Copyright Governance of User-Generated Content in Generative AI Driven Games

Abstract

As generative AI becomes embedded in user-generated content (UGC) game ecosystems, creative output increasingly arises from human–AI collaboration rather than purely manual construction. This study examines how the game industry’s “private legislation” reallocates copyright interests in AI-based UGC products, and whether such reallocations conflict with copyright’s incentive-and-balance rationale or become vulnerable in enforceability across jurisdictions. Using a mixed-methods design, the study (i) applies clause-level textual coding to standard-form contracts from eight representative products spanning AI-based UGC games, creation platforms, developer tools, and general tools, and (ii) conducts a comparative analysis of recent U.S. and Chinese judicial approaches to authorship and originality. The results suggest that strict U.S. human-authorship centrism and China’s contribution-sensitive reasoning can yield different validity boundaries for identical platform terms. Finally, the study proposes a modular, tiered rights-recognition mechanism grounded in observable “human contribution” supported by auditable logs and metadata, to improve incentive alignment and compliance in AI-based UGC games.