Adam Goldstein is a co-founder of Softmax and serves as a board member and founder emeritus, after co-founding the travel startup Hipmunk and working as a visiting scientist in Michael Levin’s lab at Tufts on cell signaling, bioelectricity, and basal cognition; he is also described as Co-founder, Chairman, and Head of Research for Softmax in external profiles.

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Alexander Iosad is Director of Government Innovation Policy at the Tony Blair Institute for Global Change, leading policy research on governing in the age of AI and how political leaders can use digital technologies to improve public services. He has deep expertise in education policy, has worked with ministers and international agencies across Africa and Europe, previously worked in edtech venture capital and public-sector innovation consulting, and holds a DPhil in history of science from the University of Oxford.

NLP researcher and data scientist with experience at Stanford University’s School of Engineering, Pr(Ai)2R Group, and Microsoft, focusing on understanding how AI models learn and process language.

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Anna Ek has served as a career counselor for Effective Altruism Sweden, supporting the organisation’s career support and coaching programmes for people seeking higher‑impact work.

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Mike McCormick is the founder and CEO of Halcyon Futures, a nonprofit grant fund and venture capital fund dedicated to ensuring that AI is developed in ways that are safe, secure, and beneficial for humanity, and he serves as a board member at the AI Verification and Evaluation Research Institute (AVERI).

Executive Director of the Safe AI Forum (SAIF). Previously a research scholar at the Centre for the Governance of AI (GovAI) studying technical AI progress and AI policy in China, and a researcher on Chinese data and technology policy at Sinolytics, Trivium China, and the Mercator Institute for China Studies; he holds a BA in Politics, Philosophy and Economics from the University of Warwick.

Assistant Professor of Computer Science at the University of Rhode Island and director of the ML4STS Lab, previously a Data Science Initiative postdoc at Brown University and a Chancellor’s Postdoctoral Fellow at UC Berkeley, with BS, MS, and PhD degrees in electrical/electrical and computer engineering from Northeastern University.

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Peter Schmidt-Nielsen is a hardware and machine learning engineer working on FPGA-accelerated servers at Saturn Data, building high-memory, high-bandwidth systems for workloads such as vector search. He previously worked as an ML engineer at Redwood Research and is a co-author of the NeurIPS 2022 paper "Adversarial Training for High-Stakes Reliability" on adversarial training methods for high-stakes AI reliability.

Danielle Goldfarb is a CIGI senior fellow and economist specializing in trade, real‑time data and the digital economy; she co‑directs the Canadian AI Adoption Initiative and holds fellowships at the Munk School of Global Affairs and Public Policy and the Asia Pacific Foundation of Canada.

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Academic at Deakin University’s School of Information Technology whose research spans reinforcement learning and related areas, officially affiliated with the Machine Intelligence Lab and the Australian Responsible Autonomous Agents Collective (ARAAC), and who serves on program committees or as area chair for major AI conferences such as NeurIPS and AAMAS.

Mario Peng Lee is an AI engineer at nexos.ai, a Vilnius-based enterprise AI platform, where he works on AI orchestration. He graduated from UCLA in 2024 with degrees in Linguistics and Computer Science and Psychology, and a minor in Data Science Engineering. Born in Chile to Taiwanese parents and raised in China, Taiwan, and Argentina, he is fluent in three languages. At UCLA he co-founded AI Safety at UCLA in 2022, a student research community that grew to over 100 members within a year and received funding from Open Philanthropy; the group developed its own AI safety curriculum and incubated student-directed projects. He also conducted undergraduate research in machine learning behavioral interpretability and natural language processing, co-authored a paper on the Diverse Names Generator in the Proceedings of the Linguistic Society of America, and co-organized a UCLA EA AI Timelines Retreat. He received a grant from the Long-Term Future Fund to cover tuition for the Stanford Artificial Intelligence Professional Program as well as funding for AI safety research in Berkeley.

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Negar Rostamzadeh is a Staff Research Scientist on Google’s Responsible AI team and an Associate Industry Member at Mila. Her work examines the social implications of machine learning and evaluation systems and develops equitable, fair ML models, including creative computer‑vision applications with societal and artistic impact.

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Nick Perlman is an editor and video editor working with 80,000 Hours’ studio team. Based in New York, he has prior experience editing and producing video content for clients including America’s Test Kitchen and independent film projects, and now focuses on editing long‑form and short‑form content for 80,000 Hours’ podcasts and videos.

Julia Stoyanovich is an Institute Associate Professor of Computer Science and Engineering at NYU Tandon, Associate Professor of Data Science at the NYU Center for Data Science, and Director of NYUs Center for Responsible AI, with research focusing on responsible data management and the societal impacts of AI.

