Perceptions and Use of Generative Artificial Intelligence in Medical Students: A Multicenter Survey

Abstract

Introduction: Generative artificial intelligence (AI) has transformative potential in medical training, and its role in medicine holds drastic implications for patients, healthcare providers, and society; however, its current use by medical students is unknown. The study aims to characterize the use, frequency of use, and perceptions of generative AI by Canadian medical students. Methods: A cross-sectional survey was distributed to 6 medical schools in Ontario, Canada, to investigate how medical students use generative AI in education, clinical settings, and for communication, and to assess the perceived barriers and enablers that influence their use. Results: A total of 167 respondents completed the survey (60.8% female, 69.3% in first and second year), and over 78.9% of respondents reported using generative AI, with ChatGPT being the most popular model; 53.0% of respondents were frequent users and reported using generative AI tools at least once a week. In clinical settings, students report using generative AI for learning and reviewing medical content, summarizing clinical guidelines, and generating differential diagnoses; 92.8% of students were willing to learn how to use generative AI to integrate it into their future clinical practice. At the same time, most medical students appreciated the limitations of generative AI in terms of its risk for inaccuracy (91.6%) and bias (78.9%); 75.9% of participants agreed that generative AI should be implemented as a resource or formal teaching topic in medical training. Discussion: The findings of this study may help guide medical education institutions in adapting curricula and developing policies to promote the ethical and appropriate use of generative AI in medicine.

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