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

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ChatGPT is a generative language model tool launched by Open-AI on November 20, 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 (Feb 13, 2023 version) 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 JMIR publisher Gunther Eysenbach, ChatGPT generates some ideas on how to use chatbots in medical education, and during the interview illustrates its' capabilities to generate a virtual patient simulation, generates quizzes for medical students, critiques a simulated doctor-patient communication, critiques research articles, comments on methods to detect machine-generated text to ensure academic integrity, generates a curriculum for health professionals to learn about AI, and helps with drafting a call for papers for a new theme issue to be launched in JMIR Medical Education on ChatGPT. The conversation also highlights the importance of proper "prompting". While the language generator does make occasional mistakes, it admits these when challenged. The interview provides a fascinating glimpse into the capabilities 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. We are soliciting papers that for example cover the following topics: 1) The potential of generative language models and AI for medical education, including their use in teaching and learning, clinical decision-making, and patient care, 2) The role of generative language models and AI in enhancing the quality of medical education, including the use of simulations, virtual patients, and other forms of digital learning resources. 3) Use of generative language models for automated essay grading and feedback in medical education 4) The development and evaluation of virtual patients generated by generative language models 5) Measuring the quality of information and simulations generated by generative language models, and strategies for improving the quality through proper prompting and other approaches. 6) Training medical students and healthcare professionals on AI and specifically on generative language models, including the development of curricula and instructional materials. 7) Ethical and legal issues related to the use of generative language models and AI in medical education, including issues related to data privacy, bias, and transparency. 8) Academic integrity issues and policies describing how medical schools allow or disallow use of generative language models. The initial call for papers was entirely machine-generated by ChatGPT, but will be edited by the human guest editors of the theme issue.