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2023 Alignment Research Updates
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High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: FAR AI
Annual research summary from FAR.AI (Far Out Research in AI), a safety-focused nonprofit; useful for tracking empirical safety research on robustness testing, value learning, and model evaluation methods as of 2023.
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Importance: 45/100organizational reportnews
Summary
FAR.AI summarizes their 2023 alignment research across three agendas: a science of robustness agenda that discovered vulnerabilities in superhuman Go systems, value alignment research producing more sample-efficient value learning algorithms, and model evaluation work developing both black-box and white-box evaluation methods.
Key Points
- •Science of robustness agenda identified exploitable vulnerabilities in superhuman Go-playing AI systems, raising questions about reliability of advanced AI.
- •Value alignment research produced more sample-efficient algorithms for value learning, potentially reducing data requirements for alignment approaches.
- •Model evaluation direction advanced both black-box and white-box methods for assessing AI system behavior and properties.
- •Report covers FAR.AI's three core research directions as an AI safety nonprofit founded in 2022.
- •Full PDF available summarizing technical research outputs from the year.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| FAR AI | Organization | 76.0 |
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2023 Alignment Research Updates
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2023 Alignment Research Updates
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November 21, 2023
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Summary
FOR IMMEDIATE RELEASE
FAR.AI Launches Inaugural Technical Innovations for AI Policy Conference, Connecting Over 150 Experts to Shape AI Governance
WASHINGTON, D.C. — June 4, 2025 — FAR.AI successfully launched the inaugural Technical Innovations for AI Policy Conference , creating a vital bridge between cutting-edge AI research and actionable policy solutions. The two-day gathering (May 31–June 1) convened more than 150 technical experts, researchers, and policymakers to address the most pressing challenges at the intersection of AI technology and governance.
Organized in collaboration with the Foundation for American Innovation (FAI) , the Center for a New American Security (CNAS) , and the RAND Corporation , the conference tackled urgent challenges including semiconductor export controls, hardware-enabled governance mechanisms, AI safety evaluations, data center security, energy infrastructure, and national defense applications.
"I hope that today this divide can end, that we can bury the hatchet and forge a new alliance between innovation and American values, between acceleration and altruism that will shape not just our nation's fate but potentially the fate of humanity," said Mark Beall, President of the AI Policy Network, addressing the critical need for collaboration between Silicon Valley and Washington.
Keynote speakers included Congressman Bill Foster, Saif Khan ( Institute for Progress ), Helen Toner (CSET), Mark Beall ( AI Policy Network ), Brad Carson ( Americans for Responsible Innovation ), and Alex Bores ( New York State Assembly ). The diverse program featured over 20 speakers from leading institutions across government, academia, and industry.
Key themes emerged around the urgency of action, with speakers highlighting a critical 1,000-day window to establish effective governance frameworks. Concrete proposals included Congressman Foster's legislation mandating chip location-verification to prevent smuggling, the RAISE Act requiring safety plans and third-party audits for frontier AI companies, and strategies to secure the 80-100 gigawatts of additional power capacity needed for AI infrastructure.
FAR.AI will share recordings and materials from on-the-record sessions in the coming weeks. For more information and a complete speaker list,
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