🤖 AI Summary
This study addresses the accelerating fragmentation of global AI governance, which exacerbates the divergence between technological development and regulatory frameworks, thereby impeding systemic interoperability and cross-jurisdictional compliance. To tackle this challenge, the work proposes a “technology–regulation dual interoperability” framework, systematically analyzing the root causes and interaction mechanisms underlying governance fragmentation through policy analysis, cross-jurisdictional comparison, and evaluation of standardization systems. The research reveals a trend of rapid yet dispersed growth in AI governance initiatives, identifies critical barriers to coordination, and offers strategic pathways and practical recommendations for fostering a compatible and coherent global AI governance ecosystem.
📝 Abstract
The Aiming for AI Interoperability report investigates the ongoing challenge of achieving regulatory and technical AI interoperability as national and global AI governance efforts are proliferating. Here, technical interoperability is the ability of AI systems and networks to function together, and regulatory interoperability is the consistency and overlap of rules across jurisdictions and sectors. This report observes an accelerating trend that many governments, standard-setting bodies, and private firms are drafting, implementing, or passing new AI laws, policies, and frameworks at a staggering pace, resulting in fragmentation and confusion for both private and public sector actors.