Database

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A high-level international dialogue series that brings together leading AI scientists and governance experts to build consensus on managing extreme risks from frontier AI systems.

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Advisor & Groups Lead at Probably Good with over a decade of experience in social impact, including nonprofit leadership, capacity-building, and philanthropic advising, and former director of a regional nonprofit helping people align their careers, time, and donations with impact.

Engineer at Fifty Years focused on deepening the firm’s AI tooling to identify and support the next generation of indispensable founders; previously led Data Science at Dyson, shipping production AI systems across multiple domains, and before that worked at Sky, BAE Systems, and Fidessa on data science and mission‑critical trading software.

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Technical University of Munich (TUM) is one of Europe's leading research universities, with significant AI safety and reliable AI research programs including the Konrad Zuse School of Excellence in Reliable AI (relAI).

Founding Generalist at Kairos leading internal operations and grantmaking logistics, previously working in operations at METR and Open Philanthropy on nonprofit and grantmaking compliance, HR, and other administrative functions, with a background in community building and event planning.

Nathan Labenz is a technology entrepreneur and artificial intelligence analyst based in Detroit, Michigan. He is the founder and former CEO of Waymark, a generative AI-powered video advertising company, and has led it from inception to becoming a prominent example of applied generative AI. Nathan now focuses on AI full time as an "AI scout" and hosts The Cognitive Revolution podcast, where he explores how advances in AI are transforming work, society, and culture through in-depth interviews and analysis.

Czech national organization promoting effective altruism through community building, events, and project incubation, with a particular focus on AI safety and high-impact careers.

Matteo Pistillo is a Senior AI Governance Researcher and Advisor at Apollo Research, where he conducts technical governance and AI policy research focused on evaluations, internal deployment, loss‑of‑control risks, and security‑relevant standards for frontier AI systems. Before working full‑time in AI governance, he practised as an international commercial disputes lawyer at Cleary Gottlieb Steen & Hamilton and specialised in technology regulation as a Fulbright Scholar at Stanford Law School.

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Computational cognitive scientist @ Princeton, studying introspection in LLMs.

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ML4Good runs intensive, fully-funded in-person bootcamps to train motivated people for careers in AI safety, covering both technical and governance tracks.

American meditation teacher and researcher in awakening, author of The Science of Enlightenment and Natural Pain Relief, and creator of the Unified Mindfulness system, which has been used in collaborations with institutions such as Harvard Medical School, Carnegie Mellon University, and the University of Vermont in contemplative neuroscience research.

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I like tweaking LLMs to understand their working

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Rory Gillis is a UK-based AI policy professional currently serving as Senior Policy Adviser (AI International) at the UK Department for Science, Innovation and Technology (DSIT), where he focuses on the UK's international engagement on artificial intelligence. He holds an MPhil in Political Theory from the University of Oxford (Mansfield College) and a BSc in Politics and Philosophy from the London School of Economics and Political Science. Prior to joining DSIT, he worked as a Research Assistant and Project Support Officer at the Oxford Internet Institute, contributing to the Governance of Emerging Technologies (GET) programme under Professor Brent Mittelstadt and Professor Sandra Wachter. In that role, he co-authored written evidence submitted to UK parliamentary committees on AI regulation and co-authored the 2024 paper "Trust and Trustworthiness in Artificial Intelligence" (with Johann Laux and Brent Mittelstadt), which examines philosophical frameworks of trust and proposes recommendations for AI governance debates. He received a small research grant to map and offer a preliminary assessment of AI ideal governance research, reflecting his early-career focus on understanding the landscape of normative AI governance scholarship.

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Nicolas Papernot is a computer scientist whose work focuses on the security and privacy of machine learning. He is a Canada CIFAR AI Chair based at the Vector Institute and a faculty member at the University of Toronto, and he serves as Co-Director of the Canadian AI Safety Institute Research Program at CIFAR.

Nick Raushenbush is a founder, investor, and advisor to tech startups who co-founded the software company Shogun and the creative agency Glass + Marker, runs a small fund investing in Y Combinator companies, and advises startups as an operating partner at Halcyon.

Joseph Bloom is a mechanistic interpretability researcher who co-founded Decode Research / Neuronpedia and led development of the SAELens library for training sparse autoencoders. He is now Head of White Box Evaluations (model transparency) at the UK AI Security Institute, and has co-authored prominent work including Open Problems in Mechanistic Interpretability, SAEBench, and "Sparse Autoencoders Do Not Find Canonical Units of Analysis." Before joining AISI he worked as an independent AI safety researcher focusing on decision transformer interpretability.

