To highlight the lack of structured AI education in internal medicine clerkships and propose a framework for integrating AI literacy into medical training, emphasizing the need for structured education.
Approach:
Survey Analysis: A nationally representative survey of 114 internal medicine clerkship directors was conducted to assess the state of AI education in clerkships.
Competency-Based Framework: Proposes applying a competency-based medical education (CBME) framework to define AI literacy for educators and develop durable AI skills.
Key Findings:
Despite recognizing the importance of AI, no clerkship reported structured teaching on AI use in their curriculum.
Over 40% of medical students use generative AI weekly, with nearly half preferring ChatGPT over attending physicians.
Barriers to teaching AI include faculty knowledge gaps, with 84% of faculty and 75% of clerkship directors lacking adequate training.
Interpretation:
Current educational frameworks must adapt to include AI competencies.
Limitations:
The survey reflects a snapshot in time and may not capture the rapidly evolving landscape of AI in medical education.
Responses may not represent all medical schools or clerkships across the country, and the survey had an 80% response rate.
Conclusion:
Defining basic AI literacy and integrating it into clerkship curricula is necessary to prepare future physicians for AI-augmented clinical practice.
