Research on Copyright Definition and Ethical Norms of Creative Content in Generative Artificial Intelligence

Abstract

With the rapid advancement of generative artificial intelligence technology, the extensive application of its generated content in literary, artistic, and scientific fields has posed profound challenges to existing copyright systems and ethical norms. This paper conducts a systematic study on the copyright definition and ethical norms of generative AI-created content. It begins by theoretically analyzing whether AI-generated content meets the originality requirements under copyright law, examines the ownership of rights under different subject models, and thereby reveals the impact on traditional author-centric theories. Furthermore, this paper analyzes the divergences in the judicial recognition of AI-generated content, the legality of training data sources and associated infringement risks, as well as the ambiguity of rights attribution under current legal frameworks. It proposes comprehensive solutions combining legal interpretation expansion, institutional innovation, and technological governance. On the ethical front, this paper examines risks related to the lack of transparency, algorithmic bias, and the erosion of cultural diversity in generative AI, and constructs a collaborative governance framework encompassing technical standards, industry self-regulation, and social supervision, aiming to provide theoretical support for the improvement of relevant laws and ethical development.