Marathon Without a Finish Line: A Learner’s Perspective on AI in Medical Education

Artificial intelligence (AI) is rapidly evolving and increasingly being integrated into health care. Medical students and residents must develop a foundational understanding of AI's applications and implications for their education and training, professional practice, and the health of their patients. In this commentary, the author, a current MD/PhD student, calls for the inclusion of AI in educational programming and suggests approaches to 5 inherent tensions in efforts to develop AI curricula. Curricula should not fixate on any one tool or technology; however, a core AI curriculum should provide all students and residents with the needed AI literacy and skills, enabling graduates to engage with, question, and responsibly use AI tools in their clinical practice. Learners also should be offered opportunities that prepare them for a variety of roles ranging from users to developers of AI models. Institutional differences in AI resources and expertise pose a challenge, underscoring the importance of unifying national modules and coproduction of curriculum with interested learners who have AI experience. Finally, all AI curricula must promote among developers and users an awareness of ethical principles when contextualizing and evaluating AI models.

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Publication Details

Journal
Academic Medicine
Published
2025-05-30
DOI
https://doi.org/10.1097/acm.0000000000006100
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
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article

Marathon Without a Finish Line: A Learner’s Perspective on AI in Medical Education

Joy Jiang
1 citations
Academic Medicine
Artificial Intelligence in Healthcare and Education
0.65
article

Marathon Without a Finish Line: A Learner’s Perspective on AI in Medical Education

Joy Jiang
article en
1 citations

Abstract

Artificial intelligence (AI) is rapidly evolving and increasingly being integrated into health care. Medical students and residents must develop a foundational understanding of AI's applications and implications for their education and training, professional practice, and the health of their patients. In this commentary, the author, a current MD/PhD student, calls for the inclusion of AI in educational programming and suggests approaches to 5 inherent tensions in efforts to develop AI curricula. Curricula should not fixate on any one tool or technology; however, a core AI curriculum should provide all students and residents with the needed AI literacy and skills, enabling graduates to engage with, question, and responsibly use AI tools in their clinical practice. Learners also should be offered opportunities that prepare them for a variety of roles ranging from users to developers of AI models. Institutional differences in AI resources and expertise pose a challenge, underscoring the importance of unifying national modules and coproduction of curriculum with interested learners who have AI experience. Finally, all AI curricula must promote among developers and users an awareness of ethical principles when contextualizing and evaluating AI models.

Academic MedicineVol. 100(9S)
Levy Economics Institute of Bard College (US), Icahn School of Medicine at Mount Sinai (US)
Quality Education
Openalex Percentile: Top 25%
Artificial Intelligence in Healthcare and Education
0.65
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