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Clear filtersBen Hoffman has worked as a researcher for GiveWell and the Open Philanthropy Project and in financial services managing a risk analytics team, and he holds an MS in Mathematics and Statistics from Georgetown University and a BA from St John’s College.
Showing 2151-2200 of 3966 results
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Clear filters to view everything →Buck Shlegeris is the CEO of Redwood Research, a nonprofit AI safety and security lab, where he leads work on AI control and related empirical safety research; he previously worked on AI alignment and outreach at the Machine Intelligence Research Institute (MIRI).
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Funding the open-source launch of a working claim-state system and the local firewall bridge that carries verification before voice into governed agent action.
Lorenzo is a full‑stack software engineer at Giving What We Can, supporting product development and maintaining the organisation’s technical infrastructure. Originally from Italy, he previously did small‑scale earning to give as a software developer in the Netherlands and, after winning a donor lottery in 2022, moved back to Italy to reflect on how to do more good.
Investigate humans’ lack of robust task alignment in amplification, and the implications for acceptability predicates
Researcher at the Machine Intelligence Research Institute working on the foundations of reasoning and agency, including logical uncertainty and decision theory; studied pure mathematics at the University of Waterloo and previously worked at Google on automatic construction of deep learning models.
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Support my postgraduate law studies and research in AI Governance
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Assistant Professor in Natural Language Processing at the University of Vienna, working in natural language processing and related areas of computational linguistics.
Alex Turner is a research scientist at Google DeepMind on the scalable alignment team, where he works on training invariants into model behavior and related alignment problems. He previously formulated and proved the power-seeking theorems, co-formulated the shard theory of human value formation, and proposed the Attainable Utility Preservation (AUP) approach to penalizing negative side effects, and he now mentors researchers through the MATS program’s Team Shard stream.
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Executive Director of Probably Good, whose widely read writing on applied psychology and philosophy has been linked from outlets such as The New York Times and TechCrunch; holds a PhD from the University of Cambridge, where he is an affiliated lecturer teaching quantitative and computational research methods.
Helen Edwards is co-founder of the Artificiality Institute, a nonprofit that explores how AI is transforming how people think, decide and live. She has led large-scale technology transformations as CIO of New Zealand’s national grid and held executive roles at organizations including Pacific Gas & Electric, Fonterra, Meridian Energy, Quartz and Transpower. She also serves as a commissioner on Oregon’s Higher Education Coordinating Commission and is a visiting researcher at UC Berkeley’s Center for Human-Compatible AI.
Josh Rosenberg is the Chief Executive Officer and a co-founder of the Forecasting Research Institute, where he oversees research, strategy, fundraising, and operations with a focus on making forecasting useful to decision-makers. Previously, he was a Senior Advisor and Senior Research Manager at GiveWell, working on management, research, grantmaking, and hiring, and he holds a B.A. in Economics and Philosophy from Pomona College.
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President and Partner at Flow Research Collective and Venture Partner at multiple early-stage funds including Lionheart Ventures, Pioneer Fund, Essence Venture Capital and 1024 Ventures, as well as Limited Partner Advisor at GTMfund.
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Paul Colognese is an AI safety researcher based in the United Kingdom, focused on understanding how AI systems represent and self-reflect on their goals and beliefs. He holds a PhD in Mathematics (Geometry, Topology, and Dynamical Systems) from the University of Warwick, where he researched translation surfaces under the supervision of Professor Mark Pollicott. His AI safety work includes building safety evaluations for Anthropic and the UK AI Security Institute, including control and sabotage evaluations that measure whether deployed AI agents could undermine safety systems. He has conducted AI threat modeling on catastrophic risk scenarios and carried out interpretability research in which he demonstrated the ability to detect an AI system's objectives through technical analysis. He participated in the MATS research program mentored by Evan Hubinger at Anthropic. He founded the London Initiative for Safe AI, a UK-based research center, and serves as AI Alignment Lead at the Center for the Study of Apparent Selves. He is active on LessWrong and the Alignment Forum, and participated in AI Safety Camp (AISC9) working on detecting agentic AI objectives via interpretability methods.
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Director of Safe AI Germany
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Sam F. Brown is an independent AI alignment researcher based in Oxford, UK. He has a background in physics and programming, and previously worked at a climate technology startup before pivoting to full-time alignment research. He has received two grants from the EA Long-Term Future Fund: an initial six-month grant (approximately £40,000) for research on goal-inference and choice-maximisation, and a subsequent twelve-month grant ($82,298) to research technical approaches to value lock-in and minimal paternalism. His work explores empowerment-based alignment — the idea of maximising humans' capacity to reach diverse future outcomes rather than inferring and locking in specific human values. He has published research essays on LessWrong and the EA Forum, including "The Empowerment of Others" and "Questions about Value Lock-in, Paternalism, and Empowerment". He is connected to the Oxford rationalist and EA community and works from spaces including Trajan House, the Centre for Effective Altruism's Oxford building.
Co-director of the Cambridge AI Safety Hub, working on AI safety fieldbuilding in Cambridge, UK. Previously a political science PhD candidate at SUNY Stony Brook, with experience in research and teaching before moving full-time into AI safety.
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Director of Operations at the AI Safety Awareness Project. Trained as a mechanical engineer, he previously worked as a design engineer at Boeing across commercial and defense programs, focusing on structural design, destructive testing, and product development. He holds a B.S.E. and an M.S. in Mechanical Engineering from Arizona State University and, beginning in 2024, transitioned from aerospace engineering into operational work and AI safety outreach.
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Yoel Roth is a nonresident scholar in the Technology and International Affairs Program at the Carnegie Endowment for International Peace and senior vice president of trust and safety at Match Group; he previously led Twitter’s trust and safety team and now focuses on governance and safety for social media and AI systems.
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12 months funding for 3 people to work full-time on projects supporting AI safety efforts
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A podcast mainly themed around AI x-risk, aimed at a non-technical audience