欧盟人工智能数据治理的政策布局与治理特征研究

doi:10.13998/j.cnki.issn1002-1248.25-0374

摘要/Abstract

摘要：

【目的/意义】 人工智能技术的快速迭代重塑了合规化、全域化与精细化的数据治理需求。欧盟率先构建了人工智能数据治理的基准框架，研究欧盟人工智能数据治理的政策布局及其特征，能够为中国参与全球人工智能数据治理提供参考。 【方法/过程】 系统收集欧盟及成员国人工智能数据治理政策文件，梳理其发展历程；构建“治理目标-治理主体-治理工具”三维分析框架，进一步解析并提炼治理核心要素，揭示欧盟人工智能数据治理的政策布局和治理特征。 【结果/结论】 研究发现，欧盟人工智能数据治理经历了从软法向硬法过渡，制度性约束力持续强化。在治理目标上，欧盟以数据伦理保障、数据安全防护和数据价值释放为核心锚点；在治理主体上，依托欧盟与成员国双层协同的立法与执行体系，并吸纳行业组织、学术界等多元利益主体参与共治；在治理工具上，聚焦数据治理规则约束与程序规范构建、数据基础设施与生态建设、内外协同与多方治理联动等措施。整体呈现出以欧盟统一规范锚定治理演进坐标，凝聚全域数据治理共识框架；成员国在平衡统一规范与构建差异化路径中保持自主调适空间；遵循数据强监管与人工智能创新协同演进的发展范式等治理特征。

关键词: 欧盟, 人工智能, 数据治理, 政策布局, 治理特征

Abstract:

[Purpose/Significance] The rapid development of artificial intelligence (AI) technology has reshaped the demand for data governance that is compliant, comprehensive, and refined. The European Union (EU) has proactively established a benchmark framework for AI data governance through targeted policy measures. However, there is a lack of systematic analysis on the policy layout and governance characteristics of AI data governance in the EU, both domestically and internationally. This paper focuses on the AI data governance policies in the EU, aiming to reveal the development process, policy layout, and governance characteristics of AI data governance in the region, providing valuable insights and references for advancing the global paradigm of AI data governance. [Method/Process] This paper systematically collects core AI data governance policy documents from 10 EU member states and the United Kingdom through multiple channels. By manually reviewing and selecting policy units related to "AI data governance," the paper traces the development process and uses a three-dimensional analytical framework - governance goals, governance bodies, and governance tools - to reveal the policy layout and governance characteristics of AI data governance in the EU. [Results/Conclusions] The study found that AI data governance in the EU has transitioned from soft law guidance to hard law regulation, gradually establishing three key governance goals: data ethics protection, data security defense, and data value release. Through the establishment of a multi-level legislative system and a coordinated execution framework, the EU focuses on regulatory constraints, procedural norms, AI system element support, and data ecosystem construction, demonstrating comprehensive governance capabilities. First, the EU has constructed a consensus framework for data governance through unified norms, centrally coordinating the diverse needs of member states during policy implementation, ensuring high consistency of governance rules across the EU. Second, the EU's policy design strikes a balance between rule uniformity and national autonomy, allowing member states to adjust policies flexibly according to their unique data cultures and industrial structures, fostering better localized governance. Third, the EU's governance model achieves a dynamic balance between "strong regulation" and "promoting development," ensuring the protection of citizens' rights through stringent ethical and risk prevention measures, while fostering innovation by releasing data value and driving AI industry growth. This paper provides a systematic analysis of the layout and characteristics of AI data governance in the EU. Future research could compare the EU framework with AI data governance policies in other major economies, such as the United States and China, to identify their respective strengths and weaknesses.

Key words: Europe, artificial intelligence regulation, data governance, data governance policy, policy layout

中图分类号: G350

董克, 宋雨宸, 吴佳纯. 欧盟人工智能数据治理的政策布局与治理特征研究[J/OL]. 农业图书情报学报. https://doi.org/10.13998/j.cnki.issn1002-1248.25-0374.

