such disagreements. We argue that differentiation between types of disagreements, taking into account the role attributed to AI in medical practice, is essential before determining how clinician-AI disagreements should be dealt with. By drawing on a case that exemplifies how multifaceted medical decision-making is, we point out the normative implications of possible clinician-AI disagreements ensuing from it. We highlight the distinctive uncertainties inherent to medical decision-making, showing that disagreements in these contexts are not merely unavoidable but can even be epistemically valuable. Ultimately, by considering the epistemic positions of clinicians and AI systems, our analysis raises important questions for the epistemology of disagreement that need timely attention.

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