AI in Medical Education: Using the Missions of Medical Education as a Guide - January 23

Alison J. Whelan, MD oversees efforts that prepare and assist deans, faculty leaders, educators, and future physicians for the challenges of 21st century academic medicine. She leads a staff that addresses critical medical school data, administrative, and operational issues; explores new models of successful mission alignment; focuses on key student and faculty issues; transforms current models of education and workforce preparation across the full continuum of medical education; and supports medical school accreditation activities. 

Prior to joining the association in 2016 as Chief Medical Education Officer, Dr. Whelan served as Professor of Medicine and Pediatrics at Washington University School of Medicine in St. Louis. She held multiple education roles: course director, clerkship director, curriculum dean and ultimately was appointed the inaugural Senior Associate Dean for Education. In this role she oversaw the continuum of medical education from medical school admissions through CME. 

Dr. Whelan received her bachelor’s degree from Carleton College in 1981. She earned her medical degree from Washington University in 1986 and completed her postgraduate work and residency at the former Barnes Hospital, now Barnes-Jewish Hospital. Dr. Whelan is an internist and clinical geneticist.

Marc Triola, MD, is a professor of medicine, the associate dean for educational informatics, and the founding director of the Institute for Innovations in Medical Education (IIME) at NYU Grossman School of Medicine.  IIME combines education strategies with new informatics solutions to connect patient care and education at NYU Langone in a research and innovation initiative that is translational, empowers transformational change in our school, and benefits our patients. Dr. Triola’s research focuses on the use of AI tools to efficiently personalize education and give new insights to programs and coaches. His lab develops new learning technologies, AI-driven educational interventions, and defines educationally sensitive patient and system outcomes that can be used to assess training.