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Ethical Governance of Artificial Intelligence in Clinical Medical Education: A Policy Framework for Developing and Implementing an Ethical Decision-Making Guideline
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Mahdieh Joukar   , Shadab Shahali * |
| , shadab.shahali@modares.ac.ir |
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Abstract: (12 Views) |
Introduction: The expansion of artificial intelligence in clinical medical education has introduced challenges regarding safety, equity, and ethics, alongside its educational opportunities. This policy brief was developed to outline the rationale, the formulation process, and a proposed policy option for an ethical decision-making framework concerning the use of artificial intelligence in clinical education.
Methods: The guideline was developed in three phases, based on the World Health Organization’s handbook for guideline development. It involved an integrated review (conducted in accordance with PRISMA 2020) with searches across PubMed, Scopus, and Web of Science databases covering the period from February 2015 to February 2026, expert consensus using the nominal group technique, and quality assessment via the AGREE II instrument. The structure of the policy brief follows four steps: defining the problem, articulating the policy, presenting arguments supported by evidence, and examining the implications.
Findings: Five ethical challenges were identified: output accuracy and hallucinations, impaired clinical judgment and overreliance, algorithmic bias and inequity, privacy and confidentiality, and academic integrity. The final guideline, comprising ten articles, defined 22 key terms, outlined general principles, distinguished between conditionally permitted and prohibited uses for students, educators, and institutions, and provided standardized disclosure instructions. Reviewers highly rated its clarity (%95.6) and scope (%92.7), with rigor and applicability also scoring well. Stakeholder involvement and editorial independence received moderate ratings. Three reviewers recommended the guideline with modifications, and one without changes.
Conclusion: The available evidence supports a risk-management framework and a context-sensitive approach to AI use. The proposed guideline should classify AI applications according to their intended purpose, data sensitivity, potential impact on educational and clinical decisions, and level of human oversight. Its effectiveness should also be evaluated following implementation.
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| Keywords: Artificial intelligence, clinical education, medical ethics, policy brief, ethical decision-making guideline |
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Type of Study: Research |
Subject:
Special
Received: 2026/Oct/Mon | Accepted: 2026/Nov/Mon | Published: 2025/Oct/Thu
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