JMIR Publications

ABSTRACT

This viewpoint article explores the ethical challenges facing the future application of large language models (LLMs) in medical education. These challenges encompass academic integrity, privacy and data risks, bias, educational unfairness, and the notable absence of transparency and interpretability. Moreover, it addresses issues related to responsibility and copyright. In addressing these ethical challenges, the author suggests drawing upon ethical guidelines from artificial intelligence applications in other domains. They propose the establishment of a globally unified ethical framework for the integration of LLMs into medical education. This framework is underpinned by eight fundamental principles: privacy and data protection, transparency and interpretability, fairness and equal treatment, academic integrity and moral norms, quality control and supervision mechanisms, accountability and traceability mechanisms, protection and respect for intellectual property rights, and fostering educational research and innovation. Through the implementation of a unified ethical framework, safeguarding individual rights and privacy, enhancing educational fairness, improving educational quality and safety, promoting academic integrity and ethical standards, and advancing educational research and innovation, the proposed guidelines aim to facilitate the reasonable and effective application of LLMs in medical education.