Department of Industrial Engineering & Decision Analytics [IEDA Seminar]     - Generative AI and Copyright: A Dynamic Perspective

10:30am - 11:30am

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 compensation to creators whose content has been used to train generative AI models (the fair use standard); and 2) the eligibility of AI-generated content for copyright protection (AI-copyrightability). 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. By constructing a dynamic model with endogenous content creation and AI model development, we unravel the impacts of the fair use standard and AI-copyrightability on AI development, AI company profit, creators income, and consumer welfare, and how these impacts are influenced by various economic and operational factors. For example, while generous fair use (use data for AI training without compensating the creator) benefits all parties when abundant training data exists, it can hurt creators and consumers when such data is scarce. Similarly, stronger AI-copyrightability (AI content enjoys more copyright protection) could hinder AI development and reduce social welfare. Our analysis also highlights the complex interplay between these two copyright issues. For instance, when existing training data is scarce, generous fair use may be preferred only when AI-copyrightability is weak. Our findings underscore the need for policymakers to embrace a dynamic, context-specific approach in making regulatory decisions and provide insights for business leaders navigating the complexities of the global regulatory environment.

Link to paper: 

Event Format
Speakers / Performers:
Prof. Alex YANG
Professor of Management Science and Operations, London Business School (LBS)

S. Alex Yang is a Professor of Management Science and Operations at London Business School. Alex holds a PhD and an MBA from the University of Chicago Booth School of Business, an MS from Northwestern University, and a BS from Tsinghua University. Focusing on inter-disciplinary topics spanning over operations, finance, and technology, Alex’s research has appeared in academic journals such as Management Science, M&SOM, and Journal of Financial Economics, and has received several best paper awards. Alex has taught on the MBA, EMBA, and executive education programmes in universities and business schools around the world. Beyond research and teaching, Alex has working and consulting experience in banks, Fintech and technology companies, hedge funds, airlines, and international organizations.

Recommended For
Faculty and staff
PG students
Department of Industrial Engineering & Decision Analytics
Department of Information Systems, Business Statistics & Operations Management
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