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Exclusion Cycles: Reinforcing Disparities In Medicine, Ana Bracic, Shawneequa L. Callier, Nicholson Price
Exclusion Cycles: Reinforcing Disparities In Medicine, Ana Bracic, Shawneequa L. Callier, Nicholson Price
Articles
Minoritized populations face exclusion across contexts from politics to welfare to medicine. In medicine, exclusion manifests in substantial disparities in practice and in outcome. While these disparities arise from many sources, the interaction between institutions, dominant-group behaviors, and minoritized responses shape the overall pattern and are key to improving it. We apply the theory of exclusion cycles to medical practice, the collection of medical big data, and the development of artificial intelligence in medicine. These cycles are both self-reinforcing and other-reinforcing, leading to dismayingly persistent exclusion. The interactions between such cycles offer lessons and prescriptions for effective policy.
Potential Liability For Physicians Using Artificial Intelligence, W. Nicholson Price Ii, Sara Gerke, I Glenn Cohen
Potential Liability For Physicians Using Artificial Intelligence, W. Nicholson Price Ii, Sara Gerke, I Glenn Cohen
Articles
Artificial intelligence (AI) is quickly making inroads into medical practice, especially in forms that rely on machine learning, with a mix of hope and hype. Multiple AI-based products have now been approved or cleared by the US Food and Drug Administration (FDA), and health systems and hospitals are increasingly deploying AI-based systems. For example, medical AI can support clinical decisions, such as recommending drugs or dosages or interpreting radiological images.2 One key difference from most traditional clinical decision support software is that some medical AI may communicate results or recommendations to the care team without being able to communicate the …