Ethics and standards in the use of artificial intelligence in medicine on behalf of the Royal Australian and New Zealand College of Radiologists
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Introduction: The Royal Australian and New Zealand College of Radiologists (RANZCR) led the medical community in Australia and New Zealand in considering the impact of machine learning and artificial intelligence (AI) in health care. RANZCR identified that medical leadership was largely absent from these discussions, with a notable absence of activity from governments in the Australasian region up to 2019. The clinical radiology and radiation oncology sectors were considered ripe for the adoption of AI, and this raised a range of concerns about how to ensure the ethical application of AI and to guide its safe and appropriate use in our two specialties. Methods: RANZCR’s Artificial Intelligence Committee undertook a landscape review in 2019 anddetermined that AI within clinical radiology and radiation oncology had the potential to grow rapidly and significantly impact the professions. In order to address this, RANZCR drafted ethical principles on the use of AI and standards to guide deployment and engaged in extensive stakeholder consultation to ensure a range of perspectives were received and considered. Results: RANZCR published two key bodies of work: The Ethical Principles of Artificial Intelligence in Medicine, and the Standards of Practice for Artificial Intelligence in Clinical Radiology. Conclusion: RANZCR’s publications in this area have established a solid foundation to prepare for the application of AI, however more work is needed. We will continue to assess the evolution of AI and ML within our professions, strive to guide the upskilling of clinical radiologists and radiation oncologists, advocate for appropriate regulation and produce guidance to ensure that patient care is delivered safely.
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The approach of forming an ethics committee or engaging existing institutional review boards contributes to the establishment of ethical best practices, promoting responsible and accountable use of AI in medical education.
“This approach not only safeguards against potential ethical pitfalls but also contributes to the establishment of ethical best practices, promoting responsible and accountable use of AI in medical education [61].”
From Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education (2024) · cites this paper as [61]
The approach of forming an ethics committee or engaging existing institutional review boards safeguards against potential ethical pitfalls.
“This approach not only safeguards against potential ethical pitfalls but also contributes to the establishment of ethical best practices, promoting responsible and accountable use of AI in medical education [61].”
From Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education (2024) · cites this paper as [61]
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Ethics Guidelines for Trustworthy AI
Cannarsa, M. (2021) · The Cambridge Handbook of Lawyering in the Digital Age · doi:10.1017/9781108936040.022 · Cited by 2,095 · see citing works
The Price of Artificial Intelligence
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- [4]The European AI Landscape Workshop Report. [Cited 3 March 2021.] Available from URL: https://ec.europa.eu/jrc/communities/sites/jrccties/files/reportontheeuropeanailandscapeworkshop.pdf
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Palaniappan, K., Lin, E. Y. T., & Vogel, S. (2024) · Healthcare · doi:10.3390/healthcare12050562 · Cited by 301 · see citing works
Franco D’Souza, R., Mathew, M., Mishra, V., & Surapaneni, K. M. (2024) · Medical Education Online · doi:10.1080/10872981.2024.2330250 · Cited by 147 · see citing works
- Authors
- Kenny, L. M., Nevin, M., & Fitzpatrick, K.
- Affiliations
- Royal Brisbane and Women’s Hospital Herston Queensland Australia
- Royal Australian and New Zealand College of Radiologists (AU)
- Corresponding author
- Fitzpatrick, Kirsten
- Venue
- Journal of Medical Imaging and Radiation Oncology
- Publisher
- Wiley
- Published
- 2021-08
- Volume
- 65
- Issue
- 5
- Pages
- 486-494
- ISSN
- 1754-9477 (ISSN-L)
- 1754-9485
- PMC
- PMC9291743
- OpenAlex
- W3191796941
- Cited by
- 41
- References
- 3
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 18 · 2023: 3 · 2022: 4 · 2021: 1
- FWCI
- 1.89
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Medical Imaging and Radiation Oncology (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- 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 › Artificial Intelligence Applications
- Keywords
- artificial intelligence in healthcare, machine learning, clinical radiology, radiation oncology, AI ethics, ethical principles, standards of practice, professional guidelines, AI regulation, stakeholder consultation
- MeSH terms
- Radiologists, Artificial Intelligence, Australia, Humans, New Zealand, Radiology
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