New White Paper: Fair Use is a Pillar of U.S. Economic Competitiveness in the Age of Generative AI

Leading Professors Argue That Undermining Fair Use Could Cost the U.S. Its AI Advantage

Washington, D.C. (June 10, 2025)—The Data Catalyst Institute (DCI) today released a new white paper titled “The Economic Importance of Fair Use for the Development of Generative Artificial Intelligence. ” The paper offers the most comprehensive economic analysis to date of how fair use in U.S. copyright law enables generative AI (GenAI) innovation, investment, and economic growth.

Authored by three professors whose expertise spans business, economics, and law—Cameron Miller, Christopher Sprigman, and Arun Sundararajan—the white paper synthesizes empirical research, industry case studies, and legal frameworks to evaluate the economic value of fair use in GenAI development. It presents a holistic case that narrowing or replacing the current U.S. fair use doctrine with more rigid frameworks would impose prohibitive costs, stifle innovation, and threaten U.S. technological leadership at a critical moment in global AI competition.

“Fair use has enabled some of America’s most important digital breakthroughs,” said Professor Miller of Syracuse University’s Whitman School of Management, “It lowers barriers to innovation, attracts investment, and drives economic growth. For generative AI, the flexibility of fair use is essential—without it, rigid alternatives could stifle productivity, startup formation, and long-term technological progress.”

Key findings of the white paper include:

• Generative AI is already producing measurable productivity and economic gains, including 20–40% efficiency improvements in professional services, major R&D returns in pharmaceuticals, and reduced costs across finance, healthcare, and retail. These gains are supported by real-world case studies, market data, and academic research.

• Fair use provides a flexible, innovation-friendly legal foundation for GenAI development by minimizing transaction costs and reducing legal uncertainty, especially compared to copyright licensing regimes, statutory exemptions, or expanded liability frameworks. This flexibility is rooted in decades of U.S. case law precedent recognizing transformative uses as protected fair use.

• Alternatives to fair use would introduce high economic inefficiencies, including complex compliance burdens and significant legal risk. The paper estimates that expanded liability frameworks could expose developers to damages ranging from $750 million to $150 billion per model, making development economically unviable for many firms.

The white paper argues that continued fair use protection for GenAI training is essential to preserving U.S. leadership in artificial intelligence and preventing a loss of long-term economic potential. At stake is not just domestic innovation, but global leadership. If fair use ceases to apply to GenAI, the report warns, the United States risks ceding technological and economic ground to foreign competitors—especially China, which is moving aggressively to expand its own AI capabilities under more permissive legal and industrial frameworks.

“This is fundamentally about U.S. competitiveness,” said Dr. Mark Drapeau of DCI, “If we hobble generative AI with legal uncertainty, others will fill the gap. But the stakes are not just legal—they are economic and geopolitical.”

About the Authors

Cameron Miller is Associate Professor of Management at the Martin J. Whitman School of Management, Syracuse University.

Christopher Sprigman is the Murray and Kathleen Bring Professor of Law and Co-Director of the Engelberg Center on Innovation Law and Policy at the NYU School of Law.

Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Director of the Fubon Center for Technology, Business and Innovation at the NYU Stern School of Business.

Read the Full White Paper

About the Data Catalyst Institute

The Data Catalyst Institute (DCI) is a research organization focused on how data and technology shape the modern economy. DCI explores how public policy affects innovation, competition, entrepreneurship, and economic opportunity. For more information, visit https://datacatalyst.org.

Support

This research was produced with support from the Computer and Communications Industry Association (CCIA).