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Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement
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 o...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768929/ https://www.ncbi.nlm.nih.gov/pubmed/31571015 http://dx.doi.org/10.1186/s13244-019-0785-8 |
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author | Geis, J. Raymond Brady, Adrian Wu, Carol C. Spencer, Jack Ranschaert, Erik Jaremko, Jacob L. Langer, Steve G. Kitts, Andrea Borondy Birch, Judy Shields, William F. van den Hoven van Genderen, Robert Kotter, Elmar Gichoya, Judy Wawira Cook, Tessa S. Morgan, Matthew B. Tang, An Safdar, Nabile M. Kohli, Marc |
author_facet | Geis, J. Raymond Brady, Adrian Wu, Carol C. Spencer, Jack Ranschaert, Erik Jaremko, Jacob L. Langer, Steve G. Kitts, Andrea Borondy Birch, Judy Shields, William F. van den Hoven van Genderen, Robert Kotter, Elmar Gichoya, Judy Wawira Cook, Tessa S. Morgan, Matthew B. Tang, An Safdar, Nabile M. Kohli, Marc |
author_sort | Geis, J. Raymond |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13244-019-0785-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6768929 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-67689292019-10-09 Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement Geis, J. Raymond Brady, Adrian Wu, Carol C. Spencer, Jack Ranschaert, Erik Jaremko, Jacob L. Langer, Steve G. Kitts, Andrea Borondy Birch, Judy Shields, William F. van den Hoven van Genderen, Robert Kotter, Elmar Gichoya, Judy Wawira Cook, Tessa S. Morgan, Matthew B. Tang, An Safdar, Nabile M. Kohli, Marc Insights Imaging Statement 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13244-019-0785-8) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2019-10-01 /pmc/articles/PMC6768929/ /pubmed/31571015 http://dx.doi.org/10.1186/s13244-019-0785-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Statement Geis, J. Raymond Brady, Adrian Wu, Carol C. Spencer, Jack Ranschaert, Erik Jaremko, Jacob L. Langer, Steve G. Kitts, Andrea Borondy Birch, Judy Shields, William F. van den Hoven van Genderen, Robert Kotter, Elmar Gichoya, Judy Wawira Cook, Tessa S. Morgan, Matthew B. Tang, An Safdar, Nabile M. Kohli, Marc Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement |
title | Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement |
title_full | Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement |
title_fullStr | Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement |
title_full_unstemmed | Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement |
title_short | Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement |
title_sort | ethics of artificial intelligence in radiology: summary of the joint european and north american multisociety statement |
topic | Statement |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768929/ https://www.ncbi.nlm.nih.gov/pubmed/31571015 http://dx.doi.org/10.1186/s13244-019-0785-8 |
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