Our world is changing rapidly, and it is critical that the health and medical sectors keep pace.
Readiness and adaptation must be core values across science, education, and clinical practice to meet the health needs of the future. At the National Academy of Medicine, we work to anticipate solutions for tomorrow’s challenges.
Initiative
Health Care Artificial Intelligence Code of Conduct
The NAM is developing a framework to ensure that AI algorithms and their application in health, health care, and biomedical science perform accurately, safely, reliably, and ethically in the service of better health for all. With this guidance in hand, health care will move closer to the algorithmic integrity and national architecture required to achieve AI’s promise and avoid the peril.
Related Resources

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Anticipatory Assessment: A New Imperative for Responsible Biomedical Innovation
Emerging technologies are redefining expectations for health and medicine and accelerating the pace of innovation. The radical novelty and convergence of platform technologies, including mRNA, gene editing, and artificial intelligence, are creating remarkable opportunities to prevent disease, personalize care, and transform health systems. For example, mRNA platform technology enabled rapid vaccine development during the COVID-19 pandemic and provided the foundation […]
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Patient Safety in the Era of AI: Draft Conditions for the Design of Safe Care
This commentary was developed under the auspices of the National Academy of Medicine (NAM)’s Steering Group on Patient Safety in the Era of AI. Introduction In the quarter-century since the publication of To Err Is Human, both the awareness and the context for patient safety have changed markedly (IOM, 2000). Treatment and diagnostic modalities have increased considerably, care systems have […]
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The current discourse surrounding artificial intelligence (AI) in health care demands a more rigorous examination of the disparity between prospective capabilities and empirically validated outcomes. As enthusiasm outpaces evidence, health care institutions face a critical inflection point. From the perspective of a researcher whose work in medical AI predates the current enthusiasm cycle, and whose belief in the technology’s fundamental […]
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