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Bridging the Artificial Intelligence Governance Gap: The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence
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This RAND policy brief compares U.S. and Chinese approaches to governing general-purpose AI systems, identifying key divergences relevant to international AI safety cooperation and global governance efforts.
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Summary
This RAND expert insights paper analyzes divergences between U.S. and Chinese AI governance frameworks, focusing on domestic regulation focus, key regulatory principles, and international governance approaches. It highlights that cooperation between the two nations may be necessary to address global safety and security risks posed by general-purpose AI systems. Understanding these differences is framed as essential for advancing international AI safety cooperation.
Key Points
- •The U.S. and China diverge in three key areas: focus of domestic AI regulation, regulatory principles, and approaches to international AI governance.
- •Both nations seek leadership in global AI governance, creating both competitive and cooperative dynamics.
- •General-purpose AI (GPAI) systems are identified as posing global safety and security challenges requiring international attention.
- •U.S.-China cooperation on AI safety may be necessary despite geopolitical tensions and governance divergences.
- •Understanding regulatory differences is a prerequisite for meaningful international AI safety and security collaboration.
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PE-A3703-1
Bridging the Artificial Intelligence Governance Gap
The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence
Oliver Guest, Kevin Wei
Expert InsightsPublished Dec 13, 2024
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The United States and China are among the world's top players in the development of advanced artificial intelligence (AI) systems, and both are keen to lead in global AI governance and development. A look at U.S. and Chinese policy landscapes reveals differences in how the two countries approach the governance of general-purpose artificial intelligence (GPAI) systems. Three areas of divergence are notable for policymakers: the focus of domestic AI regulation, key principles of domestic AI regulation, and approaches to implementing international AI governance. As AI develo
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