Received a grant from the Long-Term Future Fund for living expenses while working to establish a broad-spectrum antiviral research organization focused on biosecurity. Further details not publicly available.

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Mordechai Rorvig is a science journalist and founder of Foom Magazine, an independent, ad-free publication covering research on AI safety and ethics. He was previously a staff writer at Quanta Magazine covering computer science and AI, a role he left in August 2022 to pursue independent journalism. He holds a master's degree in physics from the University of Wisconsin, where he conducted fusion device research, and a bachelor's degree in mathematics from the University of Texas. His freelance writing has appeared in Scientific American, Wired, Vice, New Scientist, Nautilus, and IEEE Spectrum, among others. He received a $110,000 grant from Open Philanthropy in November 2022 to support independent journalism on computer science, AI, and AI safety, and additional funding from the Long-Term Future Fund to launch Foom Magazine. He is also working on a book project titled "AI: How We Got Here—A Neuroscience Perspective," which explores connections between neuroscience research and the development of modern AI systems.

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Clinical and research psychologist with over a decade of specialization in psychedelic medicine and integrative healthcare, with expertise in ibogaine and 5‑MeO‑DMT, neuropsychology, psychotherapy and psychedelic-assisted therapies.

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Research scientist at Truthful AI; previously a member of technical staff on Anthropic’s alignment team; currently on leave from a PhD in computer science at UC Berkeley, supervised by Stuart Russell.

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Dr. Ysaline Bourgine de Meder is a medieval historian who now serves as Head of Strategy at Effective Altruism Sweden, where she applies her analytical and strategic skills to AI governance and policy work.

Jugal Patel is the COO and Co-Founder of Leap Laboratories, based in San Francisco, California. According to his Crunchbase profile he previously worked at Balance.io as an Operations Lead and studied Business Administration and Finance at San Francisco State University.

Vanessa Kosoy is an AI alignment researcher based in Israel, currently serving as Director of AI Research at ALTER (Association for Long Term Existence and Resilience) and Research Lead at CORAL (Computational Rational Agents Laboratory), while pursuing a PhD in Mathematics at the Technion – Israel Institute of Technology under Shay Moran. She holds a BSc in Pure Mathematics from Tel Aviv University and an MSc in Computer Science from the Hebrew University of Jerusalem, and spent over 15 years in software engineering roles including algorithm engineer, R&D manager, and startup founder before transitioning to AI safety research full-time roughly a decade ago. She was previously a research associate at the Machine Intelligence Research Institute (MIRI) and has been funded by the Long-Term Future Fund (LTFF). Her research centers on the learning-theoretic AI alignment agenda, and she is best known for developing Infra-Bayesianism (with co-author Alex Appel), a mathematical framework for handling non-realizability in reinforcement learning, as well as Infra-Bayesian Physicalism (now called Formal Computational Realism), which addresses naturalized induction. She has been a mentor in the MATS (ML Alignment Theory Scholars) program, running a track focused on the learning-theoretic agenda, and is a prolific contributor to the AI Alignment Forum and LessWrong.

Junior Research Scholar at ILINA and a Researcher at the University of Cape Town African Hub on AI Safety, Peace and Security, conducting Africa‑centric model safety evaluations; he previously served as a Junior Research Fellow at ILINA (technical governance track), completed the AI Safety Fundamentals technical track and the ALX Software Engineering program, and holds a law degree from Kabarak University plus a postgraduate diploma from the Kenya School of Law.

Research Associate and Head of Policy at ILINA, working on governance of AI in Global South countries and the governance of AI agents, with prior experience as an AI Futures Fellow and visiting researcher at the Centre for the Study of Existential Risk; she holds law degrees from Strathmore University and Columbia Law School.

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Geoffrey Hinton is a Director of The AI Safety Foundation and a pioneering British-Canadian researcher in artificial intelligence whose work on neural networks helped launch the deep learning revolution. He is Professor Emeritus at the University of Toronto and a 2024 Nobel Laureate in Physics for contributions to the theory and practice of artificial neural networks, and he now devotes much of his work to understanding and communicating the long-term safety risks of advanced AI systems.

Tyler Whitmer is the founder and CEO/President of Legal Advocates for Safe Science and Technology (LASST), a 501(c)(3) nonprofit that uses legal advocacy to make advances in science and technology safer for people and the planet. He previously spent over 15 years as an associate and then partner at Quinn Emanuel Urquhart & Sullivan, LLP as a commercial litigator, and later served as the first general counsel of a 501(c)(3) public charity before leaving that role at the end of 2023 to start LASST.

Tom David is President of the GPAI Policy Lab, a Campus Cyber–based policy lab that fosters international cooperation on general-purpose AI security and control through research, strategic advising, and training, and he is also co-founder of PRISM Eval, which specializes in stress-testing generative AI models on critical behaviors.