Aiming for AI Interoperability: Challenges and Opportunities

TL;DR

This paper discusses the challenges and opportunities in achieving AI interoperability, emphasizing the need for harmonized technical and regulatory standards amid rapid global AI governance developments.

Contribution

It highlights the current fragmentation in AI regulation and technical standards, and explores strategies to enhance interoperability across jurisdictions and sectors.

Findings

Rapid proliferation of AI laws and policies causes fragmentation.

Technical interoperability enables AI systems to function together effectively.

Regulatory interoperability ensures consistent AI governance across regions.

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.