Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

J. Raymond Geis; Adrian P. Brady; Carol C. Wu; Jack Spencer; Erik Ranschaert; Jacob L. Jaremko; Steve G. Langer; Andrea Borondy Kitts; Judy Birch; William F. Shields; Robert van den Hoven van Genderen; Elmar Kotter; Judy Wawira Gichoya; Tessa S. Cook; Matthew B. Morgan; An Tang; Nabile M. Safdar; Marc Kohli

doi:10.1016/j.jacr.2019.07.028

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

J. Raymond Geis^*, Adrian P. Brady, Carol C. Wu, Jack Spencer, Erik Ranschaert, Jacob L. Jaremko, Steve G. Langer, Andrea Borondy Kitts, Judy Birch, William F. Shields, Robert van den Hoven van Genderen, Elmar Kotter, Judy Wawira Gichoya, Tessa S. Cook, Matthew B. Morgan, An Tang, Nabile M. Safdar, Marc Kohli

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists, and American Association of Physicists in Medicine. AI has great potential to increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and biases. Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues. Currently, there is little experience using AI for patient care in diverse clinical settings. Extensive research is needed to understand how to best deploy AI in clinical practice. This statement highlights our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders in a just manner. We believe AI should respect human rights and freedoms, including dignity and privacy. It should be designed for maximum transparency and dependability. Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future. The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes.

Original language	English
Pages (from-to)	1516-1521
Number of pages	6
Journal	Journal of the American College of Radiology
Volume	16
Issue number	11
Early online date	1 Oct 2019
DOIs	https://doi.org/10.1016/j.jacr.2019.07.028
Publication status	Published - Nov 2019

Funding

Dr. Jaremko reports support from MEDO Dx PTE Ltd, outside the submitted work; Andrea Borondy Kitts MS, MPH is COO and investor, Prosumer Heath, Associate Editor JACR, paid faculty 2019 Medtronic Global Lung Health Summit. Dr. Morgan reports personal fees from Elsevier, outside the submitted work. Dr. Tang reports support from Fonds de Recherche du Québec en Santé and Fondation de l'association des radiologistes du Québec (FRQS-ARQ 34939), during the conduct of the study. Dr Kohli reports non-financial support from Society of Imaging Informatics in Medicine, during the conduct of the study; non-financial support from Radiological Society of North America, outside the submitted work. The other authors state that they have no conflict of interest related to the material discussed in this article.

Funders	Funder number
Society for Imaging Informatics in Medicine
Radiological Society of North America
Fonds de Recherche du Québec - Santé	34939
Fondation de l'Association des radiologistes du Québec

Keywords

Artificial intelligence
data
ethics
machine learning
radiology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Geis, J. R., Brady, A. P., Wu, C. C., Spencer, J., Ranschaert, E., Jaremko, J. L., Langer, S. G., Kitts, A. B., Birch, J., Shields, W. F., van den Hoven van Genderen, R., Kotter, E., Gichoya, J. W., Cook, T. S., Morgan, M. B., Tang, A., Safdar, N. M., & Kohli, M. (2019). Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. Journal of the American College of Radiology, 16(11), 1516-1521. https://doi.org/10.1016/j.jacr.2019.07.028

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title = "Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement",

abstract = "This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists, and American Association of Physicists in Medicine. AI has great potential to increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and biases. Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues. Currently, there is little experience using AI for patient care in diverse clinical settings. Extensive research is needed to understand how to best deploy AI in clinical practice. This statement highlights our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders in a just manner. We believe AI should respect human rights and freedoms, including dignity and privacy. It should be designed for maximum transparency and dependability. Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future. The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes.",

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author = "Geis, {J. Raymond} and Brady, {Adrian P.} and Wu, {Carol C.} and Jack Spencer and Erik Ranschaert and Jaremko, {Jacob L.} and Langer, {Steve G.} and Kitts, {Andrea Borondy} and Judy Birch and Shields, {William F.} and {van den Hoven van Genderen}, Robert and Elmar Kotter and Gichoya, {Judy Wawira} and Cook, {Tessa S.} and Morgan, {Matthew B.} and An Tang and Safdar, {Nabile M.} and Marc Kohli",

year = "2019",

month = nov,

doi = "10.1016/j.jacr.2019.07.028",

language = "English",

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Geis, JR, Brady, AP, Wu, CC, Spencer, J, Ranschaert, E, Jaremko, JL, Langer, SG, Kitts, AB, Birch, J, Shields, WF, van den Hoven van Genderen, R, Kotter, E, Gichoya, JW, Cook, TS, Morgan, MB, Tang, A, Safdar, NM & Kohli, M 2019, 'Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement', Journal of the American College of Radiology, vol. 16, no. 11, pp. 1516-1521. https://doi.org/10.1016/j.jacr.2019.07.028

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T2 - Summary of the Joint European and North American Multisociety Statement

AU - Geis, J. Raymond

AU - Brady, Adrian P.

AU - Wu, Carol C.

AU - Spencer, Jack

AU - Ranschaert, Erik

AU - Jaremko, Jacob L.

AU - Langer, Steve G.

AU - Kitts, Andrea Borondy

AU - Birch, Judy

AU - Shields, William F.

AU - van den Hoven van Genderen, Robert

AU - Kotter, Elmar

AU - Gichoya, Judy Wawira

AU - Cook, Tessa S.

AU - Morgan, Matthew B.

AU - Tang, An

AU - Safdar, Nabile M.

AU - Kohli, Marc

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N2 - This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists, and American Association of Physicists in Medicine. AI has great potential to increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and biases. Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues. Currently, there is little experience using AI for patient care in diverse clinical settings. Extensive research is needed to understand how to best deploy AI in clinical practice. This statement highlights our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders in a just manner. We believe AI should respect human rights and freedoms, including dignity and privacy. It should be designed for maximum transparency and dependability. Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future. The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes.

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KW - ethics

KW - machine learning

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ER -

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

Abstract

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UN SDGs

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