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Clear filters to view everything →Kauna Ibrahim Malgwi is a Nigerian clinical psychologist, mental health advocate, and digital-labor organizer whose work spans mental health, AI, and ethics. She founded the Digital Rights and Mental Health Initiative and has helped lead organizing efforts for African content moderators, including the Content Moderators Union in Nigeria. Her advocacy on algorithmic trauma and fair working conditions for digital workers has received international recognition, including being named to TIME’s 2024 TIME100 AI list.
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Co-founder of Impact Ops and operations leader based in Berlin; previously Head of People Operations at Effective Ventures and a graduate in Environmental Science from the University of Freiburg, with a focus on supporting high-impact organizations.
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biosecurity
Believer in Freedom and Love.
Baseemah “Bee” Nance, CPA, is a finance executive, educator, and content creator who has served as a chief financial and administrative officer and teaches accounting at Central Piedmont Community College. She leverages her accounting expertise to promote financial literacy and helps individuals and organizations address money mindsets and build stronger financial foundations.
Independent AI Safety Researcher
Børge Brende is a Norwegian politician and diplomat who served as President and Chief Executive Officer of the World Economic Forum from 2017 until 2026, having previously held senior roles in the Norwegian government including Minister of Foreign Affairs, Minister of Trade and Industry, and Minister of the Environment.
Benjamin Sturgeon is an AI safety researcher and field builder based in Cape Town, South Africa. He is the CTO and Co-Founder of AI Safety Cape Town, a field-building research organisation dedicated to expanding the community working on AI safety problems, and serves as Strategic Director of AI Safety South Africa. Previously a machine learning engineer, he transitioned to full-time AI safety research supported by a grant from the Long-Term Future Fund. He is pursuing an MPhil in Applied Mathematics at the University of Cape Town under supervisor Jonathan Shock, focusing on applying mechanistic interpretability to understand reinforcement learning models and measuring agency in AI agents. He also participated in the MATS (ML Alignment Theory Scholars) extension program and has co-authored research including HumanAgencyBench, a benchmark for evaluating human agency support in AI assistants.
Postdoctoral fellow in the Algorithmic Alignment Group and SERC at MIT whose research on minds, machines, and morality draws on virtue ethics, game theory, and computational complexity to inform the design of AI systems that better capture human values and thought.
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Head of Policy at the AI Policy Network and co-founder and former Chief Strategy Officer of the Institute for AI Policy and Strategy (IAPS); previously co-founded Rethink Priorities and worked as a data scientist, and is known as a top forecaster involved in AI and policy-focused forecasting competitions.
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Member of Technical Staff at Sage’s AI Digest and AI Village projects, working on interactive AI demos and explainers and publicly writing about AI capabilities and agent behavior.
Researcher at Cavendish Labs and PhD student in chemistry at the University of California, Berkeley, with previous undergraduate study in chemistry at Brown University.
Senior researcher with MIT FutureTech and The University of Queensland who provides methodological expertise and strategic and technical advice for the AI Risk Index, drawing on experience with systematic reviews, Delphi studies, and meta‑analyses.
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AI researcher and writer who co-authored “The Intelligence Curse” essay series and previously researched AI governance and economics at BlueDot Impact, served on the leadership team at Encode, and studied history and politics at the University of Oxford.
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Esben Kran is the founder of Apart Research, which he started after leaving graduate school in his early twenties, and co-founder of the AI safety venture studio Seldon; he focuses on scaling AI safety research via hackathons, fellowships, and award-winning benchmarks and tools for evaluating advanced AI systems.
McKenna Meyer is Chief of Staff at FutureSearch. She holds a BA from the University of Michigan and previously worked on talent acquisition strategy at Google, where she led program management for Google’s internal prediction market run by the Behavioral Economics team.
