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Coleman Snell is an AI governance and strategy researcher completing his undergraduate degree in psychology and philosophy at Cornell University. He was a visiting researcher at the Centre for the Study of Existential Risk (CSER) at Cambridge, where he conducted a 6-month AI strategy and policy research stay supervised by Seán Ó hÉigeartaigh and in collaboration with Matthew Gentzel of LongView, with a focus on cooperation and policy dimensions of AI risk. He is the founder of Cornell's AI Safety Laboratory (LAISR) and served as President of Cornell Effective Altruism for three years. Coleman is a collaborating researcher at AI:FAR (AI Futures and Risks), working on AI governance strategy and grand strategy approaches to global AI risks. He also hosts the "On What Matters" podcast, a longform interview show exploring AI risk and existential risk with researchers, academics, and policymakers.
Tara Steele is the Founder and Director of the Safe AI for Children Alliance (SAIFCA), an initiative dedicated to protecting children as advanced AI systems reshape society. A former intelligence officer with a first-class law degree and certifications in AI governance, ethics and safety, she focuses on the risks AI poses to children and advises policymakers, including through appearances at UNESCO and in the UK Parliament. She serves on the Council of the International Association for Safe and Ethical AI (IASEAI) and speaks internationally on AI safety and children’s rights.
Dr. Prineha “Pri” Narang is a non-resident senior fellow at the Foundation for American Innovation and a quantum scientist and engineer. She is a Professor of Physical Sciences and Electrical and Computer Engineering at UCLA, where her NarangLab researches quantum materials, photonics, and quantum information, and previously served on the faculty at Harvard after earning her MS and PhD in Applied Physics from Caltech.
Said Achmiz is a web developer and long-standing contributor to the rationalist and effective altruism communities. He is the creator and maintainer of GreaterWrong (greaterwrong.com), an alternative frontend for LessWrong built in Common Lisp, and ReadTheSequences.com, an HTML version of Eliezer Yudkowsky's Rationality: From AI to Zombies. From 2017 onward he developed much of the design and interactive JavaScript/CSS infrastructure for Gwern.net, including its popup annotation system, sidenotes, and dark mode. He studied Computer Science (major) and Cognitive Science (minor) at Brooklyn College (CUNY) and conducted summer research at UC Santa Cruz through the SURF-IT program. He has published academic work in human-computer interaction, including research on cursor behaviors and touchless large-display interaction. He received a $60,000 grant from the Long-Term Future Fund for developing and maintaining projects and resources used by the EA and rationality communities. He has been an active LessWrong commenter since 2010 with over 4,500 comments and more than 17,000 karma.
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Raphael “Rafi” Cohen is director of the Strategy and Doctrine Program in RAND Project AIR FORCE, director of the National Security Program at the RAND School of Public Policy, and a senior political scientist and professor of policy analysis at the RAND School. His research spans defense strategy and force planning, Middle East and European security, civil-military relations, and related national security issues.
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Bilal Chughtai is a Research Engineer on the language model interpretability team at Google DeepMind, where he has worked since February 2025 within the broader AGI safety and alignment team. He studied Mathematics at the University of Cambridge, completing his undergraduate degree and a Part III (MMath) in 2021. Before joining DeepMind, he conducted independent mechanistic interpretability research supported by the Long-Term Future Fund, including a project mentored by Prof. David Bau of Northeastern University. He was also a fellow at the MATS (ML Alignment Theory Scholars) program. His notable publications include "A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations" (ICML 2023, co-authored with Lawrence Chan and Neel Nanda) and "Open Problems in Mechanistic Interpretability" (2025, co-authored with Lee Sharkey, David Bau, and over 25 other researchers). His research focuses on understanding the internal mechanisms of neural networks to advance AI safety.
Digital and human rights expert with over 25 years of experience across international development, public policy, civil society, and diplomacy, focused on freedom of expression, technology and democracy, opinion research, peacebuilding, and crisis governance.
