The Empirical Challenge of 21st-Century Medical Education
Abstract
Medical education is at a crossroads. Facing challenges wrought by science and technology as well as societal change, the curriculum is increasingly out of synch with new needs in teaching content and medical practice. The path to significant curricular reform is difficult because of a variety of factors, including deeply entrenched values, the natural resistance to change, and the accreditation process. Indeed, even the very definition of what it means to be a professional is changing with profound implications for the future role of the physician and the sacrosanct doctor–patient relationship. In this Invited Commentary, the author enumerates challenges facing medical education in the current era. To address these challenges, the author recommends specific curricular emphases for 21st-century medical education: knowledge capture and curation, collaboration with and management of artificial intelligence applications, a deep understanding of probabilistic reasoning, and the cultivation of empathy and compassion in accordance with ethical standards. Given these needs, it is imperative that schools act today to undertake significant curricular reform and, in so doing, strive to make the hard changes necessary to produce optimal practitioners in a rapidly transforming 21st century. The author provides first steps an institution can take to begin to address these challenges.
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Gaps in medical faculty knowledge of AI may be inhibiting learners who have an active interest in AI applications but lack exposure to knowledgeable faculty to help them understand, access, and apply AI.
“these gaps may be inhibiting learners who have an active interest in AI applications but lack exposure to knowledgeable faculty to help them understand, access, and apply them.42,56”
From Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes (2021) · cites this paper as [42]
The exposure of gaps in medical faculty knowledge of AI is likely to conclude that there is a need to restructure faculty positions to bridge those gaps.
“The exposure of gaps in medical faculty knowledge of AI is in the process of research but is likely to conclude that there is a need to restructure faculty positions to bridge these gaps;”
From Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes (2021) · cites this paper as [42]
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Artificial Intelligence in Undergraduate Medical Education: A Scoping Review
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“The exposure of gaps in medical faculty knowledge of AI is in the process of research but is likely to conclude that there is a need to restructure faculty positions to bridge these gaps; these gaps may be inhibiting learners who have an active interest in AI applications but lack exposure to knowledgeable faculty to…”
BackgroundNeeds, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum
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Envisioning Graduate Medical Education in 2030
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- Authors
- Wartman, S. A.
- Affiliations
- Association of Academic Health Centers (US)
- Corresponding author
- Wartman, Steven A.
- Venue
- Academic Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-10
- Volume
- 94
- Issue
- 10
- Pages
- 1412-1415
- ISSN
- 1040-2446 (ISSN-L)
- OpenAlex
- W2962544139
- Cited by
- 82
- References
- 5
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 11 · 2023: 15 · 2022: 13 · 2021: 19 · 2020: 5 · 2019: 2
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academic Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Health Sciences › Health Professions › General Health Professions › Health and Medical Education
- Health Sciences › Medicine › Psychiatry and Mental health › Empathy and Medical Education
- Keywords
- medical education, curriculum reform, artificial intelligence in healthcare, probabilistic reasoning, empathy and compassion, physician-patient relationship, professional identity, medical accreditation, knowledge curation, medical ethics
- MeSH terms
- Clinical Decision-Making, Accreditation, Artificial Intelligence, Curriculum, Education, Medical, Empathy, Humans, Physician-Patient Relations, Probability, Knowledge
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