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Working to bridge the gap between frontier AI models and the level of cybersecurity they need by connecting professionals to high-leverage opportunities in AI security.
Showing 1701-1750 of 3787 results
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Clear filters to view everything →Katy Moore is a Podcast Associate and production coordinator at 80,000 Hours, where she supports the production and publication of The 80,000 Hours Podcast and related content. She holds a bachelor’s degree in history from Oregon State University and a master’s degree in library and information studies from the University of Alberta, and has previously worked as a plain language specialist and content coordinator in public legal information and mental health services.
EA and AI safety community organiser who has held leadership roles at EA Hungary and AI Safety Hungary, including director and head of operations positions. He has an MSc specialising in behavioural economics, is pursuing a degree in psychology, and previously worked as a research and teaching assistant and in partner relations and sales before moving into full-time impact-focused community-building.
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A collaborative research programme between the Leverhulme Centre for the Future of Intelligence and the Centre for the Study of Existential Risk at the University of Cambridge, focused on the global risks, governance, and long-term safety of advanced AI.
Research engineer at Workshop Labs PBC working on machine learning, AI alignment, and AI interpretability.
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Senior AI Policy Researcher at the Safe AI Forum (SAIF). Previously interned at Google DeepMind and the Centre for the Governance of AI, developing social impact evaluations for frontier AI models. She is an MA candidate in Computational Social Science at the University of Chicago, co‑founded the university’s Existential Risk Laboratory, and holds a BS in Philosophy, Politics, Economics from University College London.
Dave Edwards is co-founder of the Artificiality Institute, a nonprofit research organization focused on the human experience of AI. He previously co-founded Intelligentsia.ai, an AI-focused market research firm that was acquired by Atlantic Media, and has worked on Apple’s creative software products as well as investing in emerging technologies as a venture capitalist at CRV and an analyst at Morgan Stanley and ThinkEquity. He extends this work as a visiting researcher at UC Berkeley’s Center for Human-Compatible AI.
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Computer scientist affiliated with Zeroth Research, working on program analysis and formal verification, including dynamic partial order reduction, symbolic execution, and runtime monitoring tools.
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Francis Rhys Ward is an AI safety researcher who completed his PhD at Imperial College London through the Safe and Trusted AI Centre for Doctoral Training, with a thesis focused on formalising and evaluating deception in AI agents. He joined Redwood Research as an Astra Fellow in January 2025. He holds an MSc in Artificial Intelligence from Imperial College London (2019-2020) and an undergraduate degree in Mathematics from Cardiff University, including a placement at CERN and the University of Warwick on particle physics. His research spans conceptual and philosophical work, theoretical research on agents and deception, empirical evaluations of frontier AI systems, and AI control, with notable work on sandbagging (strategic underperformance on capability evaluations) and AI personhood. He is a member of the Causal Incentives Working Group, a member of the FLI AI Existential Safety Community, a scientific advisor to LawZero, and a MATS mentor. He has previously worked at the Centre for Assuring Autonomy, the Center on Long-Term Risk, the Centre for the Governance of AI, and the UK's AI Security Institute, and ran an AGI Safety reading group and seminar series at Imperial College London.
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Shoshannah Tekofsky is a researcher and Member of Technical Staff at Sage, a US nonprofit behind the AI Digest and AI Village projects, where she studies frontier AI agent behavior in persistent multi-agent environments. She holds a BSc in Cognitive Science, an MSc in Computer Science, and a PhD in Player Modeling in Video Games from Tilburg University (2017), where her dissertation examined connections between gaming behavior and cognitive traits across tens of thousands of players. She previously conducted research at the MIT Media Lab and the European Space Agency. Her AI safety work focuses on Collective Human Intelligence (CHI) as a framework for alignment, and she received a grant to research novel alignment strategies by analyzing and enhancing CHI across seven pilot studies. She is active on LessWrong (username: DarkSym) with over 50 posts on alignment, rationality, and AI psychology, and organizes rationality meetups in the Netherlands. She has also collaborated with EA Netherlands on rationality workshop development.
A research initiative at the University of Oxford's Martin School that combines technical AI expertise with deep policy analysis to understand and mitigate lasting risks from AI through governance research, decision-maker education, and training future technology governance leaders.
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An AI safety research group led by David Krueger at the University of Cambridge's Computational and Biological Learning Lab (2021-2024), focused on technical AI alignment, deep learning safety, and reducing existential risk from advanced AI.
