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评估国家和国际人工智能政策对可持续发展目标3(良好健康与福祉)的规范影响。

Evaluating the normative implications of national and international artificial intelligence policies for Sustainable Development Goal 3: good health and well-being.

作者信息

Mazzi Francesca

机构信息

Brunel Law School, Brunel University London, Uxbridge UB8 3PH, United Kingdom.

出版信息

Health Aff Sch. 2025 May 29;3(6):qxaf108. doi: 10.1093/haschl/qxaf108. eCollection 2025 Jun.


DOI:10.1093/haschl/qxaf108
PMID:40584023
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12202991/
Abstract

INTRODUCTION: Artificial intelligence (AI) has transformative potential in healthcare, promising advancements in diagnostics, treatment, and patient management, attracting significant investments and policy efforts globally. Effective AI governance, comprising guidelines, policy papers, and regulations, is crucial for its successful integration. METHODS: This study evaluates 10 AI policies, namely focusing on 5 international organizations: the United Nations, the Organisation for Economic Co-operation and Development (OECD), the Council of Europe, the G20, and UNESCO, and 5 regional/national entities: Brazil, the United States, the European Union (EU), China, and the United Kingdom, to highlight the implications of AI governance for healthcare. RESULTS: The EU AI Act focuses on risk management and individual protection while fostering innovation aligned with European values. The United Kingdom and the United States adopt a more flexible approach, offering guidelines to stimulate rapid AI integration and innovation without imposing strict regulations. Brazil shows a convergence toward the EU's risk-based approach. CONCLUSIONS: The study explores the normative implications of these varied approaches. The EU's stringent regulations may ensure higher safety and ethical standards, potentially setting a global benchmark, but they could also hinder innovation and pose compliance challenges. The United Kingdom's lenient approach may drive faster AI adoption and competitiveness but risks inconsistencies in safety and ethics. The study concludes by offering recommendations for future research.

摘要

引言:人工智能(AI)在医疗保健领域具有变革潜力,有望在诊断、治疗和患者管理方面取得进展,在全球吸引了大量投资和政策努力。有效的人工智能治理,包括指导方针、政策文件和法规,对于其成功整合至关重要。 方法:本研究评估了10项人工智能政策,重点关注5个国际组织:联合国、经济合作与发展组织(经合组织)、欧洲理事会、二十国集团(G20)和联合国教科文组织,以及5个区域/国家实体:巴西、美国、欧盟、中国和英国,以突出人工智能治理对医疗保健的影响。 结果:欧盟的《人工智能法案》侧重于风险管理和个人保护,同时促进与欧洲价值观相符的创新。英国和美国采取了更为灵活的方法,提供指导方针以刺激人工智能的快速整合和创新,而不施加严格的监管。巴西表现出向欧盟基于风险的方法靠拢的趋势。 结论:该研究探讨了这些不同方法的规范性影响。欧盟的严格法规可能确保更高的安全和道德标准,有可能设定全球基准,但也可能阻碍创新并带来合规挑战。英国宽松的方法可能推动人工智能更快地采用和提高竞争力,但存在安全和道德方面不一致的风险。该研究最后为未来研究提出了建议。

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本文引用的文献

[1]
Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk.

Regul Gov. 2024-1

[2]
Considerations for addressing bias in artificial intelligence for health equity.

NPJ Digit Med. 2023-9-12

[3]
Implementing AI in healthcare-the relevance of trust: a scoping review.

Front Health Serv. 2023-8-24

[4]
Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review.

J Med Internet Res. 2023-4-4

[5]
Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare.

NPJ Digit Med. 2022-5-31

[6]
Advancing health equity with artificial intelligence.

J Public Health Policy. 2021-12

[7]
Achieving a 'Good AI Society': Comparing the Aims and Progress of the EU and the US.

Sci Eng Ethics. 2021-11-12

[8]
Machine Learning Techniques for Personalised Medicine Approaches in Immune-Mediated Chronic Inflammatory Diseases: Applications and Challenges.

Front Pharmacol. 2021-9-30

[9]
The ethics of AI in health care: A mapping review.

Soc Sci Med. 2020-9

[10]
How to Design AI for Social Good: Seven Essential Factors.

Sci Eng Ethics. 2020-6

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