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<p>Generative artificial intelligence (GenAI) and large language models represent gains in educational efficiency and personalisation of learning. These are balanced against the considerations of the learning process, authentic assessment, and academic integrity. A pedagogical approach helps situate these concerns, and informs various types of governance and regulatory approaches. In this review we identify current and emerging issues regarding GenAI in medical education including pedagogical considerations, emerging roles, and trustworthiness. Potential measures to address specific regulatory concerns are explored.</p>

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Situating governance and regulatory concerns for generative artificial intelligence and large language models in medical education

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月27日

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  • Michael Tran,
  • Chinthaka Balasooriya,
  • Jitendra Jonnagaddala,
  • Gilberto Ka-Kit Leung,
  • Neeraj Mahboobani,
  • Subha Ramani,
  • Joel Rhee,
  • Lambert Schuwirth,
  • Neysan Sedaghat Najafzadeh-Tabrizi,
  • Carolyn Semmler,
  • Zoie SY Wong

摘要

Generative artificial intelligence (GenAI) and large language models represent gains in educational efficiency and personalisation of learning. These are balanced against the considerations of the learning process, authentic assessment, and academic integrity. A pedagogical approach helps situate these concerns, and informs various types of governance and regulatory approaches. In this review we identify current and emerging issues regarding GenAI in medical education including pedagogical considerations, emerging roles, and trustworthiness. Potential measures to address specific regulatory concerns are explored.