中文    English

Journal of library and information science in agriculture ›› 2025, Vol. 37 ›› Issue (4): 12-23.doi: 10.13998/j.cnki.issn1002-1248.25-0167

   

Generative AI Governance Practices in Europe and the United States and the Enlightenment for China

ZHANG Tao, LYU Qianhui   

  1. School of Information Management, Heilongjiang University, Harbin 150080
  • Received:2025-03-09 Online:2025-04-05 Published:2025-06-25

RichHTML

3

PDF (PC)

32

Abstract:

[Purpose/Significance] Generative artificial intelligence (GAI) is currently advancing at an astonishing pace. GAI has unleashed remarkable potential in various fields and is significantly fueling social and economic development. However, this rapid progress has also given rise to a plethora of complex issues, including but not limited to data security breaches, privacy violations, the spread of false information, and intellectual property infringements. Existing research primarily focuses on the governance of AI in general, leaving a gap in in-depth exploration of GAI. This study aims to fill this void by meticulously comparing the governance approaches of Europe and the United States in the realm of GAI. Through this comparison, the study aims to provide valuable insights for China to refine its own governance system. This is not only crucial for China's domestic technological development and social stability but also plays a pivotal role in promoting the harmonization of the global governance framework for GAI. [Method/Process] This research adopts a multi-faceted approach. It commences with a comprehensive review of relevant literature, gathering insights from a wide range of academic sources to understand the current state-of-the-art in GAI governance in Europe and the United States. Additionally, it deploys the case-study method, examining real-world examples such as the development of OpenAI's GPT series in the US and the implementation of the EU's AI Act. By analyzing these cases, it can vividly illustrate the practical implications and impacts of different governance strategies, thus enabling a more in-depth and accurate comparison. [Results/Conclusions] We found that the European Union adopts a regulatory path centered on data protection and ensures the fairness and sustainability of technological development through a strict legal framework. However, this strong regulatory model may stifle innovation vitality to some extent. The United States adopts a governance model oriented towards market accountability, emphasizing technological innovation leadership and free development. It stimulates market vitality through industry self-discipline and flexible regulation, but there is a hidden danger of insufficient ethical risk control. Based on these findings, this paper recommends that China adopt a balanced approach. China should integrate elements of both the U.S. and E.U. models to foster innovation while ensuring ethical and legal compliance. Future research could explore ways to adapt these governance models to emerging trends such as integrating GAI with other emerging technologies and addressing the unique governance challenges posed by cross-border data flows.

Key words: generative AI, governance practice, comparison between Europe and the United State, AI governance, AI ethics

CLC Number: 

  • G203

Table 1

Regulations and policies on generative artificial intelligence in Europe and the United States"

区域 名称 颁布时间 颁布机构 内容
欧盟 《通用数据保护条例》[24] 2018年5月 欧盟委员会 明确数据主体权利，强化监管与处罚措施，来加强对欧盟公民个人数据的保护
《可信赖人工智能的伦理准则》[25] 2019年4月 欧盟委员会 提出可信赖的人工智能需合法、合伦理且稳健，应满足人类能动性与监督、技术稳健性与安全性、隐私与数据治理、透明度、多样性与非歧视性及公平性、社会与环境福祉、可问责性等关键要求
《人工智能法案》[26] 2024年6月 欧盟委员会 基于风险识别分析的方法，对不同类型的人工智能系统分级并提出不同要求和义务，同时明确管辖范围、倡导负责任创新、建立严格执行机制和惩罚措施
美国 《国家人工智能研究与发展战略计划》[27] 2023年5月 美国白宫科技政策办公室 明确了人工智能领域的主要研发挑战，它将确保美国在开发和使用可信赖的人工智能系统方面继续处于领导地位
《关于安全、可靠、可信开发和使用人工智能的行政命令》[28] 2023年10月 总统拜登 确立了人工智能监管的总体原则。该行政命令下关于对消费者健康和安全、敏感信息隐私（健康、财务、身份认证、生物识别等）以及就业等高风险领域的人工智能开展更严格的监管规定，可影响未来AIGC的监管
《确保肖像、声音和图像安全法案》[29] 2024年3月 美国田纳西州众议院通过第2091号法案 该法案系全美首个针对AIGC音乐创作的监管法案
《人工智能训练数据与版权保护平衡》[30] 2025年2月 美国加州议会通过第412号法案 首次以州立法形式明确人工智能训练数据版权披露的“时间红线”，并通过民事救济强化执行力

