图书情报知识 ›› 2026, Vol. 43 ›› Issue (2): 119-130.doi: 10.13366/j.dik.2026.02.119

• 情报、信息与共享 • 上一篇    下一篇

人工智能生成内容(AIGC)的监管与合规治理研究——基于多源流耦合分析

詹希旎1,2, 李白杨1,2, 张心源3, 裴雷2,4   

  1. 1.南京大学数据管理创新研究中心,苏州,215163;
    2.南京大学数据智能与交叉创新实验室,南京,210023;
    3.苏州大学社会学院,苏州,215000;
    4.南京大学信息管理学院,南京,210023
  • 出版日期:2026-03-10 发布日期:2026-05-21
  • 通讯作者: 李白杨(ORCID: 0000-0001-5490-373X),博士,准聘副教授,研究员,研究方向:数据智能、人工智能治理,Email: libaiyang@nju.edu.cn。
  • 作者简介:詹希旎(ORCID: 0000-0002-5194-4656),博士研究生,研究方向:数据智能,数字治理,Email: zhanxini@smail.nju.edu.cn;张心源(ORCID: 0000-0001-6084-6321),博士,副教授,研究方向:数字智能,信息计量与评价,Email: 442826407@qq.com;裴雷(ORCID: 0000-0003-4754-4112),博士,教授,研究方向:数字治理,政策智能计算,Email: plei@nju.edu.cn。
  • 基金资助:
    本文系国家自然科学基金青年项目“面向海外公共安全的事件画像与多源数据融合方法”(72004171)和教育部人文社科青年项目“全球数据主权博弈背景下健全我国数据跨境流动规则体系研究”(21YJC870019)的研究成果之一。

The Regulatory and Compliance Governance of Artificial Intelligence Generated Content: A Multi-source Flow Coupling Analysis

ZHAN Xini1,2, LI Baiyang1,2, ZHANG Xinyuan3, PEI Lei2,4   

  1. 1. Research Institute for Data Management & Innovation, Nanjing University, Suzhou, 215263;
    2. Laboratory of Data Intelligence and Interdisciplinary Innovation, Nanjing University, Nanjing, 210023;
    3. School of Social Science, Soochow University, Suzhou, 215000;
    4.School of Information Management, Nanjing University, Nanjing, 210023
  • Online:2026-03-10 Published:2026-05-21
  • Contact: Correspondence should be addressed to LI Baiyang, Email: libaiyang@nju.edu.cn, ORCID: 0000-0001-5490-373X
  • Supported by:
    This is an outcome of the Youth Project "Event Profiles and Multi-source Data Fusion Methods for Overseas Public Security"(72004171)supported by National Natural Science Foundation of China, and the Youth Project of Humanities and Social Sciences "Research on Improving China's Cross-border Data Flow Rules System under the Background of Global Data Sovereignty Game"(21YJC870019)supported by the Ministry of Education of China.

摘要: [目的/意义]探讨人智共生环境下影响人工智能生成内容(AIGC)有序发展的多源流要素和实践关联,为AIGC的监管与合规治理提供参考。[研究设计/方法]从多源流视角出发,结合多案例研究和事件路径分析法进行多级编码,利用风险要素调适问题源流、时机要素调适政策源流、势能与氛围要素调适政治源流,构建基于多源流耦合的AIGC监管与合规治理模型。[结论/发现]从实践反馈、政策介入时机、政治势能、国际竞合等方面分析多源流耦合,进一步提出了符合现代化监管情境和合规治理需求的提质策略。[创新/价值]结合多源流要素特征考察AIGC监管与合规治理的实践需求,有助于提升GenAI技术服务的实践效能,为AIGC高质量发展提供启示。

关键词: 人工智能生成内容(AIGC)监管, 多源流耦合, 要素调适, 合规治理, 国际竞合

Abstract: [Purpose/Significance] This paper aims to explore the multi-source flow elements and practice associations affecting the orderly development of Artificial Intelligence Generated Content(AIGC)in the human-intelligence symbiosis environment, thereby providing reference for the regulation and compliance governance of AIGC. [Design/Methodology] Starting from the perspective of multi-source flow, combining multi-case studies and event path analysis, this study carried out a multi-level coding. By using risk element to adjust the problematic source flow, timing element to adjust the policy source flow, and potential energy and atmosphere element to adjust the political source flow, we constructed a multi-source flow coupling model for AIGC regulatory and compliance governance. [Findings/Conclusion] The multi-source flow coupling is analyzed from the aspects of practice feedback, policy intervention timing, political potential energy, international competition and cooperation, leading to the proposal of quality enhancement strategy that meets the needs of modern regulatory context and the requirements of compliance governance. [Originality/Value] Examining the practice demands of AIGC's regulation and compliance governance in conjunction with multi-source flow elements characteristics can enhance the practice effectiveness of GenAI technical services and provide valuable insights for the high-quality development of AIGC.

Keywords: AIGC regulatory governance, Multi-source flow coupling, Elemental adaptation, Compliance governance, International competition and cooperation