Copyright Judicial Protection of Generative AI-Generated Content from a Human-Machine Collaboration Perspective

Abstract

The large-scale application of generative artificial intelligence (AI) has profoundly reshaped the production methods of digital content. Human-machine collaborative creation has become the new normal in the content industry. However, the existing copyright system, with its rules centered on natural person creation, faces systemic applicability challenges in AIGC scenarios. This paper takes human-machine collaboration as its analytical perspective, focusing on four core issues in the judicial protection of AIGC copyright: the determination of copyrightability, the rules of attribution of rights, the division of infringement liability, and the definition of platform due diligence obligations . Through empirical analysis and theoretical deconstruction of typical domestic and international judicial cases, it reveals the consensus and rule gaps in current judicial practice. The study finds that China's judicial practice has initially formed a standard for determining copyrightability based on "substantial human intellectual input + original expression," but significant differences remain in the criteria for judging originality, the rules of attribution of rights, and the boundaries of platform liability. This paper proposes that a "typological" determination standard centered on human creative contribution should be established, a hierarchical system of rules of attribution of rights and a dynamic system of platform due diligence obligations should be constructed, and a case guidance system should be used to promote the unification of judicial standards, so as to achieve a dynamic balance between technological innovation and copyright protection.