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Coefficient Giving runs periodic Technical AI Safety RFPs — monitor coefficientgiving.org for next round announcement.
The Open Philanthropy Technical AI Safety RFP is a grant from Open Philanthropy that funds academic researchers, independent labs, and individual scientists advancing technical AI safety.
The program committed approximately $40 million across 21 research areas, spanning adversarial machine learning, LLM misbehavior analysis, interpretability and white-box techniques, alternative risk-mitigation approaches, and theoretical work on aligning superintelligent systems.
Supported work types include discrete research projects (6–24 months), research expense grants (compute, APIs), academic startup packages, and support for new research organizations. Proposals began with a 300-word expression of interest. The prior round deadline was April 15, 2025; future rounds may be announced separately.
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Open Philanthropy Technical AI Safety RFP - $40M Available Across 21 Research Areas — EA Forum Open Philanthropy Technical AI Safety RFP - $40M Available Across 21 Research Areas by Jake Mendel , Max Nadeau , Peter Favaloro AI safety Opportunities to take action Announcements and updates Coefficient Giving Grantmaking Research Frontpage Open Philanthropy Technical AI Safety RFP - $40M Available Across 21 Research Areas This is a linkpost for https://www.
openphilanthropy. org/request-for-proposals-technical-ai-safety-research/ Open Philanthropy is launching a big new Request for Proposals for technical AI safety research , with plans to fund roughly $40M in grants over the next 5 months, and available funding for substantially more depending on application quality. Applications start with a simple 300 word expression of interest and are open until April 15, 2025.
We're seeking proposals across 21 different research areas, organized into five broad categories: Adversarial Machine Learning *Jailbreaks and unintentional misalignment *Backdoors and other alignment stress tests *Alternatives to adversarial training Exploring sophisticated misbehavior of LLMs *Experiments on alignment faking *Encoded reasoning in CoT and inter-model communication Evaluating whether models can hide dangerous behaviors Reward hacking of human oversight Applications of white-box techniques Finding feature representations Toy models for interpretability Interpretability benchmarks More transparent architectures Trust from first principles White-box estimation of rare misbehavior Theoretical study of inductive biases Alternative approaches to mitigating AI risks Conceptual clarity about risks from powerful AI New moonshots for aligning superintelligence We’re willing to make a range of types of grants including: Research expenses (compute, APIs, etc.) Discrete research projects (typically lasting 6-24 months) Academic start-up packages Support for existing nonprofits Funding to start new research organizations or new teams at existing organizations.
The full RFP provides much more detail on each research area, including eligibility criteria, example projects, and nice-to-haves. Please email aisafety@openphilanthropy. org with questions, or just submit an EOI.
Click to highlight new comments since: Today at 4:21 PM Has Open Phil (or others) conducted a comprehensive analysis for both understanding and building the AI safety field? If yes, could you share some leads to add to my research? If not, would Open Phil consider funding such work?
(either under the above or other funds) Here is a recent example: Introducing SyDFAIS: A Systemic Design Framework for AI Safety Field-Building Thao Pham🔹 Feb 27 2025 1 I'm new to applying for an AIS grant, so I have some common questions that might have been answered elsewhere: (1) what are some failure modes that I might need to consider when writing a proposal, specifically for a research project?
(2) will research expenses include stipends for the researchers? (3) can I write a grant to do a research project with my university AI safety group? I'm not sure if this will be considered a field-building or a technical AI safety grant.
Some common failure modes: Not reading the eligibility criteria Not clearly distinguishing your project from prior work on the topic you're interested in Not demonstrating a good understanding of prior work (would be good to read some/all of the papers we link to in this doc for whatever section you're applying within) Not demonstrating that you/your team has prior experience doing ML projects.
If you don't have such experience, then it's good to work with/be mentored by someone who does. "Research expeneses" does not include stipends, but you can apply for a project grant, which does. If you're looking for money to spend on ML experiments or to pay people who are spending their time doing ML research, then that may fall within this RFP.
If you're looking for money to do other things (e.g. reading groups, events, etc), then that may fall under the capacity-building team's RFPs. Curated and popular this week
Key questions and narrative sections extracted from the solicitation.
300-word expression of interest required to begin application
Based on current listing details, eligibility includes: Academic labs, independent research organizations, and individual researchers. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Approx. $40,000,000 across 21 research directions (previous RFP) Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is April 15, 2025. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
Yes — AI tools like Granted can help research funders, draft proposal sections, and check compliance. However, always review and customize AI-generated content to reflect your organization's unique strengths and the specific requirements of the solicitation.
Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.
Past winners and funding trends for this program
Academic Grant Program (NVIDIA) is sponsored by NVIDIA. NVIDIA's Academic Grant Program seeks proposals from full-time faculty members at accredited academic institutions who are using NVIDIA technology to advance work in Simulation and Modeling, Data Science, and Robotics and Edge AI. Proposals should incorporate pretrained models from ai.nvidia.com and/or make extensive use of NVIDIA software distributions.
This NOFO provides an opportunity to all FY 2018 NIST SBIR Phase I awardees to submit a Phase II application following completion of Phase I. This NOFO provides instructions for FY 2019 NIST SBIR Phase II application preparation and submission requirements. In Phase II, work from Phase I that exhibits potential for commercial application is further developed. Phase II is the R&D or prototype development phase. To apply for a Phase II award, each Phase I awardee will be required to submit a comprehensive application outlining the proposed research and a detailed plan to commercialize the final product. Each NIST Phase II award is for up to $400,000 and up to a 24-month period of performance. One year after completing the Phase II R&D activity, the awardee shall be required to report on its commercialization activities. Up to an additional $6,500 may be requested for Technical and Business Assistance (TABA); see Section 5.11 for more information about TABA. Funding Opportunity Number: 2019-NIST-SBIR-02. Assistance Listing: 11.620. Funding Instrument: CA. Category: ST. Award Amount: Up to $400K per award.
Local Government Cybersecurity Grant Program (Florida) is sponsored by Florida Digital Service. This Florida state grant program enhances cybersecurity resilience in local governments, with a priority focus on fiscally constrained rural areas. Rather than issuing direct funding, the Florida Digital Service will procure cybersecurity solutions directly on behalf of awarded applicants. The grant supports new or expanded capabilities in preventing, detecting, responding to, and recovering from cyber threats.