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The AI Safety Policy Entrepreneurship Fellowship is FAS's route for turning technical and domain expertise into frontier AI safety policy that actually moves. It is a part-time hybrid programme running 30 September 2026 to 28 February 2027, with applications due 7 September 2026, and it pays a USD 5,000 stipend plus up to USD 1,000 as a merit award.
Fellows commit roughly five hours a week to developing a policy memo on a specific AI safety challenge, attend training sessions, join an in-person retreat in California from 4 to 7 November 2026, and present at a capstone event in Washington DC during the week of 22 February 2027.
The design target is explicit and unusual: it recruits early- to mid-career professionals who have limited direct public policy experience but deep expertise elsewhere - technical AI research, academia, think tanks, civil society, industry, law, cybersecurity and national security - and teaches them the mechanics of getting an idea adopted.
Selection weighs clear understanding of AI governance challenges, concrete implementation-oriented solutions rather than broad principles, awareness of which stakeholders must be moved, and a credible commitment to translating expertise into policy outcomes. Because the stipend is modest and the time commitment part-time, this is designed to sit alongside an existing job rather than replace one.
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Or search similar grants →According to the current listing, eligibility includes: The fellowship targets early- to mid-career professionals with limited experience working directly in public policy, drawn from backgrounds including technical AI research, academia, think tanks, civil society, industry, law, cybersecurity and national security, who want to translate their expertise into policy impact. Applications are due 7 September 2026 at 11:59 PM Eastern Time. The programme runs 30 September 2026 through 28 February 2027 on a part-time hybrid basis, requiring approximately five hours per week, plus attendance at an in-person retreat in California from 4 to 7 November 2026 and a capstone event in Washington DC during the week of 22 February 2027, so participants must be able to travel to the United States for those dates. Fellows receive a USD 5,000 stipend with an additional merit award of up to USD 1,000, along with travel support, professional editing, mentorship and networking. The core deliverable is a policy memo addressing a specific AI safety challenge together with an advocacy plan. Selection emphasises concrete, implementation-oriented proposals over general commentary. Applicants should confirm current deadlines, stipend terms, residency or work-authorisation requirements and the retreat and capstone dates directly with FAS before applying. Confirm the full requirements in the official notice before applying.
The current listing shows fellows receive a stipend of USD 5,000, plus an additional merit award of up to USD 1,000 for the fellow producing the most specific and actionable policy memo and advocacy plan. amount_min of 5,000 is the base stipend and amount_max of 6,000 reflects the stipend plus the maximum merit award. Travel support, professional editing, mentorship and networking are provided in addition to the stipend. This is a small award by dollar value, and the return is access and placement rather than research funding - the fellowship's output is a policy memo carried into Washington, not a paper. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Federation of American Scientists AI Safety Policy Entrepreneurship Fellowship 2026-2027 are due September 8, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Federation of American Scientists AI Safety Policy Entrepreneurship Fellowship 2026-2027 is funded by Federation of American Scientists (FAS). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
CIFAR and the Canadian AI Safety Institute fund Catalyst Project proposals addressing sociotechnical considerations in AI safety. The program supports interdisciplinary research in machine learning applications to science and society, with recent funded projects spanning misinformation combat, trustworthy language models, democratic alignment of AI systems, Indigenous AI governance, and real-world safety in autonomous systems. Designed to catalyze new research areas and collaborations at the intersection of social sciences, humanities, and AI safety.
The Climate Change AI Innovation Grants program supports projects that address research and deployment challenges in climate change mitigation, adaptation, and climate science by leveraging AI and machine learning, while also creating publicly available datasets and tools to catalyze further work. The program enables key partnerships that accelerate the research-to-deployment cycle, creating synergies between academic researchers, nonprofits, startups and other companies, and governmental or intergovernmental organizations. Funded by the Quadrature Climate Foundation, Schmidt Futures, and Google DeepMind, with Future Earth serving as fiscal sponsor, this is one of the few dedicated grant programs specifically targeting the intersection of AI/ML and climate change. Projects typically involve climate modeling, weather prediction, emissions monitoring, energy optimization, biodiversity monitoring, and other environmental applications of machine learning. The 2026 competition opens with a full proposal deadline of September 15, 2026. The program has grown steadily since its inception, funding 23 projects to date across diverse climate domains and geographies.
Climate Change AI Innovation Grants provide seed funding for research, deployment, and the creation of datasets and tools that address climate change mitigation, adaptation, and climate science using AI and machine learning. Supported areas include power and energy systems, agriculture and food, climate science and modeling, weather prediction, ecosystems and biodiversity monitoring, remote sensing, disaster management, carbon capture, oceans, forests, and transportation. Projects are expected to produce publicly available datasets and tools.
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