Database

Daniel Kokotajlo is the co-founder and Executive Director of the AI Futures Project, a nonprofit based in Berkeley, California focused on researching the future impact of artificial intelligence. He studied philosophy at the University of North Carolina at Chapel Hill, where his research focused on formal epistemology, decision theory, and applied ethics, before leaving to work at AI Impacts and then the Center on Long-Term Risk. From 2022 to 2024 he was a governance researcher at OpenAI specializing in scenario planning, and departed in 2024 by refusing to sign a non-disparagement agreement, forgoing approximately $2 million in equity to preserve his ability to speak publicly about AI safety concerns. He is a prolific writer on LessWrong and the Alignment Forum, with over 100 posts covering AI timelines, takeoff speeds, decision theory, and existential risk from advanced AI. He co-authored the landmark scenario forecast AI 2027 (published April 2025 with Scott Alexander and others), projecting rapid progress toward AGI by the end of 2027, and was named to TIME's TIME100 AI list in both 2024 and 2025.

John Bridge is a legal researcher affiliated with the effective altruism community who received a grant from the Long-Term Future Fund to research the international viability of FHI's Windfall Clause, a policy proposal by the Future of Humanity Institute for AI developers to commit a portion of transformative AI profits to public benefit. At the time of his research, he identified as a law student. He wrote a sequence on the EA Forum titled "Towards a Worldwide, Watertight Windfall Clause" examining the legal enforceability of the Windfall Clause across seven common law jurisdictions. His published posts (May-June 2022) include analyses of inadequate contractual remedies and the challenges English law poses for good-faith obligations in AI governance agreements. He shelved the project in 2023 due to competing research demands. His work was acknowledged by Cullen O'Keefe and Haydn Bellfield, key figures in the GovAI and FHI Windfall Clause research.

Rachel Shu is the Director of Mox, an AI safety community hub in San Francisco’s Mission District, where she focuses on venue operations and community-building for researchers, engineers, and policymakers working on high-stakes questions in technology. She also works on writing and documentary projects, including cinematography for the film “SB 1047: The Battle for the Future of AI” and an Open Philanthropy–funded documentary on high-impact COVID responses.

Jack Clark is a co-founder and Head of Public Benefit at Anthropic, where he leads work at the intersection of AI policy, governance, and public benefit, and he writes Import AI, a weekly newsletter on frontier AI research and its societal implications. He previously served as Policy Director at OpenAI and, before entering AI labs, worked as a technology journalist covering supercomputers, distributed systems, and neural networks for outlets including Bloomberg BusinessWeek and The Register, as well as helping found and co-chair the AI Index at Stanford and serving on national and international AI advisory bodies.

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Rui Zhang is an Assistant Professor in the Computer Science and Engineering Department at Penn State University and a co-director of the Penn State Natural Language Processing Lab. His research focuses on trustworthy human-centered AI, LLM agents, and AI for science, and he has received recognitions including an NSF CAREER Award, a Senior Area Chair Paper Award at NAACL 2025, and an Outstanding Area Chair Award at EMNLP 2024. He is the principal investigator of an Open Philanthropy–funded project at Penn State to better mitigate sandbagging in AI models, studying behaviors such as exploration hacking and password-locking.

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Pip Foweraker is CEO of Beacon, a 501(c)(3) fiscal sponsorship agency focusing on catastrophic and existential risk, and Executive Director of Research at the Certes Institute, working on infrastructure and support for AI safety and other existential risk research.

Honours student at Deakin University focusing on transferring safety knowledge between environments using multi-objective reinforcement learning, with prior experience as a research assistant on several machine learning projects at both Deakin University and Federation University.

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Darren McKee is a Canadian author, senior policy advisor, and AI safety communicator based in Ottawa, Ontario. He holds an MSc in Experimental Psychology and a Master of Public Administration with a Global Governance concentration. McKee has served as a senior policy advisor in the Canadian federal government for over 15 years, working across domains including science and technology, behavioural science, and foresight, with roles at the Privy Council Office and Treasury Board of Canada Secretariat. He is the author of Uncontrollable: The Threat of Artificial Superintelligence and the Race to Save the World (2023), a beginner-friendly book on AI risk and safety that received endorsements from Max Tegmark, Will MacAskill, and Roman Yampolskiy, and became a number-one bestseller. McKee also co-authored a chapter on AI and autonomy in Westworld Psychology (2021) and serves as an advisor to AIGS Canada (Artificial Intelligence Governance and Safety Canada). He is the host of The Reality Check, an award-winning skepticism and critical thinking podcast ranked in the top 0.5% of podcasts globally with over 4 million downloads.

Megan Stifel is Chief Strategy Officer at the Institute for Security and Technology, where she leads organizational strategy and cyber‑related work, and is the founder of Silicon Harbor Consultants, a firm providing strategic cybersecurity operations and policy counsel after earlier service as an attorney in the U.S. Department of Justice National Security Division.

