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Volume 58 Issue 2
February 2026
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Citation: CAO Bo. The Systemic Conflict and Coordination Paths of AIGC Copyright Protection and Knowledge Production[J]. Academic Monthly, 2026, 58(2): 99-110. shu

The Systemic Conflict and Coordination Paths of AIGC Copyright Protection and Knowledge Production

  • In the pre-AI era,copyright law and knowledge production were intertwined in a three-part harmony: protecting rights to fuel innovation,limiting rights to preserve free flow of ideas,and neighboring rights to facilitate stable knowledge sharing.Chinese courts are increasingly ruling in favor of copyright protection for AI-generated content (AIGC),while scholars keep building theoretical justifications for this approach.But awarding copyrights to AIGC could disrupt this delicate balance—distorting innovation incentives,shrinking intellectual commons,and destabilizing knowledge-sharing channels.Worse still,AIGC copyrights clash with knowledge production's core values: they might compromise accuracy in natural science,reduce diversity in social sciences,and constrain creativity in arts and humanities.To reconcile this clash,we propose three copyright system upgrades: First,establish a compensation mechanism for knowledge producers in the training data of large language models.Second,clarify that selected and arranged AIGC-generated compilations can receive copyright protection.Third,set up a statutory licensing system for such compilations.
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    1. [1]

      WAN Yong ,  LI Yalan . Realizing the Function of Copyright Law in the Era of Artificial Intelligence. Academic Monthly, 2026, 58(7): 104-116.

    2. [2]

      WANG Qian . AI-Generated Content and Copyright Liability: Paradoxes and Resolutions. Academic Monthly, 2026, 58(8): 118-132.

    3. [3]

      YOU Yang . How Does AI Understand Language Meaning. Academic Monthly, 2026, 58(8): 16-28.

    4. [4]

      HE Da'an ,  LI Huaizheng . Digital Adjustment Mechanism in the Application of Artificial General Intelligence. Academic Monthly, 2026, 58(7): 54-63.

    5. [5]

      LIN Xifen ,  FU Zhangyi . How Does Public Trust in the Judiciary Shape Acceptability of Judges' AI-assisted Adjudications——An Empirical Study Based on Questionnaire Data. Academic Monthly, 2026, 58(8): 133-144.

    6. [6]

      ZHANG Yi . Cognitive Transformation in Historical Research in the Age of AI——“Fluency-Induced Occlusion” in LLM-Assisted Reading of Diplomatic Manuscripts. Academic Monthly, 2026, 58(8): 29-40.

    7. [7]

      XIE Yue . How State Capacity Is Generated in Practice——A Dynamic Equilibrium Model of Governance. Academic Monthly, 2026, 58(8): 106-117.

    8. [8]

      XU Xiangdong . Consciousness and The Moral Status of AI Agents. Academic Monthly, 2026, 58(8): 5-15.

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        The Systemic Conflict and Coordination Paths of AIGC Copyright Protection and Knowledge Production

        Abstract: In the pre-AI era,copyright law and knowledge production were intertwined in a three-part harmony: protecting rights to fuel innovation,limiting rights to preserve free flow of ideas,and neighboring rights to facilitate stable knowledge sharing.Chinese courts are increasingly ruling in favor of copyright protection for AI-generated content (AIGC),while scholars keep building theoretical justifications for this approach.But awarding copyrights to AIGC could disrupt this delicate balance—distorting innovation incentives,shrinking intellectual commons,and destabilizing knowledge-sharing channels.Worse still,AIGC copyrights clash with knowledge production's core values: they might compromise accuracy in natural science,reduce diversity in social sciences,and constrain creativity in arts and humanities.To reconcile this clash,we propose three copyright system upgrades: First,establish a compensation mechanism for knowledge producers in the training data of large language models.Second,clarify that selected and arranged AIGC-generated compilations can receive copyright protection.Third,set up a statutory licensing system for such compilations.

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