Jonathan Chen on AI in Medicine: Promise, Pitfalls, and Practice

In this episode of The Future of Medicine, we welcome Jonathan Chen, MD, PhD, clinician, AI researcher, and Associate Professor at Stanford, whose work focuses on combining human and artificial intelligence to improve clinical decision-making. Dr. Chen reflects on the rapid rise of AI in medicine, and the moment he realized everything had changed. He also walks through surprising findings from his research, including studies showing that AI alone can sometimes outperform doctors using AI tools. He explains why this happens, from human bias and “automation errors” to the ways AI systems are designed to agree with users, even when they’re wrong. Looking ahead, Dr. Chen shares his perspective on the future of AI in medicine, including the risks of overreliance, the importance of clinical judgment, and how these tools could transform everything from medical education to patient care. He also explores the concept of “do no harm” in AI systems—and why safety and accuracy are not the same thing. Thank you for watching! 🔔 Subscribe for more conversations on groundbreaking medical science and innovation. Join the conversation: – How should doctors and patients use AI responsibly? Share your thoughts in the comments below. Links: – Listen to the podcast: https://thefutureofmedicine.buzzsprou... – Watch on YouTube:    • Video   – Subscribe to our channel: @stanforddepartmentofmedicine 00:00 AI in Medicine Intro 03:54 Software Engineer Path 07:41 AI Systems Chemistry 10:13 AI Outperforms Doctors 13:09 AI Model Limitations 16:10 Automation Bias Risk ️ 19:35 Omission Harm 22:11 Clinician Advantage ‍️ 24:50 EHR Data Challenge 29:31 AI Future Vision 31:48 AI Education Role ‍ 34:25 AI Homework Dilemma 37:27 AI Feedback Loop 39:56 Magic & AI Connection 42:13 Magic & Presentations