《人工智能披露法案》[31]

《真实政治广告法案》[32]

《人工智能标签法案》[33]

 2023年9月 美国参议员提议 提出要求人工智能生成内容需要附带水印
《深度伪造问责法案》[34] 2023年9月 美国众议员提议 对未经许可的深度伪造行为作出了惩罚规定
《保护消费者免受欺骗性人工智能法案》[35] 2024年3月 美国众议员提议 要求生成式人工智能应用提供者确保其应用创建或修改的音频、视觉内容包括机器可读的披露信息，且明确指出内容是由生成式人工智能创建的
《人工智能公众意识和教育运动法案》[36] 2024年6月 美国参议员提议 检测和区分由人类生成和由算法生成或显著修改的数字媒体，包括通常称为“深度伪造”和由程序（如“聊天机器人”）生成的内容
1
张熙, 杨小汕, 徐常胜. ChatGPT及生成式人工智能现状及未来发展方向[J]. 中国科学基金, 2023, 37(5): 743-750.
ZHANG X, YANG X S, XU C S. Current state and future development directions of ChatGPT and generative artificial intelligence[J]. Bulletin of national natural science foundation of China, 2023, 37(5): 743-750.
2
王文, 申宇婧, 金臻. 大跳跃: 美国智库论DeepSeek中国人工智能[J]. 智库理论与实践, 2025, 10(2): 1-11.
WANG W, SHEN Y J, JIN Z. A major breakthrough: U.S. think tanks on DeepSeek and China's artificial intelligence[J]. Think tank: Theory & practice, 2025, 10(2): 1-11.
3
郭小东. 生成式人工智能的风险及其包容性法律治理[J]. 北京理工大学学报(社会科学版), 2023, 25(6): 93-105, 117.
GUO X D. Risks of generative artificial intelligence and its inclusive legal governance[J]. Journal of Beijing institute of technology (social sciences edition), 2023, 25(6): 93-105, 117.
4
罗梓超, 李荣, 刘如, 等. 预见性情报视角下生成式人工智能安全风险感知实践探究[J]. 情报理论与实践, 2025, 48(4): 64-71.
LUO Z C, LI R, LIU R, et al. Exploring the generative AI security risk perception framework from the perspective of predictive intelligence[J]. Information studies: Theory & application, 2025, 48(4): 64-71.
5
BURRELL J, FOURCADE M. The society of algorithms[J]. Annual review of sociology, 2021, 47: 213-237.
6
程乐. 生成式人工智能治理的态势、挑战与展望[J]. 人民论坛, 2024(2): 76-81.
CHENG L. Situation, challenge and prospect of generative artificial intelligence governance[J]. People's tribune, 2024(2): 76-81.
7
吴艳, 刘腾龙. 欧盟人工智能安全治理的路径与前景[J]. 湖北社会科学, 2024(12): 32-41.
WU Y, LIU T L. Pathways and prospects for artificial intelligence security governance in the EU[J]. Hubei social sciences, 2024(12): 32-41.
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
陈蔓芩, 代天钰. 欧盟生成式人工智能监管制度及其启示[J]. 重庆开放大学学报, 2024, 36(5): 57-64.
CHEN M Q, DAI T Y. The EU's regulatory system for generative artificial intelligence and its implications[J]. Journal of Chongqing open university, 2024, 36(5): 57-64.
10
崔文波, 张涛, 马海群, 等. 欧盟数据与算法安全治理: 特征与启示[J]. 信息资源管理学报, 2023, 13(2): 30-41.
CUI W B, ZHANG T, MA H Q, et al. Data and algorithm security governance in the European union: Characteristics and implications[J]. Journal of information resources management, 2023, 13(2): 30-41.
11
ARORA A S, SABOIA L, ARORA A, et al. Human-centric versus state-driven: A comparative analysis of the European union's and China's artificial intelligence governance using risk management[J]. International journal of intelligent information technologies, 2025, 21(1): 1-13.
12
陈亮, 张翔. 欧盟生成式人工智能立法实践及镜鉴[J]. 法治研究, 2024(6): 105-118.
CHEN L, ZHANG X. Legislative practice of generative artificial intelligence in EU and its implication[J]. Research on rule of law, 2024(6): 105-118.
13
郭梦迎, 张薇薇. 欧盟人工智能发展与治理面临的机遇和挑战[J]. 和平与发展, 2024(5): 50-76, 180-181.
GUO M Y, ZHANG W W. The opportunities and challenges faced with the development and governance of artificial intelligence in the European union[J]. Peace and development, 2024(5): 50-76, 180-181.
14
AGUILAR-ANTONIO J M. Path and governance model of artificial intelligence (AI) policies in north American countries[J]. Justicia, 2024, 29(45): 1017081.
