AI in Medical Education and Simulation

AI may appear in medical education as a writing assistant, tutor, simulated patient, feedback tool, or content generator. The Association of American Medical Colleges (AAMC) offers principles for responsible AI use in medical education, including transparency, privacy, and preparing learners to communicate technology use to patients. These principles support institutional planning; they do not certify a particular educational product or prove that a simulation improves clinical competence. AI-generated cases can contain incorrect dosing, unrealistic symptoms, or biased patient portrayals. Virtual patients may produce answers that change unpredictably, and automated feedback may reward a narrow communication style. Faculty should review materials before use, establish learning goals, and ensure learners receive supervision and debriefing. Simulation complements clinical training but cannot reproduce all aspects of patient care or replace real patient relationships. Schools should set clear rules for permitted AI use in assignments, assessment, and clinical practice. Protect student and patient data, disclose when AI is used, and teach learners how to verify information. Use accessible scenarios that represent diverse patients and avoid stigmatizing content. Collect feedback from learners and faculty, evaluate outcomes, and revise tools or activities when they do not support the curriculum. Faculty should check that cases reflect current practice, that the simulated patient’s response is appropriate, and that learners receive a structured debrief. Do not use AI-generated performance ratings for high-stakes progression decisions without evidence of validity and due process.