The United Nations University Institute in Macau has released a new policy report, Interoperability in AI Safety Governance: Ethics, Regulations, and Standards, offering critical recommendations to strengthen global AI safety frameworks through enhanced interoperability.
Drawing on country studies from China, South Korea, Singapore, and the United Kingdom, the report identifies effective tools and key barriers to interoperability in AI safety governance. It highlights practical ways to build a governance ecosystem that is globally informed yet locally grounded.
Interoperability is a cornerstone of AI governance—essential for reducing risks, fostering innovation, enhancing competitiveness, promoting standardization, and building public trust. Yet progress remains hindered by fragmented regulations, limited global coordination, and insufficient engagement from the Global South.
Focusing on autonomous vehicles, education, and cross‑border data flows, the report compares ethical, legal, and technical frameworks across the four countries. It identifies areas of convergence and divergence, offering policy recommendations aligned with the Global Digital Compact and relevant UN resolutions.
The study adopts a regulatory learning approach, engaging stakeholders in each jurisdiction to capture local insights and foster interjurisdictional learning. Coordinated by UNU, the initiative introduces a collaborative model for transnational policymaking by identifying shared challenges and co‑developing strategic responses.
Recommendations span three dimensions—ethical, regulatory, and technical interoperability. They include advancing a global AI ethics framework, establishing multilateral systems for coordinated governance, enhancing transparency and accountability, promoting interoperable digital public infrastructure, and embedding interoperability by design in technical standards.
The report concludes that the future of AI safety governance is evolving toward evidence‑based, outcomes‑oriented models that complement principle‑led frameworks. Sustaining momentum will require policymakers to deepen normative specificity, enhance legal interoperability, expand interoperable standards, strengthen data governance, and invest in AI literacy and capacity building.
Download the Full Report
- Policy Report: Interoperability in AI Safety Governance: Ethics, Regulations, and Standards – [Full Report PDF]