DONG Ke, SONG Yuchen, WU Jiachun. Layout and Characteristics of European AI Data Governance Policy[J/OL]. Journal of library and information science in agriculture. https://doi.org/10.13998/j.cnki.issn1002-1248.25-0374.

图/表 5

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欧盟人工智能数据治理核心政策文件样例"

时间	政策名称	颁布机构	地位和作用	核心内容
2018.05	《通用数据保护条例》	欧盟委员会、欧洲议会、欧盟理事会	全面数据保护法规，旨在加强个人数据的保护并统一欧盟各成员国。通过强化个人数据权利、提高透明性要求和严格责任机制，深刻影响AI领域数据治理模式	确立了合法性、目的限制等6项数据处理原则；赋予数据主体知情权、访问权、删除权等八项权利；强制要求数据控制者和处理者落实隐私设计、72小时数据泄露通知、DPIA评估及任命DPO等义务；严格规范非欧盟国家间的跨境数据传输；由成员国DPA监管执行，对违规行为处以罚款
2019.04	《可信人工智能伦理指南》	欧盟委员会、AI HLEG	倡导性文件，欧委会以政策通讯形式转发。涵盖人工智能基本原则指南，涉及个人数据保护、透明度等内容	提出“以人为本的可信人工智能”七项基本准则，包括接受人类管理监督、技术稳健安全、隐私与数据治理、透明度、多样性、非歧视与公平、社会环境福祉及问责制
2021.04	《人工智能协调计划》	欧盟委员会	推动了欧盟和成员国在人工智能发展和治理方面协同行动，以共促欧盟占据人工智能全球领导地位	提出协调欧盟机构与成员国政府推进的7项任务：完善战略布局、加大多元投入、促进产研融合、培养专业人才、推动数据共享、建立监管框架、鼓励技术应用、加强国际合作
2020.02	《人工智能白皮书》	欧盟委员会	提出了实施欧洲人工智能战略的具体路径，旨在实现“可靠”和“安全”人工智能发展	提出以监管和投资为导向，实现促进人工智能应用和解决应用风险的双重目标；明确AI监管框架应立足风险评估，对应用分级分类并实施差异化事前规制
2024.08	《人工智能法案》	欧盟委员会、欧洲议会、欧盟理事会	全球首部针对人工智能的专门性法律，旨在保护个人基本权利、民主、法治免受高风险人工智能系统影响，同时促进技术创新，推动欧盟成为人工智能领域的领导者	提出人工智能风险等级划分标准；制定覆盖人工智能产品从研发到应用全过程的风险规制体系和“谁提供谁负责”的责任划分原则；涵盖了AI大模型训练数据合规、个人数据保护、AI标识义务等合规要点

