Database

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.

Explainable backs content creators shaping how the world understands AI, running fellowships and campaigns to communicate AI safety research to broader audiences.

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.

Ex product design @ whatsapp, neeva.

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Mythos Ventures is an early-stage venture capital firm investing in prosocial technologies and safe AI systems. They back pre-seed and seed-stage founders building AGI-resilient, positive-impact companies.

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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The ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) is a premier peer-reviewed academic conference that brings together researchers and practitioners to investigate fairness, accountability, and transparency in socio-technical systems.

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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.

An AI safety research lab studying how software and industrial systems recursively improve themselves, building benchmarks and evaluation frameworks to understand the behavior and limits of self-improving AI systems.

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.

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Trying to reduce x-risks from advanced AI through outreach & education

AI safety researcher

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.

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Rubi Hudson: AI Safety Researcher, Economics PhD Student

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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Ammon Bartram is a software engineer and serial founder best known as co-founder and former CEO of the technical hiring platform Triplebyte; he serves on Redwood Research’s board of directors.

Ajay Rayasam is a Principal on the technology investment team at Osage University Partners, focusing on software, computing, and hardware deals, and previously served as Chief of Staff and Product Manager at enterprise software startup Kubisys.

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Christopher (Chris) Akin is the Chief Operating Officer at Apollo Research, where he leads operations and commercial strategy for the organization’s AI safety and evaluations work. He brings prior experience in strategy, operations, and leadership roles at organizations including CLA Consulting, BURN Manufacturing, The Base Project, and Locean Labs.

UC Berkeley's multidisciplinary research center advancing AI safety, agentic AI, and decentralization technology to empower a responsible digital economy.

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Jamie Harris is the Courses Project Lead at the Centre for Effective Altruism, leading a team running online programmes and fellowships that help people explore high-impact ways to help others.

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Joan Gass is the Co‑Founder and Co‑Executive Director of the Horizon Institute for Public Service. She brings extensive experience launching and scaling organizations, including co‑founding a nonprofit in Uganda, helping to start a strategy consulting office in Nigeria, and serving as Managing Director of a global nonprofit. She also sits on the board of the Good Food Institute and has worked on reducing infectious disease burdens and mapping opportunities for impact in the global biosecurity ecosystem. Joan holds an MBA from Stanford Graduate School of Business, an MPA from Harvard Kennedy School, and a bachelor’s degree from Yale University.

Tom Lenaerts is a full professor in the Computer Science department at Université Libre de Bruxelles, where he co-heads the Machine Learning Group focusing on artificial intelligence, computational biology and related areas. He also holds a partial affiliation as a research professor with the Artificial Intelligence Lab at Vrije Universiteit Brussel and is an affiliated researcher at UC Berkeley’s Center for Human-Compatible AI, having previously served in leadership roles such as chair of the Benelux Association for Artificial Intelligence and director of the Interuniversity Institute of Bioinformatics in Brussels.

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