A 10-case pilot using independent review and AI accountability to evaluate inscription claims
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A 10-case pilot using independent review and AI accountability to evaluate inscription claims
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Angelina Wang is an assistant professor of information science at Cornell Tech and in Cornell’s Ann S. Bowers College of Computing and Information Science, where she works on responsible AI. Her research examines the societal impacts of AI, develops methods for evaluating AI systems, and investigates fairness beyond simple, one-size-fits-all mathematical definitions. Previously she was a postdoctoral researcher at Stanford University and completed a Ph.D. in computer science at Princeton University and a B.S. in electrical engineering and computer science at the University of California, Berkeley.
Special Projects Lead at the UK AI Security Institute, working on the societal and ethical implications of advanced artificial intelligence.
3-month stipend and cloud credits to research AI collusion mitigation strategies and develop secure steganography
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Bir ben vardır benden içeri…
Shermon O. Cruz is a Philippine futurist and governance scholar who serves as Executive Director and Chief Futurist of the Center for Engaged Foresight, UNESCO Chair on Anticipatory Governance and Regenerative Cities at Northwestern University (Philippines), and Chair of The Millennium Project’s Philippines Node. His work and teaching focus on futures studies, regenerative cities, and anticipatory governance across government, multilateral, and academic settings.
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Niels uit de Bos is a mathematician and software engineer working in AI safety and mechanistic interpretability. He holds a PhD in mathematics (algebraic geometry and the geometric Langlands program) from the University of Duisburg-Essen, supervised by Jochen Heinloth, and a Master's degree from Leiden University. He completed a research internship in mechanistic interpretability at MATS 5.0 and 5.1 in 2024, mentored by Adrià Garriga-Alonso at FAR.AI (Foundational AI Research). His primary research output from this period is "Adversarial Circuit Evaluation," a workshop paper at the ICML 2024 Mechanistic Interpretability workshop, which evaluated circuits from the interpretability literature adversarially and found that circuits for the IOI and docstring tasks fail to behave similarly to the full model even on benign inputs. He also co-authored "Relating Piecewise Linear Kolmogorov-Arnold Networks to ReLU Networks," published at AISTATS 2025. Prior to AI research, he had over five years of professional software engineering experience at companies including Zopa, G-Research, and Depict (a Y Combinator ML startup).
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Communications and operations director at the Collective Intelligence Project, and a communications strategist and curator working across art, philosophy, community engagement, and technology, with prior roles such as Director of Strategy and Communications at Transformations of the Human and work with organizations including UN‑Habitat and NYU Stern.
Making a simple, easy to read platorm, where alignment plans and their criticisms can be seen and ranked. Currently in Stage 1.
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8-week stipend for a research project supervised by John Halstead, PhD, on US regulatory decision-making and Frontier AI
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Software tools and research to quantify coordination failures and inform policy decisions.
Paul M. Salmon is a professor in Human Factors and is the co-director of the Centre for Human Factors and Sociotechnical Systems at the University of the Sunshine Coast.
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This grant is funding for a 6-month stipend for Sviatoslav Chalnev to work on independent interpretability research, specifically mechanistic interpretability and open-source tooling for interpretability research.
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Keith Strier is senior vice president, global AI markets at AMD, where he leads the company’s global AI strategy, ecosystem development and strategic engagements across public and private sectors. Previously he served as vice president, worldwide AI initiatives at NVIDIA and held senior leadership roles at EY and Deloitte. He has also been active in AI policy, including serving on the U.S. National AI Advisory Committee and as founding chair of the OECD AI Compute and Climate Expert Group.
This grant is for Nathaniel Monson to spend 6 months studying to transition to AI alignment research, with a focus on methods for mechanistic interpretability and resolving polysemanticity.
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12-month salary to transition career into technical alignment research
Youngsook Park is a leading futurist from South Korea who serves as Chair of The Millennium Project’s South Korea Node and has previously been a member of its Board of Directors. After long tenures as information officer at the British Embassy Seoul and director of public diplomacy at the Australian Embassy, she has spent decades bringing global futurists to Korea, including co-organizing the Korea Future Forum.