Nicholas Greig is a researcher who has worked on neural network interpretability in the context of AI safety. He received a grant from the Long-Term Future Fund (LTFF) for neural network interpretability research, indicating engagement with the EA-adjacent AI safety community.

Wendy Schmidt is an American philanthropist and investor who serves as president and co-founder of the Schmidt Family Foundation and Schmidt Ocean Institute and has created and led multiple philanthropic initiatives focused on clean energy, resilient food systems, healthy oceans, human rights, and scientific research, including the 11th Hour Project, Schmidt Marine Technology Partners, 11th Hour Racing, Remain, and Schmidt Sciences.

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Joar Skalse is an AI safety researcher who completed his DPhil in Computer Science at the University of Oxford in 2025, supervised by Professor Alessandro Abate and supported by the Future of Humanity Institute. He received his BA and MCompPhil in Computer Science and Philosophy at Oxford, graduating top of year. His doctoral research focused on safe reinforcement learning, reward learning, and misspecification, with particular emphasis on formally defining and characterizing reward hacking. He is best known for co-authoring the influential mesa-optimizers paper ("Risks from Learned Optimization in Advanced Machine Learning Systems") as an undergraduate, and for his NeurIPS 2022 paper "Defining and Characterizing Reward Hacking". His work also includes contributions to mechanistic interpretability, the STARC framework for comparing reward functions, and the "Towards Guaranteed Safe AI" framework. He has been affiliated with FAR AI as a researcher and is co-founder and CEO of Deducto Limited, a startup applying reinforcement learning. He received a $10,000 grant from the Long-Term Future Fund in 2019 to upskill in machine learning and accelerate his contributions to AI safety research.

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Victor Shepardson is a co-founder of the Berryville Institute of Machine Learning and a machine learning researcher and engineer whose work spans deep learning, music and interactive systems, including roles at Ntrepid and the University of Iceland’s Intelligent Instruments Lab. He co-authors BIML’s foundational papers on security engineering for machine learning and architectural risk analysis of ML systems.

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Daniel Barcay is the executive director of the Center for Humane Technology and a co‑host of the podcast Your Undivided Attention. A technologist and former vice president of product at Planet Labs, he now focuses on how powerful technologies reshape human psychology, relationships, and control, drawing on experience in software engineering, strategy, and research fellowships.

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Kane Nicholson is a Machine Learning Engineer at Leonardo AI (a Sydney-based generative AI platform acquired by Canva in 2024), based in Australia. He holds a Bachelor of Engineering from Queensland University of Technology (QUT) in Brisbane. Prior to his ML career, he worked as a Software Engineer at Reel Time Gaming and as a Programming Tutor at QUT Law Society. He received a Long-Term Future Fund grant equivalent to six months of salary to fund a career transition and upskilling period with the goal of entering AI safety work. Following this upskilling grant, he transitioned into machine learning engineering at Leonardo AI.

Scott Singer is a co-founder and strategic leader of the Oxford China Policy Lab and a fellow in the Technology and International Affairs Program at the Carnegie Endowment for International Peace, where he works on global AI development and governance with a focus on China. His research and policy work centre on US–China AI relations, structural risks in the US–China relationship, and emerging technology governance, and he has contributed to landmark reports including the California Report on Frontier AI Policy and the International AI Safety Report. Scott holds a PhD in International Relations from the University of Oxford, where he was a Clarendon Scholar, and previously worked for the U.S. State Department and U.S. Senate.

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David Teter works with donors and partners at Open Philanthropy’s successor organization Coefficient Giving on high‑leverage work in AI and biosecurity; before joining, he helped start Ergo Impact, built a grants function at Effective Giving, and previously worked at BlackRock on long‑term growth and strategy.

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Aryeh Englander is a mathematician and AI researcher at the Johns Hopkins University Applied Physics Laboratory (APL), where he focuses on AI safety and AI risk analysis. He is also pursuing a PhD in Information Systems at the University of Maryland, Baltimore County (UMBC), with research centered on decision and risk analysis under extreme uncertainty, particularly regarding potential existential risks from very advanced AI. In 2021, he received a $100,000 grant from the Long-Term Future Fund to replace income lost from reducing to half-time at APL in order to pursue his doctorate, with the rationale that a PhD would position him for greater leadership and influence over AI safety practices at a major federal research institution. He is a co-leader of the Modelling Transformative AI Risks (MTAIR) project alongside David Manheim and Daniel Eth, and co-authored the paper TanksWorld: A Multi-Agent Environment for AI Safety Research. Englander is an active contributor to the AI Alignment Forum, LessWrong, and EA Forum communities.

Matt Beard is an advisor at 80,000 Hours, where he provides one‑on‑one career advising focused on high‑impact paths, especially in AI governance and policy. Before joining 80,000 Hours he worked as a legislative staffer on Canada’s National Security Committee, managed a Member of Parliament’s legislative office, and held policy analyst and grantmaking roles in the Canadian civil service. He holds an MA in political science and is based in Washington, DC.

