One of the world's oldest and most prestigious research universities, Oxford has been a central hub for AI safety and existential risk research through institutions like the Future of Humanity Institute (FHI) and the Oxford Martin AI Governance Initiative (AIGI).
One of the world's oldest and most prestigious research universities, Oxford has been a central hub for AI safety and existential risk research through institutions like the Future of Humanity Institute (FHI) and the Oxford Martin AI Governance Initiative (AIGI).
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Updated 05/18/26Funding Details
Updated 05/18/26- Annual Budget
- $3,021,200,000
- Current Runway
- -
- Funding Goal
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- Funding Raised to Date
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Org Details
Updated 05/18/26The University of Oxford has no single founding date, with evidence of teaching dating to 1096, making it the oldest university in the English-speaking world and one of the oldest in continuous operation in the world. It is a collegiate research university comprising 43 colleges and a range of academic departments organized across four divisions. As of 2024, it employs approximately 16,905 staff and hosts 22,735 full-time students. Its total annual income was approximately £3.1 billion in 2023-24, supported by a combined endowment of £8.7 billion. Oxford has been one of the most important institutional homes for AI safety and existential risk research globally. The Future of Humanity Institute (FHI), founded in 2005 by philosopher Nick Bostrom as part of the Oxford Martin School, pioneered research on existential risk, AI alignment, AI governance, longtermism, and global catastrophic risk. FHI spawned numerous influential ideas and spin-off organizations, including the Centre for the Governance of AI (GovAI), which became an independent nonprofit in 2021. FHI was closed on 16 April 2024 after facing what it described as increasing administrative headwinds within the Faculty of Philosophy, with a hiring and fundraising freeze imposed from 2020 and non-renewal of staff contracts in late 2023. Following FHI's closure, AI safety and governance research at Oxford continues through several channels. The Oxford Martin AI Governance Initiative (AIGI), co-directed by Robert Trager and Michael Osborne and housed at the Oxford Martin School, focuses on understanding risks from advanced AI through rigorous technical and policy research across five domains: frontier AI governance, technical AI governance, international AI governance, social impact of emerging technologies, and China AI governance. AIGI offers novel DPhil studentships bridging advanced AI systems and governance. The Oxford Internet Institute runs a research programme on AI, government, and policy supported by the Dieter Schwarz Foundation. In April 2025, Oxford researchers were awarded grants through the UK Government's £59 million ARIA Safeguarded AI programme to develop safety-first AI approaches. The Oxford AI Safety Initiative (OAISI), a student-led community that became independent from the university in Summer 2024, continues running ML safety bootcamps and research projects.
Theory of Change
Updated 05/18/26Oxford's approach to reducing AI-related risks operates through multiple channels: producing foundational academic research that shapes the global understanding of AI risks and governance options; training the next generation of researchers and policymakers who will work on AI safety and governance; hosting interdisciplinary institutes that bridge technical AI research with philosophy, economics, and policy; and influencing government and international AI policy through direct engagement and published analysis. The university's prestige and convening power amplify the reach of its AI safety research, helping translate academic findings into real-world governance frameworks and safety standards.
Grants Received
Updated 05/18/26Projects
Updated 05/18/26An interdisciplinary research initiative at the University of Oxford’s Oxford Martin School that aims to understand and anticipate potential risks from AI through rigorous research into the technical elements of AI, combined with deep policy analysis.
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