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.