Artificial Intelligence in Medical Education Initiative

An STFM Artificial Intelligence in Medical Education Task Force, chaired by STFM President Steven Lin, MD, is working on the following tactics to advance responsible, outcome-driven, and people-centered artificial intelligence:

• Identify and act on opportunities for collaborative work around AI within STFM (e.g. the AI in Education Collaborative and other Collaboratives)
• Identify and act on opportunities to collaborate around AI with the larger family of family medicine organizations
• Forge new partnerships with other professional societies, health systems, industry, payers, and government around AI
• Identify and promote foundational AI use cases that help the family medicine workforce 
• Identify opportunities to develop datasets that catalyze family medicine R&D and attract industry
• Identify and promote opportunities to apply AI to support core values such as equity and community
• Support the work of family medicine AI pioneers, disseminate learnings, and promote the development of new centers of excellence 
• Provide members with opportunities to practice with exemplar AI-based tools that can be applied to a wide range of clinical, educational, and research settings\
• Address key limitations to the use of AI including unintended, harmful consequences
• Identify and promote opportunities for AI to personalize the learning journey for learners (“precision medical education”)
• Identify and promote opportunities for AI to lower the burden of education administration and curriculum development for faculty
• Identify and promote opportunities to elevate members to leadership roles in AI
• Identify or create new opportunities to incorporate AI content/training into existing STFM programs and offerings for medical students, residents, and faculty
• Explore the feasibility of an AI certificate program for STFM members
• Inspire and mobilize STFM members and more broadly, frontline primary care clinicians, scholars, educators, and learners around AI

STFM Artificial Intelligence in Medical Education Task Force

• Steven Lin, MD, Stanford University School of Medicine
• Rika Bajra, MD, Stanford University School of Medicine
• Ian Bennett MD, PhD, University of Washington School of Medicine
• Linda Chang, PharmD, MPH, BCPS, University of Illinois College of Medicine at Rockford
• John Hayes DO, MCW-Prevea Green Bay Family Medicine Residency Program
• Enitza George, MD, MBA, MSAI, SUNY Downstate Health Sciences University
• Karim Hanna, MD, USF TGH Family Medicine Residency Program
• Misbah Keen, MD, MBI, MPH, University of Washington School of Medicine
• Winston Liaw, MD, MPH, University of Houston
• May Lin, DO, Touro University
• Yun Shi, MD, PhD, UT Health San Antonio
• Margaret Ann Smith, Stanford School of Medicine
• Brent Sugimoto, MD, MPH, LifeLong Medical Care Family Medicine Residency Program
• Mary Theobald, MBA, Society of Teachers of Family Medicine
• Timothy Tsai, DO MMCi, Stanford University School of Medicine
• Steven Waldren, MD, MS, American Academy of Family Physicians
• Yun Liu, Google Research