Harnessing the Promise of Artificial Intelligence Responsibly
Abstract
This Viewpoint discusses the benefits and potential harms of using artificial intelligence (AI) algorithms in medicine and proposes the collaborative creation of a Code of Conduct for AI in Health Care.
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Understanding AI requires training, especially its impact on care management decisions, patient outcomes discussions, and ethical decision-making.
“Understanding AI requires training, especially its impact on care management decisions, patient outcomes discussions, and ethical decision-making [2,39,40].”
From Reimagining Core Entrustable Professional Activities for Undergraduate Medical Education in the Era of Artificial Intelligence (2023) · cites this paper as [40]
Cites
Medical deep learning—A systematic meta-review
Egger, J., Gsaxner, C., Pepe, A., Pomykala, K. L., Jonske, F., Kurz, M., Li, J., & Kleesiek, J. (2022) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2022.106874 · Cited by 270 · see citing works
Embi, P. J. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.4622 · Cited by 99 · see citing works
Algorithmic Stewardship in Health Care—Reply
Eaneff, S., Obermeyer, Z., & Butte, A. J. (2021) · JAMA · doi:10.1001/jama.2020.24103 · Cited by 2 · see citing works
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Sorted by citations
Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge
Kanjee, Z., Crowe, B., & Rodman, A. (2023) · JAMA · doi:10.1001/jama.2023.8288 · Cited by 449 · see citing works
Automation Bias and Assistive AI: Risk of Harm From AI-Driven Clinical Decision Support
Khera, R., Simon, M. A., & Ross, J. S. (2023) · JAMA · doi:10.1001/jama.2023.22557 · Cited by 222 · see citing works
Alkhaaldi, S. M. I., Kassab, C. H., Dimassi, Z., Oyoun Alsoud, L., Al Fahim, M., Al Hageh, C., & Ibrahim, H. (2023) · JMIR Medical Education · doi:10.2196/51302 · Cited by 132 · see citing works
AI in Medicine—<i>JAMA</i>’s Focus on Clinical Outcomes, Patient-Centered Care, Quality, and Equity
Khera, R., Butte, A. J., Berkwits, M., Hswen, Y., Flanagin, A., Park, H., Curfman, G., & Bibbins-Domingo, K. (2023) · JAMA · doi:10.1001/jama.2023.15481 · Cited by 78 · see citing works
Jacobs, S. M., Lundy, N. N., Issenberg, S. B., & Chandran, L. (2023) · JMIR Medical Education · doi:10.2196/50903 · Cited by 33 · see citing works
- Authors
- Dorr, D. A., Adams, L., & Embí, P.
- Affiliations
- Oregon Health & Science University (US)
- National Academy of Medicine (US)
- Vanderbilt University Medical Center (US)
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2023-04-25
- Volume
- 329
- Issue
- 16
- Pages
- 1347
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W4361000305
- Cited by
- 49
- References
- 3
- Citations by year
- 2026: 1 · 2025: 15 · 2024: 14 · 2023: 19
- FWCI
- 1.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- artificial intelligence in healthcare, artificial intelligence algorithms, codes of conduct, responsible AI, AI harms, AI ethics, health care
- MeSH terms
- Algorithms, Artificial Intelligence, Social Control, Formal
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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