Journal of the Korean Society of Radiology (대한영상의학회지)

The Korean Society of Radiology (대한영상의학회)
권호 표지
DOI QR코드

DOI QR Code

Ethics for Artificial Intelligence: Focus on the Use of Radiology Images

인공지능 의료윤리: 영상의학 영상데이터 활용 관점의 고찰

  • Seong Ho Park (Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine)
  • 박성호 (울산대학교 의과대학 서울아산병원 영상의학과)
  • Received : 2022.03.28
  • Accepted : 2022.05.02
  • Published : 2022.07.01
Download PDF
⟨ Previous Next ⟩

Abstract

The importance of ethics in research and the use of artificial intelligence (AI) is increasingly recognized not only in the field of healthcare but throughout society. This article intends to provide domestic readers with practical points regarding the ethical issues of using radiological images for AI research, focusing on data security and privacy protection and the right to data. Therefore, this article refers to related domestic laws and government policies. Data security and privacy protection is a key ethical principle for AI, in which proper de-identification of data is crucial. Sharing healthcare data to develop AI in a way that minimizes business interests is another ethical point to be highlighted. The need for data sharing makes the data security and privacy protection even more important as data sharing increases the risk of data breach.

인공지능의 연구 개발 및 활용에서 윤리의 중요성이 의료분야뿐 아니라 전 사회적으로 점차 널리 인식되고 있다. 이 종설은 영상의학 영상데이터를 인공지능 연구에 활용할 때 개인정보의 보호 및 데이터에 대한 권리 측면에서 윤리적으로 고려할 사항들에 대해서 국내 독자들에게 실용적인 정보를 제공하고자 한다. 따라서 이 글에 담긴 내용은 많은 부분이 관련된 국내 법과 정부 제도에 바탕을 두고 있다. 인공지능의 연구 개발 및 활용에서 개인정보 보호는 매우 중요한 윤리적 원칙이며 연구 데이터의 적절한 가명처리는 개인정보 보호를 위한 핵심 방법이다. 아울러 인공지능 연구 개발에 의료 데이터를 상업적 이해관계를 최소화하며 윤리적으로 공유할 필요성도 부각되고 있다. 연구 데이터 공유는 개인정보 유출의 위험을 증가시키므로 개인정보 보호에 더욱 주의가 필요하다.

Keywords

References

  1. Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines. Nat Mach Intell 2019;1:389-399
  2. The Presidential Committee on the 4th industrial revolution. Available at. https://www.4th-ir.go.kr/article/download/744. Accessed March 27, 2022
  3. High-level Expert Group on AI. Ethics guidelines for trustworthy AI. Available at. https://data.europa.eu/doi/10.2759/177365. Accessed March 27, 2022
  4. OECD Committee on Digital Economy Policy. OECD AI principles overview. Available at. https://oecd.ai/en/ai-principles. Accessed March 27, 2022
  5. UNESCO. Recommendation on the ethics of artificial intelligence. Available at. https://en.unesco.org/artificial-intelligence/ethics. Accessed March 27, 2022
  6. WHO. Ethics and governance of artificial intelligence for health. Available at. https://www.who.int/publications/i/item/9789240029200. Accessed March 27, 2022
  7. Geis JR, Brady AP, Wu CC, Spencer J, Ranschaert E, Jaremko JL, et al. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. Radiology 2019;293:436-440
  8. Geis JR, Brady AP, Wu CC, Spencer J, Ranschaert E, Jaremko JL, et al. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. J Am Coll Radiol 2019;16:1516-1521
  9. Geis JR, Brady A, Wu CC, Spencer J, Ranschaert E, Jaremko JL, et al. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. Insights Imaging 2019;10:101
  10. Geis JR, Brady AP, Wu CC, Spencer J, Ranschaert E, Jaremko JL, et al. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. Can Assoc Radiol J 2019;70:329-334
  11. Jaremko JL, Azar M, Bromwich R, Lum A, Alicia Cheong LH, Gibert M, et al. Canadian Association of Radiologists white paper on ethical and legal issues related to artificial intelligence in radiology. Can Assoc Radiol J 2019;70:107-118
  12. The Royal Australian and New Zealand College of Radiologists. Ethical principles for AI in medicine. Available at. https://www.ranzcr.com/search/ethical-principles-for-ai-in-medicine. Accessed March 27, 2022
  13. The Korean Law Information Center. Available at. https://www.law.go.kr/%EB%B2%95%EB%A0%B9/%EA%B0%9C%EC%9D%B8%EC%A0%95%EB%B3%B4%EB%B3%B4%ED%98%B8%EB%B2%95. Accessed March 27, 2022
  14. The Korean Ministry of Health and Welfare. Available at. http://www.mohw.go.kr/react/al/sal0101vw.jsp?PAR_MENU_ID=04&MENU_ID=040101&CONT_SEQ=363309&page=1. Accessed March 27, 2022
  15. Yoo S. Park SH. Law and policy related to healthcare big data and artificial intelligence. In Park SH, Lim TH, eds. Artificial intelligence: guide for healthcare personnel. 1st ed. Paju: Koonja 2020:209-222
  16. Schwarz CG, Kremers WK, Therneau TM, Sharp RR, Gunter JL, Vemuri P, et al. Identification of anonymous MRI research participants with face-recognition software. N Engl J Med 2019;381:1684-1686
  17. Safdar NM, Banja JD, Meltzer CC. Ethical considerations in artificial intelligence. Eur J Radiol 2020;122:108768
  18. Larson DB, Magnus DC, Lungren MP, Shah NH, Langlotz CP. Ethics of using and sharing clinical imaging data for artificial intelligence: a proposed framework. Radiology 2020;295:675-682
  19. Bauchner H, Golub RM, Fontanarosa PB. Data sharing: an ethical and scientific imperative. JAMA 2016;315:1237-1239
  20. Jorgenson LA, Wolinetz CD, Collins FS. Incentivizing a new culture of data stewardship: the NIH policy for data management and sharing. JAMA 2021;326:2259-2260
  21. International Committee of Medical Journal Editors. Data sharing. Available at. https://www.icmje.org/recommendations/browse/publishing-and-editorial-issues/clinical-trial-registration.html. Accessed March 27, 2022
  22. Futoma J, Simons M, Panch T, Doshi-Velez F, Celi LA. The myth of generalisability in clinical research and machine learning in health care. Lancet Digit Health 2020;2:e489-e492
  23. Park SH, Choi J, Byeon JS. Key principles of clinical validation, device approval, and insurance coverage decisions of artificial intelligence. Korean J Radiol 2021;22:442-453
  24. Ursin G, Malila N, Chang-Claude J, Gunter M, Kaaks R, Kampman E, et al. Sharing data safely while preserving privacy. Lancet 2019;394:1902