The Hidden AI Frontier
Argues that frontier AI models kept hidden inside corporate labs pose dual-use and security risks, and proposes transparency and oversight measures for these privately held systems.
Research
IAPS
Policy research on advanced AI security and governance. www.iaps.ai
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Source IAPS · 14
Date Any time
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How Some of China’s Top AI Thinkers Built Their Own AI Safety Institute
Describes the founding of the China AI Safety and Development Association (CnAISDA), a pivotal body for frontier AI governance in China, and how its domestic and geopolitical challenges may shape frontier AI risk discussions.
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A Whistleblower Incentive Program to Enforce U.S. Export Controls
Proposes a whistleblower incentive program modeled on the SEC's to improve enforcement of U.S. export controls on AI chips and other compute-related technology.
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Countering AI Chip Smuggling Has Become a National Security Priority: An Updated Playbook for Preventing AI Chip Smuggling to the PRC
Catalogues evidence of large-scale AI chip smuggling into China and recommends policy measures, including a whistleblower program, notification rules, and location verification, to strengthen export-control enforcement.
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Assuring Growth: Making the UK a Global Leader in AI Assurance Technology
A UK policy memo recommending government market-shaping to grow the AI assurance technology industry, covering AI alignment, security and auditing tools, and the regulatory and demand uncertainties that hold it back.
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Spreadsheets vs. Smugglers: Modernizing the BIS for an Era of Tech Rivalry
Argues that Congress should increase funding for the Bureau of Industry and Security so it can enforce export controls on weapons-of-mass-destruction and sensitive technologies amid US-China tech rivalry.
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Highlights for Responsible AI from the Biden Administration's FY2025 Budget Proposal
An IAPS brief analyzing three US FY2025 budget allocations for AI, including Commerce, export-control and Energy cybersecurity funding, for their impact on responsible advanced AI development.
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Responsible Reporting for Frontier AI Development
Proposes responsible reporting of safety-critical information from frontier AI developers to government, industry and civil society, with voluntary and regulatory mechanisms for implementing it.
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Secure, Governable Chips
Proposes on-chip governance: security features on AI chips to mitigate national security risks from dual-use AI while protecting privacy, with concrete U.S. policy recommendations.
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Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework
Argues that external scrutiny, including third-party auditing, red-teaming and researcher access, is needed for public accountability over frontier LLM decisions, and sets out six requirements under the ASPIRE framework with policy recommendations.
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Preventing AI Chip Smuggling to China
Overview of AI chip smuggling into China, its current and future trajectories, and four recommendations for US policymakers to understand and mitigate large-scale smuggling of AI chips.
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Managing AI Risks in an Era of Rapid Progress
A consensus paper from many researchers outlining risks from advanced AI, including loss of human control, and proposing urgent priorities for AI R&D and governance.
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How Expertise in AI hardware Can Help with AI Governance
A career review arguing that building expertise in AI hardware can help reduce AI risks and improve governance decisions, drawing on compute governance work.
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Open-Sourcing Highly Capable Foundation Models
Argues that open-sourcing some highly capable foundation models may pose extreme risks outweighing benefits, and surveys alternative model-sharing strategies with policy recommendations for developers, standards bodies and governments.