15
LAW T, MCCALL L. Artificial intelligence policymaking: An agenda for sociological research[J]. Socius: Sociological research for a dynamic world, 2024, 10: 23780231241261596.
16
马海群, 蔡庆平, 崔文波, 等. 美国数据与算法安全治理: 进路、特征与启示[J]. 信息资源管理学报, 2023, 13(1): 52-64.
MA H Q, CAI Q P, CUI W B, et al. Data and algorithm security governance in the United States: Approaches, characteristics and enlightenments[J]. Journal of information resources management, 2023, 13(1): 52-64.
17
Copyright Office US. Copyright registration guidance: Works containing material generated by artificial intelligence[EB/OL]. [2023-03-16].
18
李颖, 李骄阳. 美国联邦政府内部部署人工智能的风险治理体系解析及其启示[J/OL]. 现代情报, 2025: 1-20.
LI Y, LI J Y. Deconstruction of the risk management system for deploying artificial intelligence within the US federal government and its implications[J/OL]. Journal of modern information, 2025: 1-20.
19
赵悦. 如何监管生成式人工智能在科学研究中的应用: 风险与策略: 基于欧盟和美国人工智能政策的分析[J]. 现代远程教育研究, 2024, 36(6): 20-29.
ZHAO Y. How to regulate the application of generative artificial intelligence in scientific research: Risks and strategies: Based on an analysis of EU and U.S. AI policies[J]. Modern distance education research, 2024, 36(6): 20-29.
20
王彦雨, 李正风, 高芳. 欧美人工智能治理模式比较研究[J]. 科学学研究, 2024, 42(3): 460-468, 491.
WANG Y Y, LI Z F, GAO F. A comparative study of European and American AI governance models[J]. Studies in science of science, 2024, 42(3): 460-468, 491.
21
迈克尔·维尔, 基拉·马图斯, 罗伯特·戈尔瓦, 等. 人工智能与全球治理: 模式、理据和紧张关系[J]. 俄罗斯学刊, 2024, 14(3): 49-72.
MICHAEL V, KIRA M, ROBERT G, et al. AI and global governance: Modalities, rationales, tensions[J]. Academic journal of Russian studies, 2024, 14(3): 49-72.
22
王怡青, 杨梦倩, 杨瑛瑛. 美欧人工智能监管动向及启示[J]. 通信世界, 2024(13): 33-35.
WANG Y Q, YANG M Q, YANG Y Y. Supervision trend of artificial intelligence in America and Europe and its enlightenment[J]. Communications world, 2024(13): 33-35.
23
梁正, 王净宇. 美、欧人工智能治理的分歧、影响及其对中国的启示[J]. 湖北社会科学, 2024(12): 42-50.
LIANG Z, WANG J Y. Divergences, impacts and implications of US and EU AI governance for China[J]. Hubei social sciences, 2024(12): 42-50.
24
Commission European. General data protection regulation[EB/OL]. [2016-05-24].
25
High-Level Expert Group on AI. Ethics guidelines for trustworthy AI[EB/OL]. [2019-04-08].
26
Commission European. Proposal for a regulation on artificial intelligence (AI Act)[EB/OL]. [2021-04-21].
27
The White House. National artificial intelligence research and development strategic plan[EB/OL]. [2023-05-23].
28
The White House. Executive order on safe, secure, and trustworthy artificial intelligence[EB/OL]. [2023-10-23].
29
Congress U.S.. No AI FRAUD act (H.R. 6943)[EB/OL]. [2024-03-21].
30
Copyright Office U.S.. Copyright and artificial intelligence[EB/OL]. [2023-03-16].
31
Senate U.S.. AI disclosure act of 2023 (S. 2691)[EB/OL]. [2023-07-05].
32
House U.S.. REAL political ads act (H.R. 3044)[EB/OL]. [2024-04-09].
33
Senate U.S.. AI labeling act (S. 2691)[EB/OL]. [2023-11-27].
34
House U.S.. DEEPFAKES accountability act (H.R. 3230)[EB/OL]. [2019-06-12].
35
Federal Trade Commission. Protecting consumers from deceptive AI[EB/OL]. [2024-03-21].
36
Congress U.S.. AI literacy act (H.R. 6791)[EB/OL]. [2023-12-14].
37
