Skip to main navigation Skip to search Skip to main content

Harnessing the potential of large language models in medical education: promise and pitfalls

  • Trista M. Benítez
  • , Yueyuan Xu
  • , J. Donald Boudreau
  • , Alfred Wei Chieh Kow
  • , Fernando Bello
  • , Le Van Phuoc
  • , Xiaofei Wang
  • , Xiaodong Sun
  • , Gilberto Ka Kit Leung
  • , Yanyan Lan
  • , Yaxing Wang
  • , Davy Cheng
  • , Yih Chung Tham*
  • , Tien Yin Wong
  • , Kevin C. Chung*
  • *Corresponding author for this work
  • University of Michigan, Ann Arbor
  • Tsinghua University
  • McGill University
  • National University of Singapore
  • Duke-NUS Medical School
  • VinUniversity
  • Shanghai Jiao Tong University
  • The University of Hong Kong
  • Capital Medical University
  • The Chinese University of Hong Kong, Shenzhen
  • Singapore National Eye Center
  • Beijing Tsinghua Chang Gung Hospital

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum. Process: Narrative review of published literature contextualized by current reports of LLM application in medical education. Conclusions: LLMs like OpenAI's ChatGPT can potentially revolutionize traditional teaching methodologies. LLMs offer several potential advantages to students, including direct access to vast information, facilitation of personalized learning experiences, and enhancement of clinical skills development. For faculty and instructors, LLMs can facilitate innovative approaches to teaching complex medical concepts and fostering student engagement. Notable challenges of LLMs integration include the risk of fostering academic misconduct, inadvertent overreliance on AI, potential dilution of critical thinking skills, concerns regarding the accuracy and reliability of LLM-generated content, and the possible implications on teaching staff.

Original languageEnglish
Pages (from-to)776-783
Number of pages8
JournalJournal of the American Medical Informatics Association
Volume31
Issue number3
DOIs
StatePublished - 1 Mar 2024

Keywords

  • ChatGPT
  • large language models
  • medical education

Fingerprint

Dive into the research topics of 'Harnessing the potential of large language models in medical education: promise and pitfalls'. Together they form a unique fingerprint.

Cite this