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放射学中人工智能的伦理问题:欧洲和北美多学会联合声明摘要

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

作者信息

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

机构信息

American College of Radiology Data Science Institute, Reston, Virginia, USA.

Department of Radiology, National Jewish Health, Denver, Colorado, USA.

出版信息

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

摘要

这是一份由美国放射学会(ACR)、欧洲放射学会、北美放射学会(RSNA)、医学影像信息学会、欧洲医学影像信息学会、加拿大放射学会以及美国医学物理学会联合发布的关于放射学中人工智能(AI)伦理的国际多学会声明的精简摘要。人工智能在提高整个放射学领域的效率和准确性方面具有巨大潜力,但也存在内在的缺陷和偏见。在放射学中广泛使用基于人工智能的智能和自主系统会增加产生具有严重后果的系统性错误的风险,并凸显出复杂的伦理和社会问题。目前,在不同临床环境中使用人工智能进行患者护理的经验很少。需要进行广泛研究以了解如何在临床实践中最佳地部署人工智能。

本声明强调了我们的共识,即放射学中人工智能的伦理使用应促进福祉、将危害降至最低,并确保利益和危害以公正的方式在利益相关者之间分配。我们认为人工智能应尊重人权和自由,包括尊严和隐私。它的设计应实现最大程度的透明度和可靠性。在可预见的未来,人工智能的最终责任和问责制仍由其人类设计者和操作者承担。

放射学界现在就应开始制定人工智能的伦理准则和实践规范,促进有助于患者和公共利益的任何应用,并应禁止在不具备这两个特征的情况下将放射学数据和算法用于经济利益。

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本文引用的文献

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What is data ethics?什么是数据伦理?
Philos Trans A Math Phys Eng Sci. 2016 Dec 28;374(2083). doi: 10.1098/rsta.2016.0360.
2
Machine Learning for Medical Imaging.用于医学成像的机器学习
Radiographics. 2017 Mar-Apr;37(2):505-515. doi: 10.1148/rg.2017160130. Epub 2017 Feb 17.
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Implementing Machine Learning in Radiology Practice and Research.在放射学实践与研究中实施机器学习
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