Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum
JMIR Medical Education, 2022
Joel Grunhut, Oge Marques, Adam T M Wyatt
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In brief
Physicians will increasingly make decisions alongside AI predictions, but medical schools largely do not teach AI. We explain why, and propose integrating AI as a longitudinal thread across the existing curriculum, covering AI tools, how clinical AI is designed, the role of data, and ethics.
Key findings
Barriers to AI in medical school curricula include a lack of faculty expertise, limited evidence, and no Liaison Committee on Medical Education (LCME) guidance on AI.
We recommend teaching AI as a longitudinal thread within existing subjects rather than as a standalone course.
Curriculum case studies should include AI recommendations that pose critical decision-making challenges, with ethics at the forefront.
Abstract
Artificial intelligence (AI) is on course to become a mainstay in the patient's room, physician's office, and the surgical suite. Current advancements in health care technology might put future physicians in an insufficiently equipped position to deal with the advancements and challenges brought about by AI and machine learning solutions. Physicians will be tasked regularly with clinical decision-making with the assistance of AI-driven predictions. Present-day physicians are not trained to incorporate the suggestions of such predictions on a regular basis nor are they knowledgeable in an ethical approach to incorporating AI in their practice and evolving standards of care. Medical schools do not currently incorporate AI in their curriculum due to several factors, including the lack of faculty expertise, the lack of evidence to support the growing desire by students to learn about AI, or the lack of Liaison Committee on Medical Education's guidance on AI in medical education. Medical schools should incorporate AI in the curriculum as a longitudinal thread in current subjects. Current students should understand the breadth of AI tools, the framework of engineering and designing AI solutions to clinical issues, and the role of data in the development of AI innovations. Study cases in the curriculum should include an AI recommendation that may present critical decision-making challenges. Finally, the ethical implications of AI in medicine must be at the forefront of any comprehensive medical education.
How to cite
Grunhut J, Marques O, Wyatt ATM. Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum. JMIR Med Educ. 2022;8(2):e35587. doi:10.2196/35587