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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.
A leading Israeli research university home to the Governance of AI Lab (GOAL), which conducts cross-disciplinary research on AI governance, legal alignment, and the safe development of advanced AI systems.
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).
5050 is a free 12-14 week company-builder program run by Fifty Years that helps scientists, researchers, and engineers become deep-tech startup founders, with a dedicated AI safety track.
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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Director of Safe AI Germany
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Sam F. Brown is an independent AI alignment researcher based in Oxford, UK. He has a background in physics and programming, and previously worked at a climate technology startup before pivoting to full-time alignment research. He has received two grants from the EA Long-Term Future Fund: an initial six-month grant (approximately £40,000) for research on goal-inference and choice-maximisation, and a subsequent twelve-month grant ($82,298) to research technical approaches to value lock-in and minimal paternalism. His work explores empowerment-based alignment — the idea of maximising humans' capacity to reach diverse future outcomes rather than inferring and locking in specific human values. He has published research essays on LessWrong and the EA Forum, including "The Empowerment of Others" and "Questions about Value Lock-in, Paternalism, and Empowerment". He is connected to the Oxford rationalist and EA community and works from spaces including Trajan House, the Centre for Effective Altruism's Oxford building.
Co-director of the Cambridge AI Safety Hub, working on AI safety fieldbuilding in Cambridge, UK. Previously a political science PhD candidate at SUNY Stony Brook, with experience in research and teaching before moving full-time into AI safety.
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Executive and Research Director of the Center for AI Safety (CAIS). A nonprofit research organization based in San Francisco focused on reducing societal-scale risks from artificial intelligence. He received a B.S. from the University of Chicago in 2018 and a Ph.D. in Computer Science from UC Berkeley in 2022, advised by Dawn Song and Jacob Steinhardt. His research spans machine learning safety, robustness, out-of-distribution detection, and AI ethics. He is the primary author of the GELU activation function (2016), which is widely used in state-of-the-art models including BERT and GPT, and created the MMLU (Massive Multitask Language Understanding) benchmark (2020), one of the most widely used LLM evaluation benchmarks. He also co-developed the MATH benchmark, Humanity's Last Exam (HLE), and authored the 2024 textbook Introduction to AI Safety, Ethics, and Society. He serves as a safety advisor to xAI and Scale AI, both at nominal compensation, and has received early-career funding from EA-aligned organizations for his work on value learning and AI alignment benchmarks.
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Director of Operations at the AI Safety Awareness Project. Trained as a mechanical engineer, he previously worked as a design engineer at Boeing across commercial and defense programs, focusing on structural design, destructive testing, and product development. He holds a B.S.E. and an M.S. in Mechanical Engineering from Arizona State University and, beginning in 2024, transitioned from aerospace engineering into operational work and AI safety outreach.
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Straumli is an AI safety company that offers managed auditing and self-serve evaluations to help AI developers identify misuse risks and ship safer models faster.
Yoel Roth is a nonresident scholar in the Technology and International Affairs Program at the Carnegie Endowment for International Peace and senior vice president of trust and safety at Match Group; he previously led Twitter’s trust and safety team and now focuses on governance and safety for social media and AI systems.
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12 months funding for 3 people to work full-time on projects supporting AI safety efforts
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A podcast mainly themed around AI x-risk, aimed at a non-technical audience
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Maxwell (Max) Clarke is a New Zealand-based software engineer and independent AI alignment researcher. He holds a Master of Science in Computer Science from Victoria University of Wellington (2020-2022), where his thesis focused on applying transformer models to hand motion modelling, and a Bachelor of Science in Computer Science from the University of Canterbury (2015-2018). After completing his MSc, he received a grant from the Long-Term Future Fund to pursue career exploration in AI alignment, during which he conducted independent research in AI interpretability in 2023. He currently works as a Python backend developer at the New Zealand Stock Exchange (NZX). He is an active participant in the Effective Altruism community in New Zealand and has spoken publicly on AI safety approaches and careers.
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