The rapid integration of artificial intelligence (AI) into medical education offers unprecedented potential for knowledge consolidation, yet it introduces significant risks regarding cognitive over-reliance. This letter argues that to safeguard future clinical reasoning, medical schools must shift from passive tool adoption to a pedagogical framework that prioritizes critical appraisal, verification, and the supervised use of AI, ensuring graduates retain independent diagnostic judgment while leveraging technological advancements.
saeidi,M . (2026). The Challenges of AI Dependency in Medical Education: From Facilitating Learning to Undermining Clinical Judgment. (e246198). Medical Education Bulletin, (), e246198 doi: 10.22034/meb.2026.588440.1132
MLA
saeidi,M . "The Challenges of AI Dependency in Medical Education: From Facilitating Learning to Undermining Clinical Judgment" .e246198 , Medical Education Bulletin, , , 2026, e246198. doi: 10.22034/meb.2026.588440.1132
HARVARD
saeidi M. (2026). 'The Challenges of AI Dependency in Medical Education: From Facilitating Learning to Undermining Clinical Judgment', Medical Education Bulletin, (), e246198. doi: 10.22034/meb.2026.588440.1132
CHICAGO
M saeidi, "The Challenges of AI Dependency in Medical Education: From Facilitating Learning to Undermining Clinical Judgment," Medical Education Bulletin, (2026): e246198, doi: 10.22034/meb.2026.588440.1132
VANCOUVER
saeidi M. The Challenges of AI Dependency in Medical Education: From Facilitating Learning to Undermining Clinical Judgment. MEB. 2026;():e246198. doi: 10.22034/meb.2026.588440.1132
