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Abstract

The rapid advancement of generative artificial intelligence (AI) poses significant challenges to traditional copyright frameworks, intensifying debates over the copyrightability of AI‐generated outputs. By comparing judicial practices in China and the United States, it has been observed that the United States maintains a conservative stance of adhering to substantive control, while China demonstrates an inclusive approach through the criterion of creative contribution. Building upon this, this article transcends the traditional binary judgment model and constructs a tiered copyright determination model. Based on the level of human control and contribution in the AI generation process, it introduces dimensions such as technological controllability and density of human intent, classifying generative AI into three tiers: strong protection, weak protection, and non‐protection. Regarding the copyrightability of content generated by generative AI, this article argues that the issue should be addressed within the framework of copyright law itself. When human participation is involved and the substantial contribution of the direct user is reflected in the AI‐generated content, meeting the requirements for copyrightable works under copyright law, corresponding protective measures should be granted.

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Business indexing term
Company / organization
Title
Tiered copyrightability for generative artificial intelligence: An empirical analysis of China and the United States judicial practices
Author
Xu, Zichun 1 ; Xu, Zhilang 2 

 School of Law and Intellectual Property, Sichuan University of Science and Engineering, Sichuan, China 
 School of Civil and Commercial Law, Southwest University of Political Science and Law, Chongqing, China 
Publication title
AI Magazine; La Canada
Volume
46
Issue
3
Number of pages
15
Publication year
2025
Publication date
Sep 1, 2025
Section
ARTICLE
Publisher
John Wiley & Sons, Inc.
Place of publication
La Canada
Country of publication
United States
ISSN
07384602
e-ISSN
23719621
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-08-22
Milestone dates
2025-07-22 (manuscriptRevised); 2025-08-22 (publishedOnlineFinalForm); 2025-07-22 (manuscriptReceived); 2025-07-29 (manuscriptAccepted)
Publication history
 
 
   First posting date
22 Aug 2025
ProQuest document ID
3251333244
Document URL
https://www.proquest.com/scholarly-journals/tiered-copyrightability-generative-artificial/docview/3251333244/se-2?accountid=208611
Copyright
© 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-11-07
Database
ProQuest One Academic