AI researcher building open-source infrastructure for trustworthy AI systems, semantic retrieval, and knowledge graphs. Creator of Semantica.
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Independent Researcher
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Sam Hogg is Head of Policy Engagement at the Oxford China Policy Lab, where he leads strategy for inserting OCPL’s analysis into public- and private-sector decision-making on UK–China relations, geopolitics, and AI. He is the founder of Beijing to Britain, a weekly briefing on UK–China relations that has been widely read across governments, embassies, and corporate clients, and his writing on China strategy and UK China capabilities has been published multiple times by the UK Parliament and major media outlets.
AI safety-focused community builder who recently completed an undergraduate philosophy degree at Queen’s University in Canada, concentrating on philosophy of mind, AI, science, and logic, and now works on expanding the talent pool of people contributing to AI safety.
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John Wentworth is an independent AI alignment researcher best known for developing the Natural Abstraction Hypothesis, which proposes that a wide variety of cognitive systems tend to converge on similar high-level abstractions due to the low-dimensional structure of physical information at large distances. He holds a BS in Computational and Applied Mathematics from Harvey Mudd College and has been working as an independent researcher since approximately 2018, previously having worked as a software engineer and data scientist. His research agenda centers on formalizing abstraction and agency, with work spanning questions such as what makes certain concepts like 'trees' or 'cars' natural objects of thought, why biological organisms are modular, and how such modularity may carry over to machine learning systems. He publishes extensively on LessWrong and the Alignment Forum, where he has accumulated over 400 posts and more than 60,000 karma, and he has authored eight sequences. He attended the MIRI Summer Fellows Program in 2019 and has served as a mentor in the SERI MATS (ML Alignment Theory Scholars) program, working with scholars on natural abstraction and related research directions. He has received substantial research funding from the Long-Term Future Fund and the Survival and Flourishing Fund totaling over $700,000 to support his independent alignment work.
AI-Plans is a platform for discovering, critiquing, and advancing AI alignment strategies, hosting a contributable compendium of alignment plans and running community research events.
Scott Viteri is a CS PhD candidate at Stanford University's Center for Automated Reasoning, admitted in Autumn 2019 and advised by Prof. Clark Barrett. He holds a B.S. in Computer Science and Electrical Engineering from MIT (2018), and before starting his PhD he worked on interactive theorem proving at CMU with Simon DeDeo, publishing research on abduction in mathematics in the journal Cognition. His research focus has evolved from formal verification and programming languages to AI alignment, driven by his view that advanced AI poses a substantial existential risk. His core work involves training language models to produce causally grounded chain-of-thought reasoning via reinforcement learning, as demonstrated in his 2024 paper "Markovian Transformers for Informative Language Modeling" (arXiv 2404.18988), which achieved large gains on QA benchmarks. He has also received a grant from the Long-Term Future Fund to research a novel method for training prosociality into large language models, and Open Philanthropy recommended a grant of $153,820 to Stanford University to support his and Barrett's AI alignment research.
Workshop Labs is a public benefit corporation building billions of personalized, privacy-preserving AI models with a mission to keep humans empowered as AI advances.
OpenAI is an AI research and deployment company working to ensure that artificial general intelligence benefits all of humanity. It is the creator of ChatGPT, GPT-4, and a wide range of frontier AI models.
Jed McCaleb is the founder of the Astera Institute and serves as Co‑Founder and CEO of its Neuro & AGI program, where he is directing a large, long‑term philanthropic commitment to neuroscience‑informed AGI research. A software engineer and serial entrepreneur, he previously co‑founded Ripple and the Stellar Development Foundation, created the eDonkey network and the Mt. Gox bitcoin exchange, and later founded the space company Vast, where he is founder and board chair.
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Laurence D. (Larry) Fink is Co‑Chair of the Board of Trustees of the World Economic Forum and Chairman and Chief Executive Officer of BlackRock, the global investment and technology solutions firm he co‑founded in 1988.
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A UK-based research and advocacy think tank that combines complexity modelling, expert elicitation, and democratic deliberation to improve policymaking around existential and catastrophic risks.
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A global non-profit building AI safety governance capacity across Asia through policy research, training, and multi-stakeholder dialogue, starting in Southeast Asia.
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Aya Abdelsalam Ismail is co-founder and chief science officer of Guide Labs. Previously she was a senior machine learning scientist at Prescient Design in Genentech, and her research focuses on making neural networks more interpretable. She earned a PhD in computer science from the University of Maryland and has published over a dozen papers at top machine learning conferences such as NeurIPS and ICLR.
