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AI and Medical Education: Possibilities and Pitfalls

CLIME | Recorded January 30, 2025

Christy Boscardin, PhD, MA

Christy Boscardin, PhD, is a professor in the Departments of Medicine and Anesthesia at UCSF and serves as Director of AI and Student Assessment in the School of Medicine. Her research focuses on medical education, assessment, AI, and equitable access to care. She also leads Medical Education Scholarship in Anesthesia. Dr. Boscardin holds degrees from UC Berkeley, Stanford, and UCLA, and serves as statistical editor for Perspectives on Medical Education and on the editorial board of Teaching and Learning in Medicine.

Brian Gin, MD, PhD

Dr. Gin is a pediatric hospitalist and medical educator with a background in chemistry, education, and computational science. He holds an MD and fellowship training from UCSF, an MA in Education and PhD in Chemistry from UC Berkeley, and is currently pursuing a PhD in Health Professions Education through Utrecht University and UCS.

His research focuses on entrustment in clinical education and the use of AI to support learning, assessment, and clinical decision-making. He is especially interested in developing open-source AI tools to increase accessibility and guide the responsible integration of AI in health professions education.

Key Takeaways

In this session, Drs. Christy Boscardin and Brian Gin explored how AI is reshaping medical education. They highlighted five key areas where AI is making an impact: admissions, classroom learning, workplace-based learning, assessment, and program evaluation.

Key insights:

  • AI is already being used to personalize learning, support feedback, analyze admissions materials, and automate assessments.

  • Custom AI tools can streamline research and literature reviews.

  • Major challenges include bias, over-reliance, loss of foundational skills, and unequal access to AI tools.

  • What’s next: Developing AI literacy, promoting open-source tools, and building collaborative research networks to keep up with rapid innovation.

The future of AI in med ed is bright, but it needs thoughtful, equitable implementation

WATCH THE RECORDING

Recorded on January 30,2025, Captions Available

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