Brief Building Equitable Artificial Intelligence in Health Care
Subtitle
Addressing Current Challenges and Exploring Future Opportunities
Anna Zink, Sarah Morriss, Anuj Gangopadhyaya, Ziad Obermeyer
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Artificial intelligence (AI) applications in health care are prone to biases that could perpetuate health disparities. In this paper, we study the ways in which AI may maintain, perpetuate, or worsen inequitable outcomes in health care. We review current approaches to evaluating and mitigating biased AI and potential applications of AI to address health equities. Finally, we discuss current incentives for equitable AI and potential changes in the regulation and policy space. As AI becomes increasingly embedded in the daily operations of health care systems, it is imperative that we understand its risks and evaluate its impacts on health equity. 

Research Areas Race and equity Health and health care
Tags Structural racism in research, data, and technology Health equity
Policy Centers Health Policy Center
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