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Navigating Copyright Risk and Governance Challenges in Artificial Intelligence Development: A Case Study From China

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  • Jian Liu
  • Liping Shen
  • Weihua Huang

Abstract

The advancement of artificial intelligence (AI) poses significant challenges regarding copyright risk and governance. This research seeks to examine the copyright risks and governance challenges associated with AI development in China. This research employed a convergent parallel mixed‐methods design, integrating structured surveys (n = 461) and semistructured interviews (n = 78) targeting AI developers, legal experts, regulators and copyright holders in China. China was selected as the focus of this study due to its rapid advancements in AI development, evolving regulatory landscape and growing global influence in shaping digital governance norms. Quantitative data were analysed using the Statistical Package for the Social Sciences (SPSS) software for descriptive and inferential statistics, while qualitative data underwent thematic analysis using NVivo software. The findings showed that AI‐powered copyright detection systems play an important role in ensuring fair compensation and protecting intellectual property rights. This study of copyright risk and governance challenges inherent in AI creation contributes novel insight by analysing collaborative governance (CG) in AI accessibility, AI copyright detection to ensure fair compensation for content creators, integrating copyright in responsible AI development and blockchain‐based copyright management. The study recommends that clear copyright regulations and CG mechanisms address the issues of AI creation and emphasize proactive measures to reduce risks, promote innovation and uphold ethical and responsible development in the evolving landscape of AI.

Suggested Citation

  • Jian Liu & Liping Shen & Weihua Huang, 2025. "Navigating Copyright Risk and Governance Challenges in Artificial Intelligence Development: A Case Study From China," Journal of International Development, John Wiley & Sons, Ltd., vol. 37(5), pages 1168-1193, July.
    • Handle: RePEc:wly:jintdv:v:37:y:2025:i:5:p:1168-1193
    DOI: 10.1002/jid.4007
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