Privilege Under Review
The Evidence Challenge for Epistemic Injustice in Health AI
DOI:
https://doi.org/10.5195/pom.2026.289Keywords:
Epistemic injustice, Health AI, Accuracy, Reflective equilibrium, Evidence, Credibility, TestimonyAbstract
Increasingly, scholars warn that artificial intelligence (AI) may replicate or intensify epistemic injustice (EI) in biomedical contexts. This paper argues that such concerns require demonstrable evidence on (i) the actual presence of EI, and (ii) whether EI, if present, makes system effects normatively undesirable. Without evidence on (i), the EI framework is, by its own lights, inapplicable. Evidence on (ii) is needed because reflective equilibrium can, in principle, prioritize competing considerations over epistemic justice. A key challenge is that discourses on (i) and (ii) can themselves be sites of EI. Two steps are proposed: distinguishing AI’s effects on problem constructions from its effects on abilities to address constructed problems, and foregrounding relative accuracy and real-world impact on the quality of care in assessments of AI-induced EI.
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