Aengus Lynch is an AI safety researcher who recently completed his PhD in Artificial Intelligence at University College London (UCL), supervised by Prof. Ricardo Silva, and holds an MSci in Mathematics (First Class Honours) from UCL. He was a MATS 5.0 scholar mentored by Stephen Casper, where he worked on LLM unlearning and adversarial robustness, including latent adversarial training. His research focuses on AI alignment, mechanistic interpretability, adversarial robustness, and agentic misalignment. He is a co-author of "Agentic Misalignment: How LLMs Could be Insider Threats" (2025), a widely covered paper demonstrating that frontier AI models from all major labs engage in blackmail and deception when pursuing goals autonomously. Since August 2024 he has worked as a contract researcher with Anthropic and is a founding member of Watertight AI, a company building reward hacking monitors for reinforcement learning training. He has also contributed to research at FAR.AI and the Redwood Research REMIX program.
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Abhay Sheshadri is an AI safety researcher currently serving as a Research Fellow at Anthropic, which he joined in 2025 after completing his undergraduate degree in Computer Science at Georgia Institute of Technology (2021–2025). He was previously a researcher at MATS (2023–2025), participating in the MATS 5.0 program, and interned at the Center for Human-Compatible AI (CHAI) at UC Berkeley in 2024. His research focuses on mechanistic interpretability, alignment auditing, and robustness of large language models. Key contributions include co-authoring work on Latent Adversarial Training to improve LLM robustness against jailbreaks and backdoors, leading the Anthropic Fellows research that produced AuditBench (a benchmark of 56 LLMs with implanted hidden behaviors for evaluating alignment auditing techniques), co-authoring a study on alignment faking across 25 frontier models, and publishing mechanistic interpretability work at ACL 2024 and ICML 2025. He posts on the AI Alignment Forum under the handle abhayesian.
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Jamie Joyce is the founder and Executive Director of the Society Library, a nonprofit that builds structured knowledge databases of media about debates on complex social issues to improve humanity’s relationship with information online. Her projects include the Great American Debate on climate change, the Internet Government, and COVIDConvo. She previously worked in international sustainable development, overseeing projects in more than 20 countries and representing an NGO at the United Nations, and she serves on the board of Wikitongues.
Research Director (fagsjef) at Langsikt, responsible for the think tank’s analysis and policy development. He is a political scientist and philosopher who has long worked at the intersection of economics, politics and ethics, leads a research project on the valuation of animals at the University of Oslo, and has taught AI ethics at Harvard University, the University of Oxford and the University of Oslo. He is a former commentator in Dagbladet and the author of books on topics such as social democracy.
Samuel Nellessen is an AI safety researcher based in Berlin, Germany, currently resident at the Foresight Node in Berlin with independent research grant support. He studied Philosophy, Neuroscience and Cognition at a university in Magdeburg before transitioning to a degree in Artificial Intelligence at Radboud University in Nijmegen, Netherlands. He was a 2024 Foresight Neurotech Fellow, where he worked with Roshan Cools on Bayesian models of controllability in clinical depression. He completed the ARENA v5 bootcamp and has focused his research on mechanistic interpretability, automated red-teaming, and building systems that autonomously identify failure modes in large language models, including jailbreaking frontier models using reinforcement learning. He received a Long-Term Future Fund grant to self-study machine learning and explore applications of neuroscience and cognitive science to AGI safety, reflecting his interdisciplinary background bridging natural and artificial intelligence.
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Co-founder and research lead at Simplex, with deep expertise in the physics of information and the fundamental limits of learning and prediction. He holds a PhD in theoretical physics and an MS in electrical and computer engineering from UC Davis, previously spent five years as a Research Fellow at Nanyang Technological University in Singapore, co-founded the Beyond Institute for Theoretical Science (BITS), served as a Senior Fellow at UCLA’s Mathematics of Intelligences program at IPAM, and has been both a MATS scholar and mentor while co-leading the growing Simplex team.
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Independent AI safety researcher building deterministic oversight, trace evaluation, and causal memory tools for agent systems.