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International Institutions for Advanced AI
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International institutions may have an important role to play in ensuring advanced AI systems benefit humanity. International collaborations can unlock AI's ability to further sustainable development, and coordination of regulatory efforts can reduce obstacles to innovation and the spread of benefits. Conversely, the potential dangerous capabilities of powerful and general-purpose AI systems create global externalities in their development and deployment, and international efforts to further responsible AI practices could help manage the risks they pose. This paper identifies a set of governance functions that could be performed at an international level to address these challenges, ranging from supporting access to frontier AI systems to setting international safety standards. It groups these functions into four institutional models that exhibit internal synergies and have precedents in existing organizations: 1) a Commission on Frontier AI that facilitates expert consensus on opportunities and risks from advanced AI, 2) an Advanced AI Governance Organization that sets international standards to manage global threats from advanced models, supports their implementation, and possibly monitors compliance with a future governance regime, 3) a Frontier AI Collaborative that promotes access to cutting-edge AI, and 4) an AI Safety Project that brings together leading researchers and engineers to further AI safety research. We explore the utility of these models and identify open questions about their viability.
Forward citations
Cited by 4 Pith papers
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The Case for Globally Beneficial Technology
Everyone has a moral claim to material benefit from advanced technologies such as AI, grounded in five overlapping arguments from rights, beneficence, luck, knowledge commons, and global justice.
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Towards Responsible Governing AI Proliferation
The paper proposes a 'Proliferation' paradigm of AI, where small, hidden, augmented, decentralized, and open-weight models challenge compute-centric governance.
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Domestic frontier AI regulation, an IAEA for AI, an NPT for AI, and a US-led Allied Public-Private Partnership for AI: Four institutions for governing and developing frontier AI
Compute governance can underpin four institutions for frontier AI: domestic regulation, an International AI Agency, a Secure Chips Agreement, and a US-led Allied Public-Private Partnership.
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Quantifying detection rates for dangerous capabilities: a theoretical model of dangerous capability evaluations
A new model quantifies how test sensitivity, capability growth, and threshold placement determine bias and detection lag in dangerous AI evaluations.
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