Generative AI and Copyright: A Dynamic Perspective

Abstract

The rapid advancement of generative AI is poised to disrupt the creative industry. Amidst the immense excitement for this new technology, its future development and applications in the creative industry hinge crucially upon two copyright issues: 1) the eligibility of AI-generated content for copyright protection (AI- copyrightability); 2) the compensation to creators whose content has been used to train generative AI models (fair use standard). While both issues have ignited heated debates among academics and practitioners, most analysis has focused on their challenges posed to existing copyright doctrines. In this paper, we aim to better understand the economic implications of these two regulatory issues and their interactions between each other. By constructing a dynamic game-theoretical model with endogenous content creation and generative AI-model development, we unravel the direct and indirect impacts of fair use standards and AI- copyrightability on AI development, the profits of the AI company and consumer welfare. We also examine how these impacts are influenced by various economic and operational factors such as data availability and AI model quality. Our findings provide crucial insights for business leaders navigating the complexities of the global regulatory environment and underscore the need for policymakers to embrace a dynamic, context-specific approach in making regulatory decisions.