中图分类号：D923.4文献标志码：ADOI:10.19358/j.issn.2097-1788.2026.06.011中文引用格式：龚旖.AIGC的版权激励困境与出路：一种法经济学的分析框架［J］.网络安全与数据治理，2026，45（6）：82-88. 英文引用格式：Gong Yi.Copyright incentive dilemma and approaches for AIGC:an analytical framework of law and economics［J］.Cyber Security and Data Governance，2026，45（6）：82-88.
Copyright incentive dilemma and approaches for AIGC: an analytical framework of law and economics
Gong Yi
School of Intellectual Property,Nanjing University of Science and Technology
Abstract： As a new type of object emerging from the development of modern technology,Artificial IntelligenceGenerated Content (AIGC) has led to a technological deconstruction of the definitions of "work" and "author" in traditional copyright systems.Current discussions on copyrightability and subject qualification predominantly focus on elemental analysis,often overlooking the negative externalities that cause incentive imbalances.Introducing the rational person model and transaction cost theory as tools for economic analysis of law can help achieve the goal of incentivizing copyright creation.Regarding the nature of works,copyright incentive measures adopted in legislation and judicial practices vary across countries.A costbenefit analysis supports the rationality and necessity of recognizing AIGC as works from an incentive logic perspective.In terms of subject qualification,artificial intelligence is still in its developmental infancy and lacks the foundation for ethical personhood.From the perspective of data governance practice,specific neighboring rights system designs—such as rights allocation and protection duration—should be proposed based on the distinction between rights and liability subjects and fictional creation subjects.Additionally,institutional suggestions such as granting AI the right to be identified as an author are put forward.At the same time,we should adhere to the principle of AI for good and seize the appropriate policy window period,in order to provide references for data governance in addressing the challenges posed by AIGC.
Key words : AI-generated content; copyrightability; legal subject; incentive theory
