Generative Artificial Intelligence: Implications for Biomedical and Health Professions Education

Abstract

Generative artificial intelligence (AI) has had a profound impact on biomedicine and health, both in professional work and in education. Based on large language models (LLMs), generative AI has been found to perform as well as humans in simulated situations taking medical board exams, answering clinical questions, solving clinical cases, applying clinical reasoning, and summarizing information. Generative AI is also being used widely in education, performing well in academic courses and their assessments. This review summarizes the successes of LLMs and highlights some of their challenges in the context of education, most notably aspects that may undermine the acquisition of knowledge and skills for professional work. It then provides recommendations for best practices to overcome the shortcomings of LLM use in education. Although there are challenges for the use of generative AI in education, all students and faculty, in biomedicine and health and beyond, must have understanding of it and be competent in its use.

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