Sören Mindermann is a machine learning researcher and AI safety scientist currently based in Montreal, where he is a postdoctoral researcher at Mila (Quebec Artificial Intelligence Institute) under Yoshua Bengio. He completed his DPhil (PhD) in machine learning at the University of Oxford (2019-2023), supervised by Yarin Gal at the OATML group and Allan Dafoe at the Centre for the Governance of AI, co-funded by Oxford and Google DeepMind. He also holds degrees in machine learning from UCL and in mathematics and Future Planet Studies from the University of Amsterdam. He served as the Scientific Lead of the first International AI Safety Report (2025), a comprehensive review of AI capabilities and risks backed by 33 nations, and is a Research Affiliate at the Oxford Martin AI Governance Initiative. His research covers AI safety evaluations, large language model honesty, data selection for large-scale deep learning, causal inference, and health applications of machine learning. Notable publications include co-authorship on "The Alignment Problem from a Deep Learning Perspective" (ICLR 2024), "Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training" (2024), and "Managing Extreme AI Risks amid Rapid Progress" (Science, 2024), as well as influential COVID-19 policy intervention studies published in Science and Nature Communications. He received funding from the Long-Term Future Fund for his AI strategy PhD at Oxford/FHI.

Professor Julia Powles is the Executive Director of the UCLA Institute for Technology, Law & Policy at UCLA School of Law and UCLA Samueli School of Engineering, and Tech Policy Lead for the university-wide UCLA DataX initiative. Her research and teaching focus on privacy, intellectual property, internet governance, and the law and politics of data, automation and artificial intelligence.

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Kayla Blomquist is the Co-founder and Executive Director of the Oxford China Policy Lab and a DPhil researcher at the Oxford Internet Institute, specialising in AI governance, US–China relations, and international technology competition. She previously served as a U.S. diplomat in China, focusing on governance of emerging and dual-use technologies, human rights, and the use of new technology in government services. Kayla’s academic background includes an MSc from the Oxford Internet Institute and a BA with honours in International Relations, Public Policy, and Mandarin Chinese from the University of Denver, and she is professionally fluent in Mandarin.

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Martin Tisné is the chief executive officer of the AI Collaborative, an initiative of The Omidyar Group created to ensure that artificial intelligence is governed in the public interest. A longtime philanthropic entrepreneur, he previously led the Data & Digital Rights impact area at Luminate and helped found multistakeholder initiatives such as the Open Government Partnership and other transparency-focused NGOs.

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Nikhil Kunapuli is an independent researcher and currently Head of Research at Praxis, a company focused on building innovative urban environments, a role he has held since September 2022. He holds a B.S. in Physics from MIT (2014-2018) and an M.S. in Physics from the University of Illinois Urbana-Champaign (2022). Earlier in his career, he co-founded Luminous Computing, an AI hardware startup, serving as COO from 2018 to 2019, before departing to pursue direct AI safety work. He conducted research at the New England Complex Systems Institute (NECSI) and received a $30,000 Long-Term Future Fund grant in April 2019 for independent AI safety deconfusion research, specifically studying safe exploration and robustness to distributional shift through the lens of biological complex systems and theoretical biology. His approach sought to generate insights applicable to AI safety by examining how natural organisms and ecosystems handle robustness and exploration challenges. He also writes a personal Substack, Inspired Nonsense, covering AI, physics, and philosophy.

Software engineer with a mix of practical industry experience and formal qualifications whose research interests include software development methodologies and ethics for artificial intelligence systems, and who is listed as a researcher with ARAAC.

Charlie Steiner is an independent AI alignment researcher based in Boston, MA, focused on the problem of value learning. He holds a PhD in condensed matter physics and transitioned into AI safety research, where he works on making conceptual progress on value learning and translating that progress into experiments using language models and model-based reinforcement learning. A particular focus of his work is how to translate values and policies between different learned ontologies, with the goal of modeling human preferences—including higher-order preferences—in a principled rather than ad hoc way. He is an active contributor to LessWrong and the Alignment Forum (where his LW 1.0 username was Manfred), with over 75 posts and significant community engagement. He has received funding from the Long-Term Future Fund for a 12-month independent research salary to pursue value learning research. He also appears on the Future of Life Institute's community pages as an independent researcher in the AI safety space.

Devon Fritz is the co-founder of the nonprofit High Impact Professionals and author of The High-Impact Professional’s Playbook. He has spent nearly a decade coaching professionals on maximizing their career impact and advising on strategic philanthropic giving, and previously served as Chief Operating Officer at Ambitious Impact. His background includes software development and degrees in computer science, information technology, and computational linguistics.

Co-founder of Compassion in Machine Learning (CaML), working on AI safety and alignment methods such as synthetic pretraining data so that future AI systems show robust compassion toward all sentient beings, including non-humans.

Associate Professor and Head of Information Technology within the Institute of Innovation, Science and Sustainability at Federation University Australia, whose research focuses on multi-objective reinforcement learning, safe and explainable AI, and digital health, and who is an active member of the Australian Responsible Autonomous Agents Collective (ARAAC).

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