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参考文献 39

[1]	Artificial Intelligence Index Report 2025[EB/OL]. [2025-03-27].
[2]	周文泓, 叶雅寒, 熊小芳. 我国面向人工智能的数据治理政策体系构建进展与展望[J]. 图书馆论坛, 2025, 45(5): 141-150.
	ZHOU W H, YE Y H, XIONG X F. Progress and prospects of data governance policy system for artificial intelligence in China[J]. Library tribune, 2025, 45(5): 141-150.
[3]	徐伟, 何野. 生成式人工智能数据安全风险的治理体系及优化路径: 基于38份政策文本的扎根分析[J]. 电子政务, 2024(10): 42-58.
	XU W, HE Y. Governance system and optimization path of data security risk of generative artificial intelligence: Based on the grounded analysis of 38 policy texts[J]. E-Government, 2024(10): 42-58.
[4]	周文泓, 杨璐羽, 吴一凡. 欧盟数据政策体系研究及其启示[J]. 情报理论与实践, 2025, 48(1): 184-192, 204.
	ZHOU W H, YANG L Y, WU Y F. Research on data policy system of EU and its implications[J]. Information studies: Theory & application, 2025, 48(1): 184-192, 204.
[5]	李凯莉. 《人工智能法案》对欧盟数字主权构建的回应及成效[J]. 政法论丛, 2025(2): 156-169.
	LI K L. The response of artificial intelligence act to EU digital sovereignty and its effectiveness[J]. Journal of political science and law, 2025(2): 156-169.
[6]	CANCELA-OUTEDA C. The EU's AI act: A framework for collaborative governance[J]. Internet of Things, 2024, 27: 101291.
[7]	李继峰, 张成龙, 刘鑫, 等. 面向人工智能的数据治理框架[J]. 大数据, 2025, 11(1): 3-20.
	LI J F, ZHANG C L, LIU X, et al. Data governance framework for artificial intelligence[J]. Big data research, 2025, 11(1): 3-20.
[8]	JUSTO-HANANI R. The politics of Artificial Intelligence regulation and governance reform in the European Union[J]. Policy sciences, 2022, 55(1): 137-159.
[9]	WANG S R, ZHANG Y M, XIAO Y M, et al. Artificial intelligence policy frameworks in China, the European union and the United States: An analysis based on structure topic model[J]. Technological forecasting and social change, 2025, 212: 123971.
[10]	王旭, 谢方, 邱均平. 全球人工智能治理研究: 进展、挑战与策略[J]. 图书馆论坛, 2025, 45(8): 86-96.
	WANG X, XIE F, QIU J P. A study on global artificial intelligence governance: Progress, challenges, and strategies[J]. Library tribune, 2025, 45(8): 86-96.
[11]	钭晓东. 论生成式人工智能的数据安全风险及回应型治理[J]. 东方法学, 2023(5): 106-116.
	DOU X D. On the data security risk of generative AI and its responsive governance[J]. Oriental law, 2023(5): 106-116.
[12]	丁道勤. 生成式人工智能训练阶段的数据法律问题及其立法建议[J]. 行政法学研究, 2024(6): 16-28.
	DING D Q. Data legal issues and legislation advice during the training phase of generative artificial intelligence[J]. Administrative law review, 2024(6): 16-28.
[13]	OECD.AI. The OECD artificial intelligence policy observatory - OECD.AI[EB/OL]. [2025-03-27].
[14]	吴佳纯, 董克, 马廷灿. 我国数据跨境流动治理政策分析与优化路径研究: 基于“执行主体-政策工具-政策目标”协同视角[J]. 现代情报, 2025, 45(8): 109-120.
	WU J C, DONG K, MA T C. Research on policy analysis and optimization path of cross-border data flow governance in China: Based on the synergistic perspective of "executing subjects-policy tools-policy objectives"[J]. Journal of modern information, 2025, 45(8): 109-120.
[15]	Commission European. General data protection regulation[EB/OL]. [2025-03-27].
[16]	Commission European. Guidelines on automated individual decision-making and profiling for the purposes of regulation[EB/OL]. [2025-03-27].
[17]	Commission European. Ethics guidelines for trustworthy AI[EB/OL]. [2025-03-27].
[18]	Parliament European. A governance framework for algorithmic accountability and transparency[EB/OL]. [2025-03-27].
[19]	United Kingdom Parliament. AI in the UK: Ready, willing and able[EB/OL]. [2025-03-27].
[20]	Commission European. A european strategy for data[EB/OL]. [2025-03-27].
[21]	Commission European. White paper on artificial intelligence - A European approach to excellence and trust[EB/OL]. [2025-03-27].
[22]	Bundesministerium für Wirtschaft und Klimaschutz. Strategie künstliche intelligenz der bundesregierung[EB/OL]. [2025-03-27].
[23]	Ministry of Economic Affairs and Employment of Finland. Artificial intelligence 4.0 programme[EB/OL]. [2025-03-27].
[24]	Department for Science, Innovation and Technology. National AI strategy[EB/OL]. [2025-03-27].
[25]	Commission European. Generative AI and the EUDPR[EB/OL]. [2025-03-27].
[26]	Rijksoverheid. Overheidsbrede visie generatieve AI[EB/OL]. [2025-03-27].
[27]	Bundesministerium für Bildung und Forschung. BMBF-aktionsplan künstliche intelligenz[EB/OL]. [2025-03-27].
[28]	Accueil Direction générale des Entreprises. Stratégie nationale pour l'intelligence artificielle - 2e phase[EB/OL]. [2025-03-27].
[29]	Commission European. Coordinated plan on artificial intelligence[EB/OL]. [2025-03-27].
[30]	Parliament European. EU AI act[EB/OL]. [2025-03-27].
[31]	Parliament European. Data governance act[EB/OL]. [2025-03-27].
[32]	HOWLETT M, RAMESH M, PERL A. Studying public policy: Policy cycles and policy subsystems[M]. Oxford: Oxford University Press, 2009.
[33]	黄丽娜, 黄璐. 中国互联网治理的政策工具: 型构、选择与优化: 基于1994-2017年互联网政策文本的内容分析[J]. 情报杂志, 2020, 39(4): 90-97, 73.
	HUANG L N, HUANG L. Policy tools of Internet governance in China: Structure, selection and optimization: Content analysis of Internet policy texts(1994-2017)[J]. Journal of intelligence, 2020, 39(4): 90-97, 73.
[34]	MCDONNELL L M, ELMORE R F. Getting the job done: Alternative policy instruments[J]. Educational evaluation and policy analysis, 1987, 9(2): 133-152.
[35]	高再红, 张心志. 欧盟参与人工智能全球治理的政策工具、路径特征及影响分析[J]. 中国科技论坛, 2025(5): 150-160.
	GAO Z H, ZHANG X Z. The policy tools, path characteristics and impacts of the EU's participation in the global governance of artificial intelligence[J]. Forum on science and technology in China, 2025(5): 150-160.
[36]	Commission European. Digital markets act[EB/OL]. [2025-03-27].
[37]	High-Level Expert Group on AI. Policy and investment recommendations for trustworthy artificial intelligence[EB/OL]. [2025-03-27].
[38]	曾雄, 梁正, 张辉. 欧盟人工智能的规制路径及其对我国的启示: 以《人工智能法案》为分析对象[J]. 电子政务, 2022(9): 63-72.
	ZENG X, LIANG Z, ZHANG H. The regulation path of artificial intelligence in EU and its enlightenment to China: Taking the artificial intelligence act as the analysis object[J]. E-Government, 2022(9): 63-72.
[39]	Department for Science, Innovation and Technology. AI regulation: A pro-innovation approach[EB/OL]. [2025-03-27].

