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Integrating AI Scribes into Medical Education: Guardrails for Preserving Clinical Reasoning
Jane Abernethy1, Anna Shah2, Belinda Chen3
1Johns Hopkins Bayview Medical Center, Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jaberne1@jhmi.edu.
Abstract:
Clinical documentation is a cornerstone of physician training, not only as a record of care but as a catalyst for clinical reasoning. For medical trainees, writing notes compels them to prioritize information, justify decisions, and synthesize fragmented data into coherent narratives. With the emergence of artificial intelligence (AI) scribes that auto-generate clinical notes from ambient audio, the task of composing notes is increasingly outsourced, raising questions about its impact on education. At our internal medicine residency program, we piloted a 6-month implementation of an AI scribe tool with 48 residents, generating nearly 1000 notes. We propose seven best practices-mapped to the Accreditation Council for Graduate Medical Education (ACGME) Core Competencies-with the goal that AI scribes support, rather than erode, the development of reflective practice and diagnostic thinking. These include establishing baseline documentation skills, structured AI training, critical review of AI-generated notes, and new opportunities for feedback. In this formative moment, educators must guide learners to use AI as a scaffold for reasoning, not a substitute for it.
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