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推进健康与基因组学领域的人工智能伦理:来自韩国一项公众调查的经验教训。

Advancing artificial intelligence ethics in health and genomics: lessons from a public survey in South Korea.

作者信息

Lee Jungim, Yoo Wonhoo, Kim Hannah

机构信息

Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea.

Asian Institute for Bioethics and Health Law, Yonsei University, Seoul, Republic of Korea.

出版信息

Front Genet. 2025 Jul 9;16:1563544. doi: 10.3389/fgene.2025.1563544. eCollection 2025.

DOI:10.3389/fgene.2025.1563544
PMID:40704061
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12284414/
Abstract

Advances in healthcare and genetics are becoming increasingly integrated with artificial intelligence (AI), offering transformative potential alongside complex ethical challenges. This study aimed to assess public awareness and perceptions of AI ethics in healthcare (AI-H) in South Korea, with the ultimate goal of informing the development of research ethics guidelines. A nationwide online survey was conducted from January 10 to 20, 2023, targeting the general public, and 1,002 respondents were recruited through stratified random sampling. The questionnaire explored expectations of AI-H, perceived risks, willingness to share different types of personal data, and the perceived importance of various ethical principles and education targets. A large majority of respondents (84.5%) expressed optimism about the positive impacts of AI-H over the next five years, while only 3.1% anticipated negative consequences. Key concerns included the disclosure of personal information (54.0%), potential AI errors causing harm (52.0%), and ambiguous legal responsibilities (42.2%). Willingness to share data was highest for electronic medical records (72.8%), lifestyle data (72.3%), and biometric data (71.3%), while genetic data was least preferred (64.1%). Ethical principles considered most important were privacy protection (83.9%), safety and security (83.7%), legal duties (83.4%), and responsiveness (83.3%). Developers (70.7%), medical institution managers (68.2%), and researchers (65.6%) were identified as top priorities for ethics education, whereas the general public (31.0%) and students (18.7%) ranked lower. This study represents the first nationwide assessment of public ethical awareness of AI-H in South Korea. While there is strong support for AI-H, significant concerns remain, particularly regarding data privacy and legal accountability. The findings highlight the need for expanded ethics education, especially among younger populations, and for balanced attention to ethical principles beyond privacy, such as inclusiveness and accessibility. These insights provide valuable guidance for developing socially responsible AI policies and practices in healthcare.

摘要

医疗保健和遗传学领域的进展正日益与人工智能(AI)相结合,在带来变革潜力的同时也带来了复杂的伦理挑战。本研究旨在评估韩国公众对医疗保健领域人工智能伦理(AI-H)的认知和看法,最终目标是为研究伦理准则的制定提供参考。2023年1月10日至20日对韩国公众进行了一项全国性在线调查,通过分层随机抽样招募了1002名受访者。问卷探讨了对AI-H的期望、感知到的风险、分享不同类型个人数据的意愿,以及各种伦理原则和教育目标的重要性。绝大多数受访者(84.5%)对未来五年AI-H的积极影响表示乐观,而只有3.1%的人预计会有负面影响。主要担忧包括个人信息泄露(54.0%)、人工智能错误可能造成伤害(52.0%)以及法律责任不明确(42.2%)。分享数据的意愿在电子病历(72.8%)、生活方式数据(72.3%)和生物识别数据(71.3%)方面最高,而遗传数据最不受青睐(64.1%)。被认为最重要的伦理原则是隐私保护(83.9%)、安全保障(83.7%)、法律义务(83.4%)和响应能力(83.3%)。开发者(70.7%)、医疗机构管理人员(68.2%)和研究人员(65.6%)被确定为伦理教育的首要对象,而普通公众(31.0%)和学生(18.7%)的排名较低。本研究是韩国首次对公众对AI-H的伦理认知进行的全国性评估。虽然对AI-H有强烈支持,但仍存在重大担忧,特别是在数据隐私和法律问责方面。研究结果凸显了扩大伦理教育的必要性,尤其是在年轻人群体中,以及需要平衡关注隐私之外的伦理原则,如包容性和可及性。这些见解为在医疗保健领域制定对社会负责的人工智能政策和实践提供了有价值的指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/900695e5e161/fgene-16-1563544-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/e338eacc2546/fgene-16-1563544-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/5bbe46582556/fgene-16-1563544-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/9a3658c03734/fgene-16-1563544-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/900695e5e161/fgene-16-1563544-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/e338eacc2546/fgene-16-1563544-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/5bbe46582556/fgene-16-1563544-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/9a3658c03734/fgene-16-1563544-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0084/12284414/900695e5e161/fgene-16-1563544-g004.jpg

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1
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2
Emerging challenges in AI and the need for AI ethics education.人工智能领域新出现的挑战以及人工智能伦理教育的必要性。
AI Ethics. 2021;1(1):61-65. doi: 10.1007/s43681-020-00002-7. Epub 2020 Oct 6.
3
American public opinion on artificial intelligence in healthcare.美国公众对医疗人工智能的看法。
PLoS One. 2023 Nov 9;18(11):e0294028. doi: 10.1371/journal.pone.0294028. eCollection 2023.
4
The ethics of advancing artificial intelligence in healthcare: analyzing ethical considerations for Japan's innovative AI hospital system.人工智能在医疗保健领域的伦理问题:分析日本创新型人工智能医院系统的伦理考量。
Front Public Health. 2023 Jul 17;11:1142062. doi: 10.3389/fpubh.2023.1142062. eCollection 2023.
5
Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review.美国公众对医疗保健领域人工智能认知的调查:系统综述。
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6
Reframing data ethics in research methods education: a pathway to critical data literacy.在研究方法教育中重新构建数据伦理:通往批判性数据素养之路。
Int J Educ Technol High Educ. 2023;20(1):11. doi: 10.1186/s41239-023-00380-y. Epub 2023 Feb 20.
7
Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey.医生和医学生对临床人工智能的接受度:一项横断面调查的系统评价
Front Med (Lausanne). 2022 Aug 31;9:990604. doi: 10.3389/fmed.2022.990604. eCollection 2022.
8
Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients.患者对医疗保健中人工智能的态度和认知:一项横断面调查
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9
Perspectives of Patients About Artificial Intelligence in Health Care.患者对医疗保健中人工智能的看法。
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10
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