Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement

J Raymond Geis^{1

2}, Adrian Brady³, Carol C Wu⁴, Jack Spencer⁵, Erik Ranschaert⁶, Jacob L Jaremko⁷, Steve G Langer⁸, Andrea Borondy Kitts⁹, Judy Birch¹⁰, William F Shields¹¹, Robert van den Hoven van Genderen¹², Elmar Kotter¹³, Judy Wawira Gichoya^{14

15}, Tessa S Cook¹⁶, Matthew B Morgan¹⁷, An Tang¹⁸, Nabile M Safdar¹⁵, Marc Kohli¹⁹

Affiliations

¹ American College of Radiology Data Science Institute, Reston, Virginia, USA. raym.geis@gmail.com.
² Department of Radiology, National Jewish Health, Denver, Colorado, USA. raym.geis@gmail.com.
³ Mercy University Hospital, Cork, Ireland.
⁴ University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
⁵ Department of Linguistics and Philosophy, MIT, Cambridge, Massachusetts, USA.
⁶ Netherlands Cancer Institute, Amsterdam, the Netherlands.
⁷ Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada.
⁸ Radiology Department-Mayo Clinic, Rochester, Minnesota, USA.
⁹ Lahey Hospital & Medical Center, Burlington, Massachusetts, USA.
¹⁰ Pelvic Pain Support Network, Poole, UK.
¹¹ General Counsel, American College of Radiology, Reston, Virginia, USA.
¹² Center of Law and Internet, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
¹³ Department of Radiology, University Medical Center, Freiburg, Germany.
¹⁴ Department of Interventional Radiology, Oregon Health & Science University, Portland, Oregon, USA.
¹⁵ Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
¹⁶ Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁷ Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.
¹⁸ Centre de Recherche du Centre Hospitalier de L'Université de Montréal, Quebec, Canada.
¹⁹ Department of Radiology and Biomedical Imaging, UCSF, San Francisco, California, USA.

PMID: 31571015
PMCID: PMC6768929
DOI: 10.1186/s13244-019-0785-8

Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement

J Raymond Geis et al. Insights Imaging. 2019.

. 2019 Oct 1;10(1):101.

doi: 10.1186/s13244-019-0785-8.

Authors

Affiliations

¹ American College of Radiology Data Science Institute, Reston, Virginia, USA. raym.geis@gmail.com.
² Department of Radiology, National Jewish Health, Denver, Colorado, USA. raym.geis@gmail.com.
³ Mercy University Hospital, Cork, Ireland.
⁴ University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
⁵ Department of Linguistics and Philosophy, MIT, Cambridge, Massachusetts, USA.
⁶ Netherlands Cancer Institute, Amsterdam, the Netherlands.
⁷ Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada.
⁸ Radiology Department-Mayo Clinic, Rochester, Minnesota, USA.
⁹ Lahey Hospital & Medical Center, Burlington, Massachusetts, USA.
¹⁰ Pelvic Pain Support Network, Poole, UK.
¹¹ General Counsel, American College of Radiology, Reston, Virginia, USA.
¹² Center of Law and Internet, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
¹³ Department of Radiology, University Medical Center, Freiburg, Germany.
¹⁴ Department of Interventional Radiology, Oregon Health & Science University, Portland, Oregon, USA.
¹⁵ Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
¹⁶ Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁷ Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.
¹⁸ Centre de Recherche du Centre Hospitalier de L'Université de Montréal, Quebec, Canada.
¹⁹ Department of Radiology and Biomedical Imaging, UCSF, San Francisco, California, USA.

PMID: 31571015
PMCID: PMC6768929
DOI: 10.1186/s13244-019-0785-8

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 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 which 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.

Keywords: Artificial Intelligence; Data; Ethics; Machine Learning; Radiology.

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Conflict of interest statement

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.

References

1. Kohli M, Prevedello LM, Filice RW, Geis JR (2017) Implementing machine learning in radiology practice and research. AJR Am J Roentgenol:1–7 10.2214/AJR.16.17224 - PubMed
1. Erickson BJ, Korfiatis P, Akkus Z, Kline TL (2017) Machine learning for medical imaging. Radiographics 37:505–515 10.1148/rg.2017160130 - PMC - PubMed
1. Mittelstadt BD, Floridi L (2016) The ethics of big data: current and forseeable issues in biomedical contexts. Sci Eng Ethics 22:303–341 10.1007/s11948-015-9652-2 - PubMed
1. IEEE Standards Association. IEEE Global Initiative Ethically Aligned Design, Version 2 (EADv2). Institute of Electrical and Electronics Engineers. Available via: https://standards.ieee.org/content/dam/ieeestandards/standards/web/docum.... Accessed 23 Aug 2019
1. O’Neil C. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. 1. New York: Crown; 2016.

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Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement

Affiliations

Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement

Authors

Affiliations

Abstract

Conflict of interest statement

References

LinkOut - more resources

Full Text Sources