治理主体维度	机构层级	主要职责
立法主体	欧盟	由欧盟委员会负责起草并提案，欧洲议会对条款进行实质审议与修正，欧盟理事会协调各国政策立场，三者通过共同决策程序形成立法成果
立法主体	成员国	一般为政府负责政策草案的起草与战略规划，议会负责对草案进行审议与修订，并通过立法程序推动政策落地，具体分工则根据各国政体各有不同
执行主体	欧盟	包括GDPR框架下的EDPB与EDPS等数据治理机构、AI ACT设立的AI Office与EAIB，以及ENISA、FRA等技术与法律支持机构；负责统筹规则执行与监督、协调成员国合规行动、并为行业垂直监管与标准互操作提供指导与支持
执行主体	成员国	包括依据GDPR开展数据保护的成员国数据保护机构（DPAs）和依据AI ACT设立的国家主管机构（NCAs）监督AI系统合规；此外还有专门设立的AI监管机构（如西班牙AESIA）负责专项治理，以及行业垂直监管部门执行各自领域细则，共同推进人工智能数据治理的实施与协调
利益主体	行业组织、学术界、社会公民等多方	包括行业组织、学术界和公民社会组织，通过制定最佳实践与技术标准、开展前沿研究和伦理审查，以及代表公众利益的监督与反馈，以多方协同的方式补充公共治理，提升人工智能数据治理的专业性、可操作性与社会信任