Abstract Platform algorithms have significantly transformed traditional content moderation models, which historically depended primarily on human expertise. By leveraging artificial intelligence (AI) and advanced computational methods, platforms have substantially reduced the labour costs and operational demands associated with human review processes. Simultaneously, algorithmic enforcement tools are frequently promoted as potential solutions for addressing the inherent biases associated with human decision-making in content governance. Nevertheless, the risks associated with the algorithmic black box phenomenon highlight the urgent need to enhance transparency, platform liability and due process. Strengthening these mechanisms is critical to ensuring effective public oversight and regulatory scrutiny of automated content governance systems, particularly as AI moderation considerably influences the free flow of information and the safeguarding of user rights. This article examines the intersection of AI, copyright regulation and platform liability within the evolving digital content ecosystem. As AI-driven content moderation tools become prevalent, traditional regulatory frameworks are proving inadequate to address the complex challenges that arise. In light of recent legislative and judicial developments in the USA and the European Union, this article examines the implications of automated copyright enforcement and the application of the fair use doctrine, while also assessing the prospects for reforming existing platform liability regimes. Copyright issues arising from digital creation encompass multiple dimensions. At the intersection of technology and regulation, effective content moderation requires the integration of AI, algorithmic enforcement mechanisms and data-driven technologies to facilitate both technical analysis and normative judgement. This integration is essential for accurately delineating the scope and interpretation of safe harbour exemptions within existing copyright frameworks.
Chien-Chih Lu (Mon,) studied this question.
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