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The emergence of artificial intelligence (AI) in health care offers unprecedented opportunities to improve patient and clinical team outcomes, reduce costs, and impact population health. While there have been a number of promising examples of AI applications in health care, it is imperative to proceed with caution or risk the potential of user disillusionment, another AI winter, or futher exacerbation of existing health- and technology-driven disparities.

This Special Publication synthesizes current knowledge to offer a reference document for relevant health care stakeholders. It outlines the current and near-term AI solutions; highlights the challenges, limitations, and best practices for AI development, adoption, and maintenance; offers an overview of the legal and regulatory landscape for AI tools designed for health care application; prioritizes the need for equity, inclusion, and a human rights lens for this work; and outlines key considerations for moving forward. 

AI is poised to make transformative and disruptive advances in health care, but it is prudent to balance the need for thoughtful, inclusive health care AI that plans for and actively manages and reduces potential unintended consequences, while not yielding to marketing hype and profit motives. 

Authors

• Michael Matheny (Co-Chair), Vanderbilt University Medical Center and the Department of Veterans Affairs
• Sonoo Thadaney Israni (Co-Chair), Stanford University
• Andrew Auerbach, University of California, San Francisco
• Andrew Beam, Harvard University
• Paul Bleicher, OptumLabs
• Wendy Chapman, University of Melbourne
• Jonathan Chen, Stanford University
• Guilherme Del Fiol, University of Utah
• Hossein Estiri, Harvard Medical School
• James Fackler, Johns Hopkins School of Medicine
• Stephan Fihn, University of Washington
• Anna Goldenberg, University of Toronto
• Seth Hain, Epic
• Jaimee Heffner, Fred Hutchinson Cancer Research Center