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Journal of library and information science in agriculture

   

Layout and Characteristics of European AI Data Governance Policy

DONG Ke1,2,3, SONG Yuchen1, WU Jiachun1   

  1. 1. Research Institute for Data Management Innovation, Nanjing University, Suzhou 215163
    2. Laboratory of Data intelligence and Interdisciplinary Innovation, Nanjing University, Nanjing 210046
    3. Nanjing University Library, Nanjing 210023
  • Received:2025-06-09 Online:2025-09-08

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

CLC Number: 

  • G350

Fig.1

Research framework"

Table 1

Sample core policy document on AI data governance in the EU"

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

Fig.2

Map of the development of AI data governance policy in Europe"

Fig.3

The governing body of European AI data governance"

Table 2

Primary responsibilities of the EU’s AI data governance bodies"

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
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
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
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