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Clear filtersCambodian computer scientist and technology leader with around two decades of experience in data and artificial intelligence, former Google AI programme lead and current Head of Data and AI Ecosystems at the World Economic Forum, who co-founded and serves as Executive Director of AI Safety Asia while advising the UN Secretary-General’s High-Level Advisory Body on Artificial Intelligence.
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Nick Bostrom is a Swedish-born philosopher known for his work on existential risk and the long-term future of humanity. He was Professor of Philosophy at the University of Oxford and founding Director of the Future of Humanity Institute from 2005 until its closure in 2024, and is now the founder and principal researcher at the nonprofit Macrostrategy Research Initiative.
Sofia Lanfri is a data scientist and research program manager with experience in geospatial and epidemiological analysis. She serves as Program Director at the Beneficial AI Foundation and coordinates BAIF’s involvement in Signal Shot and other AI safety projects.
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Orpheus Lummis is a software developer and community organizer based in Montréal, Canada, focused on advancing AI safety through convenings, coordination, and software. He is the founder of HΩ (Horizon Omega), a Canadian non-profit that runs the AI Safety Unconference series, the Guaranteed Safe AI Seminars, and a weekly AI Safety Events and Training newsletter. He has organized multiple editions of the AI Safety Unconference, including events co-located with NeurIPS and a fully virtual edition in 2024, and organized the Limits to Control Workshop in 2025. He has received funding from the Long-Term Future Fund for upskilling in AI techniques, deep reinforcement learning, and AI safety, and engaged with David Krueger's AI safety reading group at Mila. He is a software engineer generalist with specialties in distributed systems and machine learning, and was a core contributor to DefraDB, a decentralized user-centric database.
A research project developing non-maximizing, aspiration-based designs for AI agents that avoid objective function maximization, arguing that such optimization is inherently unsafe in sufficiently capable AGI systems.
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Director of the UC Berkeley Cybersecurity Clinic and lecturer at the School of Information, Elijah Baucom is a cybersecurity and privacy technologist, engineer, and activist focused on the intersection of technology, humanity, liberation, and political education; through the clinic he teaches and trains students to consult with and support social‑sector organizations that are particularly susceptible to ideologically motivated cyber attacks, and he is also the founder of Everyday Security, which provides cybersecurity and IT support to human rights and movement organizations.
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Technical Program Manager at the Technical Alignment Research Accelerator (TARA) and Master of AI student at UNSW, with a background including a Bachelor of Science in Mathematical Physics and a Diploma in Music from the University of Melbourne, completion of TARA v1 with a capstone project on causal interventions on a chess model, acceptance into the SPAR program, leadership roles in Effective Altruism University of Melbourne, and work on AI-focused education seminars.
Alex Flint is an independent AI alignment researcher and monastic. He completed his PhD with the Active Vision Lab at the University of Oxford (2008-2012) in robotics and computer vision on a Clarendon Fund scholarship, following undergraduate studies in computer science at the University of Adelaide. After his PhD he led computer vision engineering at Flyby Media in New York City, then co-founded Zippy.ai, a robotics startup focused on last-mile delivery, which was acquired by Cruise (GM's autonomous vehicle division) in 2018. He subsequently left industry to pursue independent AI alignment research and is affiliated with the Monastic Academy for the Preservation of Life on Earth in Vermont. His alignment research focuses on foundational theories of optimization, knowledge, and agency, including a widely cited post "The ground of optimization" selected as Best of LessWrong 2020. He has received funding from the Long-Term Future Fund for independent research and is active on LessWrong and the AI Alignment Forum.
Ben Hoffman has worked as a researcher for GiveWell and the Open Philanthropy Project and in financial services managing a risk analytics team, and he holds an MS in Mathematics and Statistics from Georgetown University and a BA from St John’s College.
Buck Shlegeris is the CEO of Redwood Research, a nonprofit AI safety and security lab, where he leads work on AI control and related empirical safety research; he previously worked on AI alignment and outreach at the Machine Intelligence Research Institute (MIRI).
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Lorenzo is a full‑stack software engineer at Giving What We Can, supporting product development and maintaining the organisation’s technical infrastructure. Originally from Italy, he previously did small‑scale earning to give as a software developer in the Netherlands and, after winning a donor lottery in 2022, moved back to Italy to reflect on how to do more good.
Researcher at the Machine Intelligence Research Institute working on the foundations of reasoning and agency, including logical uncertainty and decision theory; studied pure mathematics at the University of Waterloo and previously worked at Google on automatic construction of deep learning models.
