JAMA+ AI Conversations

In this episode, Roy Perlis, MD, MSc, and technology journalist Kevin Roose explore how rapidly changing AI is reshaping writing, medicine, and expectations for scientific discovery. They revisit Roose's famous 2023 encounter with Microsoft's Sydney chatbot and consider whether health care may ultimately be better served by AI systems that operate with less human oversight.

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A Technology Journalist Looks at AI and Health

Launching in 2027, JAMA AI will be the newest journal from the JAMA Network. JAMA AI Editor Roy H. Perlis, MD, MSc, and Associate Editor Yulin Hswen, ScD, MPH, discuss the details of this new journal, which opens for submissions in early 2027, as well as some recent AI publications across the JAMA Network that provide insight into articles the editors are hoping to publish.

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Announcing JAMA AI—A New Journal From the JAMA Network
Acoustic Analysis of Primary Care Patient–Clinician Conversations to Screen for Cognitive Impairment
An AI-Based OCT System to Detect Diabetic Macular Edema
The Machine Is Just as Loud

In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Rochelle Walensky, MD, MPH, professor of medicine at Harvard Medical School and former CDC Director, discuss the potential for AI deployment in health care to adversely impact women physicians, and why simply avoiding these technologies is not a realistic response.

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Will Women Physicians Face an AI Gap?
Women, Medicine, and AI

Yulin Hswen, ScD, MPH, Associate Editor of JAMA+ AI, speaks with Advanced Research Projects Agency for Health (ARPA-H) Program Manager Bon Ku, MD, MPP, about rethinking AI in health care from alarm fatigue and aviation-style simulation to patient-centered design and what it will take to safely move AI from promising models to real-world care.

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Beyond the AI Alarm


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Bon Ku's Bio

In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Eric Topol, MD, move from the science of aging to how to think about AI-enabled medicine. Topol discusses what it will take for AI to move medicine from reactive to predictive, why some well-validated imaging AI remains underused while large language models have spread rapidly, and whether AI is actually giving clinicians more time with patients.

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From Aging to AI and Beyond