The Role of ChatGPT, Generative Language Models, and Artificial Intelligence in Medical Education: A Conversation With ChatGPT and a Call for Papers

By Gunther Eysenbach. JMIR Medical Education, 2023

725 citations recorded by the source corpus.

ChatGPT is a generative language model tool launched by OpenAI on November 30, 2022, enabling the public to converse with a machine on a broad range of topics. In January 2023, ChatGPT reached over 100 million users, making it the fastest-growing consumer application to date. This interview with ChatGPT is part 2 of a larger interview with ChatGPT. It provides a snapshot of the current capabilities of ChatGPT and illustrates the vast potential for medical education, research, and practice but also hints at current problems and limitations. In this conversation with Gunther Eysenbach, the founder and publisher of JMIR Publications, ChatGPT generated some ideas on how to use chatbots in medical education. It also illustrated its capabilities to generate a virtual patient simulation and quizzes for medical students; critiqued a simulated doctor-patient communication and attempts to summarize a research article (which turned out to be fabricated); commented on methods to detect machine-generated text to ensure academic integrity; generated a curriculum for health professionals to learn about artificial intelligence (AI); and helped to draft a call for papers for a new theme issue to be launched in JMIR Medical Education on ChatGPT. The conversation also highlighted the importance of proper “prompting.” Although the language generator does make occasional mistakes, it admits these when challenged. The well-known disturbing tendency of large language models to hallucinate became evident when ChatGPT fabricated references. The interview provides a glimpse into the capabilities and limitations of ChatGPT and the future of AI-supported medical education. Due to the impact of this new technology on medical education, JMIR Medical Education is launching a call for papers for a new e-collection and theme issue. The initial draft of the call for papers was entirely machine generated by ChatGPT, but will be edited by the human guest editors of the theme issue.

Subfields: General Health Professions, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/8cf01c76b506f6bca5258071ed309fc4430c24d3

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In General Health Professions

In Health Informatics

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Generative artificial intelligence (2023, background): “In January 2023, ChatGPT reached over 100 million users, making it the fastest-growing consumer application to date (Eysenbach, 2023).”
Generative AI in healthcare: an implementation science informed translational path on application, integration and governance (2024, background): “These cases can be based on a diverse range of medical conditions, patient demographics and clinical scenarios, providing a comprehensive learning platform for medical students and healthcare professionals [51, 52].”
Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions (2023, background): “LLMs have the potential to significantly impact all phases of medical education programs, offering numerous benefits in various aspects, including curriculum planning, delivery, assessments, programmatic enhancements, and research [8-30].”
Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review (2023, background): “[1] Creation of learning materials “By serving as a virtual teaching assistant, ChatGPT could be leveraged to provide students with real-time and personalized feedback.””
Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health (2023, background): “For example, the author in [109], engages in a dialog with a chatbot, asking it to simulate a patient with undiagnosed diabetes and the common labs that may need to be run.”
The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions (2023, neutral): “133 Companies appear to have a limited understanding of how to systematize the deployment of generative AI with most workplace applications appearing to be motivated by the individual employees.”
Fabrication and errors in the bibliographic citations generated by ChatGPT (2023, background): “Several authors have noted that ChatGPT tends to cite works that do not actually exist 12,16–25 , and 6 studies have systematically investigated the extent of the problem 13,15,26–29 .”
ChatGPT in Healthcare: A Taxonomy and Systematic Review (2023, background): “The decision is echoed by the academic community [58, 97, 115, 66], agreeing that ChatGPT-generated content must be scrutinized by human experts before being used [58], as the generated content, such as references [105, 12, 40, 31] could be fabricated.”