AI in GME education

Artificial intelligence (AI) is rapidly being integrated across the landscape of graduate medical education (GME) with applications spanning the residency application and selection process, clinical training and post graduate practice. This paper reviews the history of AI in GME and its current integration across the GME continuum, highlighting its benefits, limitations and challenges. AI enhances training through improved efficiency, personalized education, reduced clerical burden, workflow optimization, and diagnostic support. However, significant concerns persist, including bias in algorithmic decision-making, threats to authenticity in application materials, erosion of clinical reasoning skills with overreliance on AI, and unclear accountability for its use in clinical care. To address these challenges, we propose the establishment of a multidisciplinary committee to standardize AI use, promote ethical implementation, improve AI literacy, reduce bias, and ensure equitable outcomes.