俞可平. 全球治理引论[J]. 马克思主义与现实, 2002(1): 20-32.
YU K P. Introduction to global governance[J]. Marxism & reality, 2002(1): 20-32.
38
曾雄, 梁正, 张辉. 欧美算法治理实践的新发展与我国算法综合治理框架的构建[J]. 电子政务, 2022(7): 67-75.
ZENG X, LIANG Z, ZHANG H. The new development of algorithm governance practice in Europe and America and the construction of algorithm comprehensive governance framework in China[J]. E-Government, 2022(7): 67-75.
39
VULETIĆ D. High risk artificial intelligence systems and legal doctrine of essential facilities: In search for a dynamic model[J]. Interdisciplinary description of complex systems, 2025, 23(1): 72-81.
40
陈永伟. 超越ChatGPT: 生成式AI的机遇、风险与挑战[J]. 山东大学学报(哲学社会科学版), 2023(3): 127-143.
CHEN Y W. Beyond ChatGPT: Opportunities, risks, and challenges from generative AI[J]. Journal of Shandong University (philosophy and social sciences), 2023(3): 127-143.
41
李默, 杨彬. 从生成式人工智能到通用人工智能: 赋能图书馆知识服务模式创新[J]. 农业图书情报学报, 2024, 36(6): 50-61.
LI M, YANG B. From generative artificial intelligence to artificial general intelligence: Enabling innovation models in library knowledge services[J]. Journal of library and information science in agriculture, 2024, 36(6): 50-61.
42
李蒙. 美国联邦贸易委员会隐私和数据安全领域行政执法和解研究[D]. 上海: 上海交通大学, 2022.
LI M. Research on the administrative law enforcement settlement of the US federal trade commission in the field of privacy and data security[D]. Shanghai: Shanghai Jiao Tong University, 2022.
43
周巧. 欧盟《人工智能法》监管沙盒制度及启示[J]. 科技创业月刊, 2025, 38(1): 157-162.
ZHOU Q. The regulatory sandbox system of the EU artificial intelligence act and its implications[J]. Journal of entrepreneurship in science & technology, 2025, 38(1): 157-162.
44
Legislature California. AB-311 genAI accountability act[EB/OL]. [2024-01-01].
45
NATALI H, NICHOLAS D. ChatGPT and the AI act[J]. Internet policy review, 2023, 12(1): 28-28.
46
严少华, 杨昭. 欧美人工智能治理模式比较及启示[J]. 战略决策研究, 2024, 15(3): 41-65, 110-111.
YAN S H, YANG Z. Comparison of artificial intelligence governance model between the EU and the US[J]. Journal of strategy and decision-making, 2024, 15(3): 41-65, 110-111.
47
徐明. 生成式人工智能大模型的安全挑战与治理路径研究[J]. 信息通信技术与政策, 2025(1): 10-19.
XU M. Research on security challenges and governance path of generative artificial intelligence big model[J]. Information and communications technology and policy, 2025(1): 10-19.
48
马海群, 李金玲, 于同同, 等. 全生命周期视阈下公共数据伦理准则框架研究[J]. 农业图书情报学报, 2023, 35(6): 29-42.
MA H Q, LI J L, YU T T, et al. A framework of ethics guidelines on public data from a whole life cycle perspective[J]. Journal of library and information science in agriculture, 2023, 35(6): 29-42.
[1] LUO Guofeng, YI Tong, YAN Zhouzhou. Critical Information Literacy Education in University Libraries from the Perspective of AIGC Application [J]. Journal of library and information science in agriculture, 2025, 37(1): 47-58.
[2] Fan YUAN, Jia LI. Opportunities, Challenges, and Future Directions for Generative Artificial Intelligence in Library Information Literacy Education: A Scoping Review [J]. Journal of library and information science in agriculture, 2024, 36(9): 44-57.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Editorial Board of Journal of library and information science in agriculture
Tel：(010)82109667　Fax：(010)82109667　E-mail：xuekan＠caas.cn
Powered by Beijing Magtech Co., Ltd.
知识共享许可协议