Wolfgang Miesbach: The Risk of Deskilling in Modern AI Assisted Medicine
Wolfgang Miesbach, Professor of Medicine at Frankfurt University Hospital, shared a post on LinkedIn about a recent article by Yuhe Ke et al., published in Nature Medicine, adding։
“Loosing your skills by AI?
This Perspective in Nature Medicine shows how AI can undermine clinical competence: students risk ‘never‑skilling’ (they never build independent diagnostic schemas), while experienced clinicians risk deskilling and mis‑skilling (eroding existing skills or internalising AI errors as ‘truth’).
The problem is not AI itself, but overuse of ‘answer‑delivery mode’ that bypasses the hard cognitive work needed for robust reasoning, calibration and metacognitive judgment.
The authors propose a 3‑step approach:
- AI‑free reasoning zones (history, exam, DDx, management) for trainees andperiodic “AI‑off” drills for seniors,
- guided learning‑mode AI with Socratic questioning and built‑in errors to train verification/override ,
- integrated human-AI collaboration where clinicians contribute context, values and responsibility instead of just relaying outputs .
The question for education, leadership and regulators: how do we ensure that, in an AI‑rich world, every clinician can still fly manually when the ‘autopilot’ fails?”
Title: AI-induced never-skilling in medical education
Authors: Yuhe Ke, Liyuan Jin, Jasmine Chiat Ling Ong, Arun J. Thirunavukarasu, Josip Car, Carol Y. Cheung, Yih Chung Tham, Daniel Shu Wei Ting, Marcus Eng Hock Ong, Scott Compton, Aditee Narayan, Pearse A. Keane, Tien Yin Wong, David W. Bates, Patrick Tan, Nan Liu
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