Center On Long-Term Risk (CLR) funds research and training aimed at reducing worst-case risks from advanced AI, with a distinctive emphasis on astronomical suffering (s-risks), multi-agent conflict, cooperation, and related technical and philosophical questions. It tends to support researchers, fellows, and collaborative projects working on AI safety, governance, decision theory, and macrostrategy, rather than broad service delivery or general nonprofit work. Grants are global and often flexible in size, with an emphasis on high-leverage early research and capacity building.
Rolling, research-focused grants with highly variable sizes, from small awards of around £2,000 to larger grants approaching £39,000; also runs an annual summer research fellowship with stipend/support for promising researchers. Funding is typically directed to research, tuition, living costs, and collaborative projects, and appears to be invitation- or fit-driven rather than a broad open-call program.
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Monitor the rolling CLR Fund rather than waiting for a fixed deadline, and tailor proposals tightly to s-risk reduction, cooperative AI, AI governance, or related technical/philosophical work. Strong applications will explain the research question, why it is relevant to worst-case AI risk, and what concrete output will be produced; the Summer Research Fellowship is a separate annual pathway for newer researchers seeking training and evaluation.
Current and upcoming funding from Center On Long-Term Risk that your nonprofit may be able to apply for.
Who can apply: Recipients may be charitable organizations, academic institutions, or individuals. Priority is given to individuals who want to make research contributions to CLR’s current priority areas, but support may be available for any high-quality work relevant to s-risks now or in the future.
Deadline: Rolling basis
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Create a free accountDeadlines and eligibility are summarized from public sources and may change — always confirm the details on the funder's official application page before applying.