Ethical considerations in artificial intelligence
Abstract
With artificial intelligence (AI) precipitously perched at the apex of the hype curve, the promise of transforming the disparate fields of healthcare, finance, journalism, and security and law enforcement, among others, is enormous. For healthcare - particularly radiology - AI is anticipated to facilitate improved diagnostics, workflow, and therapeutic planning and monitoring. And, while it is also causing some trepidation among radiologists regarding its uncertain impact on the demand and training of our current and future workforce, most of us welcome the potential to harness AI for transformative improvements in our ability to diagnose disease more accurately and earlier in the populations we serve.
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HEIs make prominent contributions to AI governance as research efforts are critical in assessing impact, minimizing harm, and promoting well-being and social good.
“HEIs also make prominent contributions to the process as research efforts are critical in assessing the impact of intelligent applications, minimizing harm, and promoting well-being and social good [27].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [27]
It is difficult to assign liability for medical malpractice arising from defects in AI.
“Also, it is difficult to assign liability for medical malpractice arising from defects in AI 37,38.”
From Artificial intelligence in pancreatic cancer (2022) · cites this paper as [38]
Students who learn in an environment where ethical values are lived, not just stated, are more receptive to topics related to algorithmic responsibility and show a greater willingness to engage in reflections on the regulation of AI.
“Recent studies show that students who learn in an environment where ethical values are lived-not just stated-are more receptive to topics related to algorithmic responsibility and show a greater willingness to engage in reflections on the regulation of AI [43,48-50].”
Cites
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Langlotz, C. P., Allen, B., Erickson, B. J., Kalpathy-Cramer, J., Bigelow, K., Cook, T. S., Flanders, A. E., Lungren, M. P., Mendelson, D. S., Rudie, J. D., et al. (2019) · Radiology · doi:10.1148/radiol.2019190613 · Cited by 368 · see citing works
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Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility?
Naik, N., Hameed, B. M. Z., Shetty, D. K., Swain, D., Shah, M., Paul, R., Aggarwal, K., Ibrahim, S., Patil, V., Smriti, K., et al. (2022) · Frontiers in Surgery · doi:10.3389/fsurg.2022.862322 · Cited by 931 · see citing works
Artificial Intelligence in Low- and Middle-Income Countries: Innovating Global Health Radiology
Mollura, D. J., Culp, M. P., Pollack, E., Battino, G., Scheel, J. R., Mango, V. L., Elahi, A., Schweitzer, A., & Dako, F. (2020) · Radiology · doi:10.1148/radiol.2020201434 · Cited by 228 · see citing works
Prakash, S., Balaji, J. N., Joshi, A., & Surapaneni, K. M. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12111914 · Cited by 159 · see citing works
Artificial intelligence in pancreatic cancer
Huang, B., Huang, H., Zhang, S., Zhang, D., Shi, Q., Liu, J., & Guo, J. (2022) · Theranostics · doi:10.7150/thno.77949 · Cited by 142 · see citing works
“Also, it is difficult to assign liability for medical malpractice arising from defects in AI [37,38].”
BackgroundOnciul, R., Tataru, C.-I., Dumitru, A. V., Crivoi, C., Serban, M., Covache-Busuioc, R.-A., Radoi, M. P., & Toader, C. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14020550 · Cited by 113 · see citing works
AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities
Wu, C., Zhang, H., & Carroll, J. M. (2024) · Future Internet · doi:10.3390/fi16100354 · Cited by 99 · see citing works
“HEIs also make prominent contributions to the process as research efforts are critical in assessing the impact of intelligent applications, minimizing harm, and promoting well-being and social good (Safdar, Banja, and Meltzer 2020).”
Oncioiu, I., & Bularca, A. R. (2025) · Societies · doi:10.3390/soc15060144 · Cited by 64 · see citing works
Shobayo, O., & Saatchi, R. (2025) · Diagnostics · doi:10.3390/diagnostics15091072 · Cited by 53 · see citing works
Embracing the future of physician-patient communication: GPT-4 in gastroenterology
Nashwan, A. J., Abujaber, A. A., & Choudry, H. (2023) · Gastroenterology & Endoscopy · doi:10.1016/j.gande.2023.07.004 · Cited by 23 · see citing works
- Authors
- Safdar, N. M., Banja, J. D., & Meltzer, C. C.
- Affiliations
- Emory University (US)
- Corresponding author
- Meltzer, Carolyn C.
- Venue
- European Journal of Radiology
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 122
- Pages
- 108768
- ISSN
- 0720-048X (ISSN-L)
- OpenAlex
- W2991574913
- Cited by
- 243
- References
- 3
- Citations by year
- 2026: 24 · 2025: 47 · 2024: 77 · 2023: 36 · 2022: 32 · 2021: 15 · 2020: 12
- FWCI
- 4.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Radiology (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
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Keywords
- AI ethics, artificial intelligence in healthcare, radiology, diagnostic accuracy, early disease detection, radiologist workforce, artificial intelligence adoption
- MeSH terms
- Radiologists, Artificial Intelligence, Forecasting, Humans, Radiology, Workflow
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