Documentation, Informaiton & Knowledge ›› 2023, Vol. 40 ›› Issue (4): 41-51.doi: 10.13366/j.dik.2023.04.041

• Academic Focus(1):Artificial Intelligence Generated Content (AIGC)Governance • Previous Articles     Next Articles

Generative Artificial Intelligence Governance Action Framework:Content Analysis Based on AIGC Incident Report Texts

ZHU Yu1, CHEN Guanze2, LU Yongrong3, FAN Wei4   

  1. 1. School of Information Management, Nanjing University, Nanjing, 210023;
    2. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, 999077;
    3. Pittsburgh Institute, Sichuan University, Chengdu, 610207;
    4. Sichuan University Library, Chengdu, 610065
  • Online:2023-07-10 Published:2023-08-16
  • Contact: Correspondence should be addressed to ZHU Yu, Email:, ORCID:0000-0002-2548-828X

Abstract: [Purpose/Significance] The breakthrough of Generative Artificial Intelligence(Generative AI)has led to the explosive growth of Artificial Intelligence Generated Content(AIGC), which inevitably cause people to be negatively affected by information overload, information noise, information security, and other related issues, making social information governance face new challenges. This paper aims to analyze and discuss the characteristic attributes of AIGC incidents, so as to provide a reference for Generative AI governance in China. [Design/Methodology] Based on AI Incident Database(AIID)and taking AIGC-related incident reports as samples for content analysis, the types, causes, damage objects and countermeasures of existing AIGC incidents were discussed. [Findings/Conclusion] The diversity of the objects affected by AIGC incidents, the wide distribution of the scope, and the complex unknown of the potential harm, result in the resources and capabilities of any single actor not being able to effectively deal with the crisis. It is necessary for actors of government, enterprises and society to form a governance participation model of "diversity + coordination + checks and balances", and to carry out information governance under the action framework of "context-consciousness-action". [Originality/Value] This paper introduces AIID as a case source database, provides an intuitive demonstration of the relevant details of existing AIGC incidents and forms a three-level category framework for AIGC incident analysis through content analysis.The action frame of Generative AI governance formed in this study is helpful to promote the exploration and practice of Generative AI governance from a macro perspective.

Key words: Generative artificial intelligence, Artificial Intelligence Generated Content(AIGC), Information governance, Action framework, Content analysis