과학기술학 관점에서 본 헬스케어 AI 윤리와 환자·시민 참여
Healthcare AI Ethics and Patient and Public Engagement: An Science and Technology Studies (STS) Perspective
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This article discusses Junhewk Kim’s “Patient and Public Involvement Model in Healthcare artificial intelligence (AI) Ethics.” I focus on two key aspects of Kim’s argument: the particularity of healthcare AI research compared to traditional medical research, and the exclusive legitimacy of patients and citizens as the subjects of external validation. I contend that Kim’s current reasoning does not elucidate the unique nature of big data in healthcare AI and risks limiting the democratic potential of participatory models. The field of Science and Technology Studies (STS), which explores the relationship between science and society, could help to strengthen Kim’s argument by providing a more focused analysis of big data and citizen participation. I conclude that although public involvement is a procedural condition for creating ethical healthcare AI, it is not sufficient on its own to render healthcare AI ethical. The realization of ethical healthcare AI depends on fostering robust interactions among patients, citizens, and experts that go beyond individualistic notions of privacy and ownership and challenge the rigid divide between healthcare professionals and laypeople.
Abstract
This article discusses Junhewk Kim’s “Patient and Public Involvement Model in Healthcare artificial intelligence (AI) Ethics.” I focus on two key aspects of Kim’s argument: the particularity of healthcare AI research compared to traditional medical research, and the exclusive legitimacy of patients and citizens as the subjects of external validation. I contend that Kim’s current reasoning does not elucidate the unique nature of big data in healthcare AI and risks limiting the democratic potential of participatory models. The field of Science and Technology Studies (STS), which explores the relationship between science and society, could help to strengthen Kim’s argument by providing a more focused analysis of big data and citizen participation. I conclude that although public involvement is a procedural condition for creating ethical healthcare AI, it is not sufficient on its own to render healthcare AI ethical. The realization of ethical healthcare AI depends on fostering robust interactions among patients, citizens, and experts that go beyond individualistic notions of privacy and ownership and challenge the rigid divide between healthcare professionals and laypeople.
참고문헌 (16)
- Hess DJ, "Undone science: social movements, mobilized publics, and industrial transitions" (2016), The MIT Press
- Epstein S, "The construction of lay expertise : AIDS activism and the forging of credibility in the reform of clinical trials", Sci Technol Human Value, 20(4), pp.408~437 (1995)[DOI]
- Brown P, "Popular epidemiology and toxic waste contamination : lay and professional ways of knowing", J Health Soc Behav, 33(3), pp.267~281 (1992)[DOI]
- Shin Y, "The government should play a role greater than that of construction supervisor in the national bio-big data infrastructure", J Korean Med Soc, 39(36), pp.e262~ (2024)[DOI]
- Criado Perez C, "Invisible women: data bias in a world designed for men" (2019), Chatto & Windus
- Eubanks V, "Automating inequality: how high-tech tools profile, police, and punish the poor" (2018), St. Martin’s Press
- Petryna A, "When experiments travel: clinical trials and the global search for human subjects" (2009), Princeton University Press
- Strasser BJ, "Big data is the answer ... but what Is the question?", Osiris, 32(1), pp.328~345 (2017)[DOI]
- Edwards PN, "A vast machine: computer models, climate data, and the politics of global warming" (2013), The MIT Press
- Talyor L, "Group privacy: new challenges of data technologies", pp.1~12 (2017), Springer International Publishing
- Helm P, "Generating reality and silencing debate : synthetic data as discursive device", Big Data Soc, 11(2), pp.2053951724124944~ (2024)[DOI]
- Research ethics guidelines for healthcare AI researchers, "National Institute of Health", National Institute of Health, ~ (2023)
- Pols J, "Knowing patients : turning patient knowledge into science", Sci Technol Human Value, 39(1), pp.73~97 (2014)[DOI]
- Hartblay C, "Disability expertise : claiming disability anthropology", Curr Anthropol, 61(S21), pp.S26~S36 (2020)[DOI]
- Haraway D, "Situated knowledges : the science question in feminism and the priviledge of partial perspective", Fem Stud, 14(3), pp.575~599 (1988)[DOI]
- Blacker S, "When citizen science is public relations", Soc Stud Sci, 51(5), pp.780~796 (2021)[DOI]