Clinical Report: Addressing the Gap in AI Instruction within Internal Medicine Clerkships

Overview

A survey of internal medicine clerkship directors reveals a significant gap in AI education, with no structured teaching on AI reported. This highlights a need for educational frameworks to integrate AI literacy into medical training.

Background

The integration of artificial intelligence (AI) into healthcare is rapidly evolving, impacting clinical practice and medical education. Despite the increasing use of AI tools by medical students, there is a lack of formal instruction on AI in medical school curricula.

Data Highlights

No structured teaching on AI was reported by any of the 114 internal medicine clerkship directors surveyed.

Key Findings

• 84% of faculty and 75% of clerkship directors reported insufficient knowledge about AI as a barrier to teaching.
• Over 40% of medical students use generative AI tools weekly.
• Nearly half of clerkship directors reported no AI training at all.
• One-in-five clerkship directors felt incorporating AI into the curriculum was unimportant.

Clinical Implications

Educators need to develop basic AI literacy to guide medical students in using AI tools.

Conclusion

The findings indicate a need for structured AI education in medical training.

Related Resources & Content

1. Kumar et al., Journal of General Internal Medicine, 2024 -- Addressing the Gap in AI Instruction within Internal Medicine Clerkships
2. Frontiers in Medicine — Integrating AI into undergraduate medical education: an exploration of learner-centered approaches through AI
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6. Integrating AI into undergraduate medical education: an exploration of learner-centered approaches through AI
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8. Preparing Tomorrow's Physicians for AI-Driven Healthcare: Insights from a Study on Medical Students', Interns', and Residents' Knowledge, Attitudes, and Educational Needs
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