Artificial intelligence (AI) systems are increasingly deployed transnationally without accountability, leading to issues like cancer detection algorithms misdiagnosing patients in the Global South due to biased training data, and AI in European border systems risking incorrect asylum seeker returns. This global deployment, lacking shared standards and governance, has sparked a "governance race" among international entities and governments, resulting in a fragmented patchwork of standards and legislation with limited scope or enforcement.
Countries like Singapore, India, Brazil, and the United States are developing divergent domestic AI governance mechanisms, ranging from voluntary frameworks to binding laws and risk-based approaches. This regulatory fragmentation challenges companies and undermines capacity for shared rules on attribution and accountability for transnational harms. The United Nations is positioned to deepen collective understanding and enhance interoperability through initiatives like the Global Digital Compact, which mandates an Independent International Scientific Panel on AI and a Global Dialogue on AI Governance to build international consensus.
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