A collaborative research programme between the Leverhulme Centre for the Future of Intelligence and the Centre for the Study of Existential Risk at the University of Cambridge, focused on the global risks, governance, and long-term safety of advanced AI.
A collaborative research programme between the Leverhulme Centre for the Future of Intelligence and the Centre for the Study of Existential Risk at the University of Cambridge, focused on the global risks, governance, and long-term safety of advanced AI.
People
Updated 05/18/26Director, AI: Futures and Responsibility Programme
Funding Details
Updated 05/18/26- Annual Budget
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- Current Runway
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- Funding Goal
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Org Details
Updated 05/18/26The AI: Futures and Responsibility Programme (AI:FAR) is a collaborative research initiative between the Leverhulme Centre for the Future of Intelligence (LCFI) and the Centre for the Study of Existential Risk (CSER) at the University of Cambridge. The programme was established around 2018-2019 and is directed by Dr Sean O hEigeartaigh, who previously served as CSER's founding Executive Director (2013-2015) and Acting Director (2021-2023). AI:FAR concentrates on three primary activities: understanding the ways AI developments could create lasting or extreme societal consequences, developing interventions that are likely to be robustly beneficial across a range of potential futures given uncertainties about AI system evolution, and implementing policies by partnering with stakeholders in academia, policy, industry, and civil society to translate research recommendations into practical applications. The programme's research is organized around three themes. Futures and foresight focuses on technology forecasting, trends analysis, impact assessment, participatory foresight, and methodological innovation in scenario analysis. Governance, ethics and responsible innovation examines the norms and principles needed within AI research communities and broader AI governance, and how to move beyond high-level principles to practical implementation. Safety, security and risk addresses specific challenges posed by AI in contexts ranging from pandemic response to defense to critical systems such as global agriculture. Notable projects include research on ethical challenges of deploying AI during crises (published in Nature Machine Intelligence), analysis of AI benchmarking and progress indicators, mapping AI safety challenges to research directions, participatory Citizen Science Labs studying perceptions of emotion recognition technologies (supported by Nesta), and multi-institution reports on translating ethical principles into responsible AI practices. The programme director co-chairs the World AI Conference's International AI Governance Programme and has led projects building cooperation on AI governance with research leaders in China and other countries. The team includes a Cambridge-based director and a network of collaborating scholars, research associates, and research affiliates drawn from institutions worldwide, including researchers such as Jess Whittlestone (now at the Centre for Long-Term Resilience), Haydn Belfield, Giulio Corsi, Jose Hernandez-Orallo, Matthijs Maas, Elizabeth Seger, and others. The programme has maintained a steady output of academic publications, policy reports, and governance recommendations since its inception.
Theory of Change
Updated 05/18/26AI:FAR's theory of change operates through three connected mechanisms. First, by conducting rigorous foresight research on AI development trajectories, they identify underexplored risk scenarios and potential societal impacts before they materialize, enabling proactive rather than reactive governance. Second, by developing practical interventions and governance frameworks that are robust across a range of uncertain futures, they aim to ensure that safety measures remain effective regardless of which specific AI development path unfolds. Third, by actively partnering with policymakers, industry leaders, and international bodies (including the OECD, United Nations, and national governments), they translate academic research into real-world policies and standards that shape how AI is developed and deployed. The underlying belief is that interdisciplinary research combining technical understanding with governance expertise, conducted within a world-class university setting with strong international networks, can meaningfully influence the trajectory of AI development toward safer and more beneficial outcomes.
Grants Received
Updated 05/18/26Projects– no linked projects
Updated 05/18/26Discussion
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