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

  • J. Raymond Geis*
  • , Adrian 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 JournalArticleAcademicpeer-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 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.

Original languageEnglish
Article number101
Pages (from-to)1-6
Number of pages6
JournalInsights into Imaging
Volume10
Issue number1
Early online date1 Oct 2019
DOIs
Publication statusPublished - 1 Dec 2019

Funding

This article is a joint statement published in Insights into Imaging [10.1186/s13244-019-0785-8], Radiology [10.1148/radiol.2019191586], Journal of American College of Radiology [10.1016/j.jacr.2019.07.028], and Canadian Association of Radiologists Journal [10.1016/j.carj.2019.08.010].

FundersFunder number
Canadian Association of Radiologists Journal
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    UN SDGs

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

    1. SDG 16 - Peace, Justice and Strong Institutions
      SDG 16 Peace, Justice and Strong Institutions

    Keywords

    • Artificial Intelligence
    • Data
    • Ethics
    • Machine Learning
    • Radiology

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