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AI in Medical Education: Opportunities, challenges ...
Session Recording: AI in Medical Education
Session Recording: AI in Medical Education
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Video Summary
This session explored the rapidly expanding role of artificial intelligence in medical education, especially in endocrinology training. Moderated by Dr. Julie Chen, the panel included Drs. Ruchi Gawba, Andrew Crawford, and Alistair Thompson, who shared perspectives on AI’s promise and risks.<br /><br />Panelists agreed AI can reduce administrative burden, personalize learning, improve curriculum design, and support literature review, feedback, and board preparation. However, they emphasized that AI must be used thoughtfully because of concerns about accuracy, hallucinated references, privacy, bias, and the risk of “de-skilling” or “mis-skilling” trainees who rely on it too heavily.<br /><br />A major theme was the need for clear AI policies in training programs. Dr. Gawba outlined four key principles: transparency, accountability, data privacy/security, and educational integrity. The panel favored a layered approach to policy development involving institutions, GME leadership, professional societies, and accrediting bodies.<br /><br />Live demonstrations showed practical uses of AI tools like Gemini and NotebookLM for building curricula and journal club materials. The panel stressed that AI should support, not replace, critical thinking and learner engagement. The session closed with discussion of future use in board review and undergraduate medical education.
Keywords
artificial intelligence
medical education
endocrinology training
graduate medical education
AI ethics
faculty training
clinical accuracy
educational technology
AI policy
data privacy
curriculum design
board preparation
critical thinking
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