Highlights
- Divergent national narratives produce discordant AI policies that hinder productive multilateral collaboration. This results in international governance frameworks insufficient to address the challenges posed by the technology.
- Dyadic case studies demonstrate how competing national narratives generate bilateral tensions that lead to systemic barriers for multilateral AI coordination.
- While national narrative literacy among policymakers remains the ideal, a pragmatic alternative to foster collaboration focuses on identifying narrow technical domains where functional needs create common ground.
Abstract
Artificial intelligence (AI) presents governance challenges that extend beyond national borders, demanding international cooperation to mitigate harms and coordinate safety standards. Concurrently, AI regulatory frameworks emerging from the United States (U.S.), China, and the European Union (EU) are developing along increasingly divergent paths, generating bilateral tensions that hinder multilateral collaboration. These policy divergences are not merely the product of competing economic interests or technical disagreements, but reflect deeper national narratives—collective stories rooted in history about a people’s identity and what they understand government’s role in technological development to be—that shape how each actor conceptualizes the benefits and harms of AI. Understanding AI policy divergence through a narrative lens reveals both the inefficiencies of current multilateral efforts and where latent points of convergence exist. An option for facilitating meaningful international AI cooperation involves designing diplomatic strategies that account for different narrative frameworks.