Fairness metrics for health AI: we have a long way to go

Abstract

The use of Artificial Intelligence (AI) is on track to revolutionize healthcare, with performance in medical tasks such as clinical diagnosis often being comparable to expert-level accuracy, at least in the laboratory. AI can play a significant role in healthcare, enabling clinicians to make more accurate and timely diagnoses and devise effective treatment plans. However, the amplification of pre-existing healthcare inequity with the use of AI models is a legitimate concern. Recent works have shown that medical imaging AI models can easily encode and learn patient-sensitive characteristics1 and cause significant performance disparities between patient subgroups.

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