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Clear filtersLorenzo 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.
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Clear filters to view everything →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.
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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.
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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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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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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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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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George Green is an open-source intelligence (OSINT) researcher who received funding from the Long-Term Future Fund to support living costs during an additional semester in the US and to purchase OSINT equipment and software. The grant suggests involvement in intelligence research with potential relevance to existential risk or AI safety topics, though further details about this individual's affiliations and work are not publicly available.
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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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Gavin J. Taylor is a researcher affiliated with the Institute for Globally Distributed Open Research and Education (IGDORE), based in São Carlos, Brazil. He studied at the University of Queensland and consults for Resonant Health Inc., a company developing a medical device using low-dose microwaves for antiviral applications. His research focuses on physical virology, microwave viral inactivation, optical simulations, and Micro-CT imaging. In 2020, he received a $30,000 grant from the Long-Term Future Fund to conduct a computational study on using a light-to-vibrations (L2V) mechanism as a targeted antiviral, with the aim of identifying viruses susceptible to inactivation via resonant vibrational frequencies. He has published peer-reviewed work including a 2024 paper in Applied Physics Reviews on virus inactivation by matching vibrational resonance, and a 2023 comment in Viruses correcting mathematical errors in SARS-CoV-2 microwave inactivation research. His work is recognized as providing a mathematical model for predicting microwave frequencies effective for viral inactivation.
Charbel-Raphaël Segerie is Executive Director and co-founder of CeSIA, the French Center for AI Safety, and an OECD AI expert. His bio notes that CeSIA is part of the EU AI Office’s evaluator consortium for the Code of Practice on harmful manipulation risks, and that he helped initiate and co-lead the Global Call for AI Red Lines, an international campaign for binding limits on catastrophic AI risks.
Chana Messinger is Head of Video at 80,000 Hours and leads the team behind the AI In Context YouTube channel. She is an effective altruist and rationalist with a background in writing and education, and has been experimenting with short‑form and long‑form video to communicate the risks of transformative AI and what people can do about them. In addition to her work at 80,000 Hours, she maintains a personal blog and online presence discussing reasoning, ethics, and AI.
Bálint Árpád Pataki is a Senior Advanced AI Policy Researcher at the Centre for Future Generations (CFG), based in Brussels, where he focuses on EU artificial intelligence innovation policies and communicates research findings directly to policymakers. He holds an MPP from the Blavatnik School of Government at the University of Oxford (Green Templeton College, class of 2022) and an undergraduate degree in Public Policy and Economics from Leiden University College. He previously worked as an Accredited Parliamentary Assistant for MEP Eva Maydell, contributing to EU AI Act negotiations and advising on EU AI, biotechnology, and quantum policies. His research and advocacy have focused on supporting the European Commission's work on establishing a CERN-for-AI initiative — an international public-private partnership for trustworthy frontier AI development — and his work has been featured in Euractiv, Tagesspiegel, Science Business, Parliament Magazine, and Tech Policy Press. He has lectured at Oxford, Cambridge, and Leiden universities and briefed US Congressional staffers on EU AI policy developments. He participated in the ML Safety Scholars program while studying AI policy at Oxford.
Daniel is a Senior Growth Specialist at Giving What We Can, helping connect more people with the 10% Pledge and effective giving by working across the digital product and marketing experience. Before joining GWWC, he co‑founded an online school and resource platform for facilitators, focusing on brand, website and product experience, and since moving from Germany to the Netherlands in 2020 he has been active in the Dutch effective altruism community.
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Operations and community-building specialist with a Master’s degree in cognitive psychology. She joined EA Hungary in 2024, where she plays a key role in operations and course facilitation, and also supports AI Safety Hungary as an operations advisor.
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