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Peter Ruschhaupt is a researcher and policy analyst with a background in electrochemical energy storage, who has been exploring a transition into AI governance. He holds a PhD from the Karlsruhe Institute of Technology (KIT) and Helmholtz Institute Ulm (HIU), where his research focused on binders and electrolytes for supercapacitors, and an MSc from Friedrich-Alexander University Erlangen-Nuremberg (FAU). He worked as a Cleantech Analyst at Future Cleantech Architects (FCA), a climate innovation think tank based in Germany, where he contributed to research and policy analysis on industrial decarbonization and energy storage. He received a grant from the Long-Term Future Fund to spend three months exploring career options in AI governance, including upskilling, networking, producing work samples, and applying for relevant positions.

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The Schwartz Reisman Institute for Technology and Society (SRI) is a University of Toronto research institute that convenes experts across disciplines to ensure that powerful technologies like AI are responsible, inclusive, and beneficial to everyone.

Armielyn Obinguar is Chief Technology Officer and co‑founder of Safe, a fintech startup building escrow‑as‑a‑payment tools, and an AI community leader in Southeast Asia. She was recognized as a Women in AI APAC AI Humanitarian finalist in 2023 and collaborates with organizations such as UNICEF, the ITU and UNDP on projects that use AI to broaden access to education and promote inclusive development.

Founding Dean of Deep Science Ventures’ College, where he leads the Venture Science Doctorate, a three-year fully funded PhD program training commercially minded scientists to build moonshot companies addressing global challenges.

Joseph Gordon-Levitt's collaborative media platform, which established a dedicated AI safety arm (HitRecord AI Safety Project LLC and AI Safety Digital Media Fund) to use storytelling and public engagement to address AI risks.

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Acting Director at AI Impacts, research engineer at Palisade

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Vass Bednar is a CIGI senior fellow and managing director of the Canadian Shield Institute whose work sits at the intersection of technology and public policy; she previously led McMaster University’s MPP in Digital Society program and writes the "regs to riches" policy newsletter.

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A Washington, DC-based 501(c)(3) nonprofit that conducts AI policy research, develops actionable legislative proposals, and educates U.S. policymakers on responsible innovation. It is the research and education arm of the Americans for Responsible Innovation family of organizations.

Alex is a Community Engagement Coordinator at Giving What We Can, growing the community of pledgers through high‑touch personal outreach and one‑on‑one relationships and helping people explore what meaningful impact looks like for them. Before joining GWWC, he spent a year focused on personal development through travel, entrepreneurship and volunteer work, launched his own business, and gained experience at Natixis Investment Managers during his placement year. He holds a First Class Honours degree in International Relations from Loughborough University.

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Dr. Jan Kinne is a researcher in the Economics of Innovation and Industrial Dynamics unit at ZEW – Leibniz Centre for European Economic Research in Mannheim and co-founder and CEO of ISTARI.AI, where he develops AI-based web-mining methods for firm- and innovation-level analysis. He studied geoinformatics at Heidelberg University and Loughborough University and earned a doctorate (Dr. rer. nat.) from the University of Salzburg on web-based innovation indicators.

Independent Researcher

Jack Wildman is a senior software engineer at FutureSearch. He holds a PhD in Materials Physics from Heriot-Watt University and previously worked as a senior software engineer at Metaculus and as a development team lead at Ito World.

Reporting and analysis on capitalism, great power competition, and the race to build machine superintelligence by freelance journalist Garrison Lovely.

Arjun Panickssery is an AI safety researcher and entrepreneur based in the San Francisco Bay Area. He studied at the University of Illinois at Urbana-Champaign and has been active in AI alignment research through multiple programs and institutions. He participated in MATS (Machine Learning Alignment Theory Scholars), including an extension phase in London, where his research on the safety implications of LLM self-recognition produced the widely-cited paper "LLM Evaluators Recognize and Favor Their Own Generations" (co-authored with Samuel R. Bowman and Shi Feng), which demonstrated that frontier models such as GPT-4 can recognize their own outputs and exhibit self-preference bias that could undermine safety techniques like reward modeling and constitutional AI. He subsequently worked on scalable oversight benchmarks as part of MATS Summer 2024 and previously held roles at METR Evals and an AI risks organization. He is also building Zembla, an AI-powered platform for accelerated, individualized learning, and writes frequently about AI tutoring and education research.