12-week part-time stipend to research specialized AI hardware requirements for large AI training, with IAPS mentor Asher Brass
Spencer Greenberg is an advisor to Nonlinear, a mathematician and entrepreneur, and the founder of Spark Wave, a startup foundry that creates software products to solve important problems. The Nonlinear team bio notes that he also founded ClearerThinking.org and holds a PhD in applied mathematics from NYU with a specialty in machine learning.
Funding for Computer Science PhD
Kyunghyun Cho is the Glen de Vries Professor of Health Statistics and a professor of Computer Science and Data Science at New York University, co-directs the Global Frontier AI Lab with Yann LeCun, and is a CIFAR Fellow in Learning in Machines & Brains.
Vincent Luczkow is a machine learning researcher and engineer based in the San Francisco Bay Area. He completed his MSc at Mila (Montreal Institute for Learning Algorithms) in 2020, and subsequently pursued a PhD at McGill University under the supervision of Doina Precup and Prakash Panangaden, with a research focus on reinforcement learning and causality. His thesis explored structural causal models for reinforcement learning, introducing approaches to learn minimal causal models of environments at the time-step level. In 2020, he received a $10,000 grant from the Long-Term Future Fund to support research on counterfactual impact minimization, which connects to AI safety work on designing agents that avoid unintended side effects. He has since worked at insitro, a machine learning drug discovery company. He is also active in the forecasting community through Manifold Markets and maintains a personal website and GitHub under the handle vluzko.
Markov Grey is co-founder and CTO of Equilibria Network and the primary author and project developer of the AI Safety Atlas. He contributes across research, writing, distillation, website development, and video creation, and previously worked as a scriptwriter at Rational Animations, a distillation fellow at AISafety.info (Stampy), and in software development and cybersecurity.
Alparslan Bayrak is an effective altruism community builder in Turkey, founding EA Bilkent and EA Ankara, mentoring in the Open Student Program, and working to launch effective animal advocacy projects.
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An Australian charity that conducts policy research and advocates for government action to reduce catastrophic and existential risks, with a focus on AI safety, pandemic prevention, and disaster preparedness.
Maksim Vymenets is an AI safety translator based in Saint Petersburg, Russia. He received a grant from the Long-Term Future Fund to translate AGI safety-related texts, including posts from LessWrong and the AI Alignment Forum, into Russian. His work aims to make AI alignment and x-risk content accessible to Russian-speaking audiences, filling a gap in the availability of such material in Russian. He is active in the rationalist and AI safety community as a LessWrong contributor.
Creating a cinematic AI safety documentary with entertainment value for the public. Need 5k to create trailer & foundational interviews.
Smitha Milli is a Research Scientist at Meta FAIR in the AI & Society group, where their research focuses on pluralistic alignment and collective governance of AI systems. They received both their BS and PhD in Electrical Engineering and Computer Science from UC Berkeley, advised by Anca Dragan and Moritz Hardt, and were supported by an NSF Graduate Research Fellowship and an Open Philanthropy AI Fellowship during their doctoral studies. Prior to Meta FAIR, they were a Postdoctoral Associate at Cornell Tech, supported by the Open Philanthropy Project. During their time at UC Berkeley's Center for Human-Compatible AI (CHAI), Smitha co-authored foundational AI safety papers including "Inverse Reward Design" (NeurIPS 2017) and "Should Robots Be Obedient?" (IJCAI 2017) with Stuart Russell, Anca Dragan, and Dylan Hadfield-Menell. Their current research addresses the gap between engagement-based optimization and socially beneficial objectives in algorithmic systems, with a focus on value-aligned ranking, algorithmic monoculture, and democratic approaches to AI governance. They have received funding from the Long-Term Future Fund for travel to the Symposium on AGI Safety.
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