Reconstruction of Digital Cultural Property Value Chain Driven by AIGC Technology:Theoretical Construction and Governance Path Exploration
Jin Hui1,2, Zhang Yuqing1,2
1. College of Politics and Public Administration, Qingdao University, Qingdao 266071, China; 2. Intellectual Property Research Institute, Qingdao University, Qingdao 266071, China
Abstract：The breakthrough development of artificial intelligence generated content (AIGC)technology is reconstructing the logic of digital cultural production,and it is also posing a systematic challenge to the intellectual property system rooted in the industrial civilization.In the production process,AIGC technology is dissolving the subjectivity of traditional creation via the tripartite interaction of “human-algorithm-data”,and it is also causing ownership alienation and labor value masking.In the circulation process,platform algorithms reconstruct the cultural power structure via invisible manipulation,and the cross-border rule vacuum exacerbates the risk of institutional arbitrage.In the consumption process,the liquidity dilemma of property ownership and algorithmic domination have resulted in the weakening of user rights and the standardization of cultural values.To address these challenges,based on the theory of digital innovation ecosystem,this article constructs a three-dimensional analysis framework of “technical architecture-institutional resilience-ecological resilience”to explore the deconstruction and reconstruction mechanisms of AIGC technology on the value chain of digital cultural property rights,and to reveal the paradigm overturning effects of AIGC technology on the intellectual property system.These studies can provide a systematic solution for cultural property governance in the digital age that combines theoretical innovation and practical value.
金辉, 张禹晴. AIGC技术驱动的数字文化产权价值链重构:理论建构与治理路径探究[J]. 中国科技论坛, 2026(1): 106-113.
Jin Hui, Zhang Yuqing. Reconstruction of Digital Cultural Property Value Chain Driven by AIGC Technology:Theoretical Construction and Governance Path Exploration. , 2026(1): 106-113.
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