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

被引:36
作者
Geis, J. Raymond [1 ,2 ]
Brady, Adrian P. [3 ]
Wu, Carol C. [4 ]
Spencer, Jack [5 ]
Ranschaert, Erik [6 ]
Jaremko, Jacob L. [7 ]
Langer, Steve G. [8 ]
Kitts, Andrea Borondy [9 ]
Birch, Judy [10 ]
Shields, William F. [11 ]
van Genderen, Robert van den Hoven [12 ]
Kotter, Elmar [13 ]
Gichoya, Judy Wawira [14 ,15 ]
Cook, Tessa S. [16 ]
Morgan, Matthew B. [17 ]
Tang, An [18 ]
Safdar, Nabile M. [15 ]
Kohli, Marc [19 ]
机构
[1] Amer Coll Radiol, Data Sci Inst, Reston, VA USA
[2] Natl Jewish Hlth, Dept Radiol, Denver, CO USA
[3] Mercy Univ Hosp, Cork, Ireland
[4] Univ Texas MD Anderson Canc Ctr, Houston, TX 77030 USA
[5] MIT, Dept Linguist & Philosophy, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[6] Netherlands Canc Inst, Amsterdam, Netherlands
[7] Univ Alberta, Dept Radiol & Diagnost Imaging, Edmonton, AB, Canada
[8] Mayo Clin, Radiol Dept, Rochester, MN USA
[9] Lahey Hosp & Med Ctr, Burlington, MA USA
[10] Pelv Pain Support Network, Poole, Dorset, England
[11] Amer Coll Radiol, Gen Counsel, Reston, VA USA
[12] Vrije Univ Amsterdam, Ctr Law & Internet, Amsterdam, Netherlands
[13] Univ Med Ctr, Dept Radiol, Freiburg, Germany
[14] Oregon Hlth & Sci Univ, Dept Intervent Radiol, Portland, OR 97201 USA
[15] Emory Univ, Dept Radiol & Imaging Sci, Atlanta, GA 30322 USA
[16] Univ Penn, Dept Radiol, Philadelphia, PA 19104 USA
[17] Univ Utah, Dept Radiol & Imaging Sci, Salt Lake City, UT USA
[18] Ctr Hosp Univ Montreal, Ctr Rech, Quebec City, PQ, Canada
[19] UCSF, Dept Radiol & Biomed Imaging, San Francisco, CA USA
关键词
Artificial intelligence; data; ethics; machine learning; radiology;
D O I
10.1016/j.jacr.2019.07.028
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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. Al 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.
引用
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页码:1516 / 1521
页数:6
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