Trajectory Labs is a nonprofit coworking and events space in downtown Toronto dedicated to AI safety research and community building. It provides free workspace, weekly events, and a peer network to grow Toronto's AI safety ecosystem.
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Conor Barnes is a software developer and writer based in Halifax, Nova Scotia, Canada. He works at 80,000 Hours as a Job Board Product Engineer, having joined as a software engineer before taking on responsibility for the job board platform. Prior to 80,000 Hours, he worked at a startup and as a cataloguer at a library, and is self-taught in software engineering without a university degree. In 2022, he received a Long-Term Future Fund grant to build x-risk-tree.com, an interactive EA alternative to the Doomsday Clock that visualizes existential risk as a branching tree of possible futures using Metaculus prediction data. He is active on the EA Forum under the handle Ideopunk and also writes fiction and non-fiction on his personal website and Substack.
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Assistant Professor in Natural Language Processing at the University of Vienna, working in natural language processing and related areas of computational linguistics.
Alex Turner is a research scientist at Google DeepMind on the scalable alignment team, where he works on training invariants into model behavior and related alignment problems. He previously formulated and proved the power-seeking theorems, co-formulated the shard theory of human value formation, and proposed the Attainable Utility Preservation (AUP) approach to penalizing negative side effects, and he now mentors researchers through the MATS program’s Team Shard stream.
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Executive Director of Probably Good, whose widely read writing on applied psychology and philosophy has been linked from outlets such as The New York Times and TechCrunch; holds a PhD from the University of Cambridge, where he is an affiliated lecturer teaching quantitative and computational research methods.
Helen Edwards is co-founder of the Artificiality Institute, a nonprofit that explores how AI is transforming how people think, decide and live. She has led large-scale technology transformations as CIO of New Zealand’s national grid and held executive roles at organizations including Pacific Gas & Electric, Fonterra, Meridian Energy, Quartz and Transpower. She also serves as a commissioner on Oregon’s Higher Education Coordinating Commission and is a visiting researcher at UC Berkeley’s Center for Human-Compatible AI.
Josh Rosenberg is the Chief Executive Officer and a co-founder of the Forecasting Research Institute, where he oversees research, strategy, fundraising, and operations with a focus on making forecasting useful to decision-makers. Previously, he was a Senior Advisor and Senior Research Manager at GiveWell, working on management, research, grantmaking, and hiring, and he holds a B.A. in Economics and Philosophy from Pomona College.
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).
CEO and co-founder of Apollo Research. An AI safety organization he co-founded in May 2023 that specializes in evaluating dangerous capabilities and deceptive behaviors in frontier AI models. He holds a PhD in Bayesian Machine Learning from the International Max-Planck Research School in Tübingen, as well as an M.Sc. in Machine Learning and dual B.Sc. degrees in Computer Science and Cognitive Science from the University of Tübingen. Prior to founding Apollo Research, he was a Research Fellow at Epoch AI (June 2022–April 2023), where he worked on AI forecasting. His research at Apollo focuses on scheming detection, AI control, and dangerous capability evaluations, and the organization collaborates with frontier labs including OpenAI and Anthropic as well as government bodies like the UK AI Security Institute. He serves as a mentor in the MATS program for AI safety researchers and became a Manifund regrantor in 2025. He was named to TIME's 100 Most Influential People in AI for 2025.
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President and Partner at Flow Research Collective and Venture Partner at multiple early-stage funds including Lionheart Ventures, Pioneer Fund, Essence Venture Capital and 1024 Ventures, as well as Limited Partner Advisor at GTMfund.
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Paul Colognese is an AI safety researcher based in the United Kingdom, focused on understanding how AI systems represent and self-reflect on their goals and beliefs. He holds a PhD in Mathematics (Geometry, Topology, and Dynamical Systems) from the University of Warwick, where he researched translation surfaces under the supervision of Professor Mark Pollicott. His AI safety work includes building safety evaluations for Anthropic and the UK AI Security Institute, including control and sabotage evaluations that measure whether deployed AI agents could undermine safety systems. He has conducted AI threat modeling on catastrophic risk scenarios and carried out interpretability research in which he demonstrated the ability to detect an AI system's objectives through technical analysis. He participated in the MATS research program mentored by Evan Hubinger at Anthropic. He founded the London Initiative for Safe AI, a UK-based research center, and serves as AI Alignment Lead at the Center for the Study of Apparent Selves. He is active on LessWrong and the Alignment Forum, and participated in AI Safety Camp (AISC9) working on detecting agentic AI objectives via interpretability methods.
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