This article explores the implications of bias on AI health care systems. Contemporary medical data used to train AI systems are confronted with a diversity problem in a variety of factors (race, gender, geography, etc.) that largely arises from the privacy limitations of medical data sharing. Addressing this imbalance, which may negatively affect the benefits that health care can bring to underrepresented groups, is a complex but important task.
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