Stanford Computational Medicine Research Colloquium | Choosing Insight Over Overload in the Age of AI
Zoom livestream: https://stanford.zoom.us/j/97887596012?pwd=bGVpbG1uL2ZBdEd2cHQzcVJMR3p6UT09
Webinar ID: 978 8759 6012 | Passcode: 420642
KEY INFO
When: Thursday, October 29, 2026, 12:00-1:00 p.m. Pacific
Where: Tapao Hall, 3180 Porter Drive, rooms B107 and B136, Palo Alto, CA 94304, or online via Zoom
Lunch will be served during talk | Q&A will follow
AFTER THE TALK
Recordings are posted on the ARISE podcast page within a week: https://www.arise-ai.org/podcast
SPEAKERS
Philip R.O. Payne, PhD, FACMI, FAMIA, FAIMBE, FIAHSI
Chief Health AI Officer | Vice Chancellor, Biomedical Informatics and Data Science | Professor and Director, Institute for Informatics, Data Science, and Biostatistics (I2DB) | Professor, Medicine & Computer Science and Engineering at Washington University and BJC Health
Dr. Philip Payne is an internationally recognized leader in biomedical informatics, artificial intelligence, and data science. He is the Janet and Bernard Becker Professor and founding Director of the Institute for Informatics, Data Science, and Biostatistics (I2DB) at Washington University in St. Louis, where he also serves as Vice Chancellor for Biomedical Informatics and Data Science for WashU Medicine and Chief Health AI Officer for WashU Medicine and BJC Health System.
With more than twenty years of experience, he has made transformative contributions to integrating informatics and data-driven solutions in healthcare, advancing translational bioinformatics, clinical research informatics, and precision medicine to improve patient outcomes through the intelligent use of biomedical data. His research portfolio spans projects funded by the National Institutes of Health, the Agency for Healthcare Research and Quality, and industry partners, focused on leveraging complex datasets, from genomics to population health, to solve critical healthcare problems and translate laboratory breakthroughs into bedside impact.
Dr. Payne is also deeply committed to education and mentorship, having developed curricula and training programs that prepare the next generation of scientists and healthcare professionals to navigate an increasingly data-driven landscape. He is a prominent advocate for public-private partnerships that accelerate the translation of data-driven innovation into practice, and his work has earned numerous awards recognizing his standing as a thought leader at the intersection of data science, informatics, and healthcare.
THE TALK
“Choosing Insight Over Overload in the Age of AI”
Medicine has always been a knowledge-processing discipline. From the Edwin Smith papyrus and the narrative patient registers of 18th-century hospitals, to the Problem-Oriented Medical Record and today’s electronic health record, the practice of medicine has depended on standardized observation, case-based learning, documented intervention, decision support, and professional accountability.
Artificial intelligence, evolving from rule-based expert systems to statistical machine learning to today’s generative and agentic models, is the newest and most capable chapter in that history, and is natively suited to the demands of modern clinical reasoning. However, significant questions remain before this potential can be reliably realized: whether AI can match expert-level clinical judgment, how humans and AI should collaborate in high-stakes and sensitive care settings, and why even well-validated tools struggle to scale across diverse health systems.
Drawing on recent evidence from diagnostic reasoning trials, large-scale ambient documentation deployments, and multi-institutional validation studies, Dr. Payne describes two divergent paths for health systems adopting AI: one in which poor design choices compound data overload, alert fatigue, and inequity, and another in which thoughtful, explainable, and well-governed AI produces genuine insight, efficiency, and improved outcomes for clinicians and patients alike.
HOST & MODERATOR
Hosted by the Stanford Division of Computational Medicine. Moderated by Jonathan H. Chen, MD, PhD, PI at Stanford ARISE.
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