Jamie Condliffe is the opinion editor at Transformer, running the publication’s opinion section and commissioning and editing pieces from external authors. He was previously chief content officer at Sifted, executive editor at Protocol and DealBook editor at The New York Times.
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Arran McCutcheon is an effective altruist with an interest in AI governance and policy. Originally from Kilmarnock, Scotland, he holds a postgraduate degree and has lived and worked across multiple countries including China, Portugal, Spain, and Germany. He received a Long-Term Future Fund grant of approximately $6,000 in October 2023 to support part-time work on AI governance projects and activities. He has been active in the EA community since at least 2018, contributing to discussions on AI safety, UK policy, and alignment funding on the EA Forum. He has also posted on the EA Forum about UK government policy opportunities, reflecting an interest in bridging effective altruism with institutional policy work.
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Georgia Bullen is Executive Director of Superbloom (formerly Simply Secure), a nonprofit focused on human‑centered, rights‑respecting technology and usable security and privacy. She has more than two decades of experience at the intersection of usability, design, technology, data, and policy, including leadership roles at New America’s Open Technology Institute and stewardship of the Measurement Lab initiative. Georgia serves as an advisor to TechCongress and is active in the global internet health and digital rights community.
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Max Räuker is a German AI governance researcher and infrastructure builder based in Berlin. He holds a BSc in Biology from Osnabrück University, where he was affiliated with the Institute of Cognitive Science. He worked as a Research Contractor at Rethink Priorities' AI Governance & Strategy team, co-authoring the 2023 expert survey on intermediate goals in AI governance with Michael Aird, which surveyed over 100 longtermism-aligned AI governance practitioners. He is a co-founder of AI Policy Bulletin, a publication providing policy-relevant perspectives on frontier AI governance, and was a 2023 fellow at the Talos Network, which supports European AI policy professionals. More recently, he has been working at Future Matters to shape its AI governance strategy and received funding from the Long-Term Future Fund to maintain and improve an AI governance document sharing hub, providing infrastructure for the field. He has also contributed to field-building projects in AI governance through EA Germany's employer of record program.
Jonathan Gibson is a reporter at The Dispatch based in Washington, D.C., where he covers artificial intelligence and national security. Before joining The Dispatch, he lived in London and completed a bachelor’s degree in politics and international relations at the London School of Economics and Political Science, and he is currently supported by the Tarbell Center for AI Journalism.
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Andis Draguns is a machine learning researcher and Principal Researcher at Contramont Research, a 501(c)(3) nonprofit AI safety research lab. He is also an MS student at the University of Latvia's Institute of Mathematics and Computer Science (IMCS UL) and a MATS alumnus. His research focuses on AI security and alignment, particularly adversarial robustness, cryptographic backdoors in language models, and mechanistic anomaly detection. He co-authored the NeurIPS 2024 paper "Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits," which introduced a novel class of backdoors that defenders cannot trigger even with full white-box access. He received LTFF funding for a project on finding and characterising provably hard cases for mechanistic anomaly detection, a technique aimed at flagging when AI systems produce outputs for anomalous internal reasons.
Dr. John Beieler is the Executive Director of the Applied Research Laboratory for Intelligence and Security (ARLIS) at the University of Maryland, where he leads applied research efforts in areas such as artificial intelligence, quantum computing, human–machine teaming, and social and behavioral sciences for the national security enterprise. Before joining ARLIS, he served as Assistant Director of National Intelligence for Science & Technology and Director of Science and Technology at the Office of the Director of National Intelligence, where he was also the Intelligence Community’s Chief Artificial Intelligence Officer. Earlier in his career, he was a program manager at the Intelligence Advanced Research Projects Activity, a research scientist at the Johns Hopkins Human Language Technology Center of Excellence, and a data scientist at Caerus Associates. He holds a Ph.D. and M.A. in political science from Pennsylvania State University and a B.A. in political science from Louisiana State University.
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Industry 4.0 specialist and Managing Partner at Syndustry, serving as treasurer of the Existential Risk Observatory and overseeing the foundation’s organization and accounting.
