JOURNAL ARTICLE

China's regulations on the attribution of AI-generated content: an exploration based on the open-ended approach.

  • Published In: Journal of Intellectual Property Law & Practice, 2025, v. 20, n. 5. P. 318 1 of 3

  • Database: Legal Source 2 of 3

  • Authored By: He, Xinhang; Shan, Pingji 3 of 3

Abstract

This article focuses on the challenges and legal considerations surrounding copyright ownership of AI-generated content under China’s current copyright law, particularly following the 2020 amendment that introduced an open-ended classification system including a catch-all provision for new types of works. It analyzes judicial cases revealing inconsistencies in courts’ assessments of originality and human intellectual contribution in AI-generated works, highlighting the broad discretion judges currently exercise. The article recommends legislative clarification by establishing a “priority application for traditional work categories” principle, issuing judicial interpretations to define AI’s instrumental role as a creative tool, and advocating for cautious, substantive judicial evaluation to balance innovation with copyright protection. These measures aim to provide clearer legal guidance for intellectual property practitioners and support the sustainable development of China’s AI and creative industries.

Additional Information

  • Source:Journal of Intellectual Property Law & Practice. 2025/05, Vol. 20, Issue 5, p318
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2025
  • ISSN:17471532
  • DOI:10.1093/jiplp/jpae109
  • Accession Number:187729254
  • Copyright Statement:Copyright of Journal of Intellectual Property Law & Practice is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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