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Aaron Gertler is a researcher and writer at 80,000 Hours. Before joining the organisation, he wrote for Coefficient Giving and the Centre for Effective Altruism. In addition to his research and communication work at 80,000 Hours, he has authored numerous articles on effective altruism and high‑impact careers.
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Andy McLoughlin is Managing Partner at Uncork Capital, where he invests in software startups, and he is a co-founder and US Trustee of Founders Pledge. Earlier, he co-founded enterprise collaboration platform Huddle and became a first-money-in angel investor in more than 40 startups. Born and raised in the UK, he holds a BA in economics from the University of Sheffield and was awarded an OBE in 2015 for services to the UK technology industry.
Osmani Redondo is a Madrid-based AI safety educator and community builder who founded AI Safety Madrid and Women4AISafety España, coordinates BlueDot Impact Spain, and co-facilitates Spanish-language ENAIS/AIS Collab cohorts, focusing on making AI safety education accessible for Spanish-speaking professionals.
Simona Gandrabur leads Mila’s AI Safety Studio, drawing on a long career as a pioneer in conversational AI and former head of AI strategy at National Bank of Canada. At Mila she oversees efforts to design safer generative‑AI systems, particularly for sensitive domains such as youth mental health and high‑risk chatbot use.
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Emmett Shear is the CEO and founder of Softmax, an independent research lab on organic alignment. He is a partner at Y Combinator, previously founded and led Twitch as CEO, and briefly served as OpenAI’s “extremely interim” CEO after working as an independent researcher on alignment and agency.
Curriculum Developer & Instructor at the Center for Applied Rationality. John is a software engineer who has worked at Amazon and AI Impacts, was the primary author of the PyMC3 probabilistic programming library, and holds bachelor’s degrees in chemical engineering and paper science and engineering from the University of Washington.
Florian Tramèr is an assistant professor of Computer Science at ETH Zurich and head of the SPY Lab, working on computer security, machine learning and cryptography. His research studies the worst‑case behaviour of deep learning systems from an adversarial perspective to understand and mitigate long‑term threats to users’ safety and privacy; he earned a PhD in computer science from Stanford University under Dan Boneh and subsequently spent a year at Google Brain.
Irene Solaiman is an AI strategist, researcher, and policy expert who serves as Chief Policy Officer and SVP of Strategy at Hugging Face, where she leads company strategy, AI policy, and research on responsible AI. She previously worked on AI and public policy at OpenAI and Zillow and is widely recognized for her contributions to AI safety and governance, including being named an Innovator Under 35 by MIT Technology Review.
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Swaleha Parveen is a Dubai-based AI safety researcher and security engineer specializing in natural language processing and AI-driven cybersecurity solutions, building AI security projects, writing about responsible AI, and speaking publicly about how to design and deploy trustworthy AI systems.
Co-founder of Probably Good and a technology leader who previously headed the Karmel group at Google Research, including the Google Flood Forecasting Initiative providing global flood forecasts, and who now also serves as a venture partner at Firstime and teaches applied ethics and information security at Tel Aviv University.
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Alexander Large received a career transition grant from the Long-Term Future Fund to support job hunting and networking, indicating an interest in moving into x-risk or AI safety-related work. No further public information about their background, current role, or affiliations was found.
Professor Kimberlee Weatherall is a Professor of Law at the University of Sydney, where she specializes in the regulation of technology and intellectual property law and serves as a Chief Investigator in the ARC Centre of Excellence for Automated Decision‑Making and Society and Co‑Director of the University’s Centre for AI, Trust and Governance. She is a Fellow at the Gradient Institute and was a member of the Commonwealth Government’s Temporary AI Expert Group in 2024. Her research focuses on technology regulation—especially AI and automated decision‑making—and on data governance, privacy and the legal implications of data use.
Ezra Karger is an economist at the Federal Reserve Bank of Chicago and co-founder and Research Director of the Forecasting Research Institute, where he develops incentive-compatible methods for forecasting unresolvable questions and runs large-scale expert forecasting studies on topics such as existential risk and the economic effects of AI.