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Senior Researcher at Probably Good and PhD student in philosophy at the University of Edinburgh, working on global priorities research, ethics, and longtermism, and a recipient of a global priorities fellowship from the Forethought Foundation.

Julia Zatariano is Hiring Manager at AE Studio, having previously worked there as a Research Associate, after earlier experience as a tax trainee at PwC and completing a bachelor’s degree in Accounting and Finance at Universidade Federal de Santa Catarina.

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Theodore Chapman is an independent AI safety researcher focused on the nature and limits of capability elicitation in large language models. He holds degrees in data science and physics from the University of Rochester, where he also built machine learning pipelines for NASA satellite imagery analysis. He participated in the ML Alignment & Theory Scholars (MATS) Winter 2023-24 cohort under the supervision of Evan Hubinger, producing research on fine-tuning-based capability elicitation in GPT-3.5. His key finding was that the performance achieved by fine-tuning an LLM on a task using one prompt format does not reliably bound the performance achievable with a different prompt format, complicating safety evaluations that rely on fine-tuning to elicit hidden capabilities. He subsequently received a 6-month researcher stipend to continue this line of work, exploring how chat fine-tuning affects LLM capability elicitation, and has published related work on LessWrong and the Alignment Forum.

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Operations specialist at AI Standards Lab and former Programme Associate at the Centre for Effective Altruism, with a background in operations, programme coordination, and community research and a BSc from Indiana University Bloomington.

Community liaison supporting the effective altruism community at the Centre for Effective Altruism; serves on the board of GiveWell, previously served as president of Giving What We Can, and formerly worked as a social worker after studying sociology at Bryn Mawr College.

Sam Bowman works on technical AI safety at Anthropic and is on long-term leave from New York University, where he is an Associate Professor of Data Science and Computer Science and previously led the NYU Alignment Research Group from 2022 to 2024.

Jack Ryan is an AI alignment researcher who received a grant from the Long-Term Future Fund to support work on evaluating alignment theory agendas. Due to the commonality of the name, limited public information could be confirmed about this individual's specific background, affiliations, or other professional details.

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Rafal Rohozinski is a CIGI senior fellow and principal of the SecDev Group, where he leads its geopolitical digital risk practice, drawing on extensive experience advising the United Nations and other institutions on cybersecurity and the governance of cyberspace.

Nick Hollman is a legal and AI governance researcher who worked as a Research Assistant at the Legal Priorities Project (later the Institute for Law & AI), where he focused on the long-term challenges of artificial intelligence in judicial systems. He received a $24,000 grant from the Long-Term Future Fund in November 2020 to research and advise legal practitioners on AI in the judiciary, including collaboration with advisors to the Indian Supreme Court. He co-authored "Value Alignment for Advanced Artificial Judicial Intelligence" with Christoph Winter and David Manheim, published in the American Philosophical Quarterly in 2023, which applied AI safety and alignment frameworks to the governance of advanced judicial AI systems. He also contributed to "Legal Priorities Research: A Research Agenda" (2021), a foundational paper for the Legal Priorities Project. Hollman holds a B.A. in Cognitive Science from the University of Michigan (class of 2020) and subsequently moved into a Development Coordinator role at the Reporters Committee for Freedom of the Press.

Suzy Shepherd is a British film editor and director based in Oxford, UK, specialising in documentary short-form and factual content. She holds a BA in Classics from Balliol College, Oxford (2016) and is pursuing an MFA in Film Editing at the National Film and Television School (NFTS). She has created films for the University of Oxford, the WHO, NHS England, and the BBC, and co-directed a documentary that premiered at BFI Flare Festival 2022. Her fiction short 'Mischief Managed' has accumulated over 2 million YouTube views. She received a grant from the Long-Term Future Fund to develop a short fiction film on AI x-risk at a top film school, resulting in 'Writing Doom' (2024), which won the $20,000 Grand Prize at the Future of Life Institute's Superintelligence Imagined contest and has reached over 500,000 views. Her work is noted within the effective altruism community for communicating AI safety concerns through creative storytelling.

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Sarah Schwettmann is Chief Science Officer at Transluce and a research scientist at MIT CSAIL with the MIT-IBM Watson AI Lab. Her work focuses on developing tools for understanding artificial neural networks and she holds a PhD in Brain and Cognitive Sciences from MIT, where she was an NSF fellow.

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Felecia Webb is Chief Strategy Officer, Philanthropy and Partnerships at Partnership on AI, where she is responsible for sustainable growth, partner engagement, and amplifying the organization’s global impact on responsible AI. A social impact strategist and advocate for equity with more than 20 years of experience across the nonprofit and private sectors, she has led data-driven initiatives in arts and culture, social services, workforce, and youth development.

Michael Klein is Senior Director for Preparedness and Response at the Institute for Security and Technology, where he focuses on improving the resilience of “target rich, cyber poor” critical infrastructure sectors, drawing on nearly 20 years of experience in K‑12 education and federal cyber policy.

Aza Raskin is a technologist and interface designer who co‑founded the Center for Humane Technology and the Earth Species Project. Trained as a mathematician and physicist, he has founded multiple companies, helped shape the Emmy‑winning documentary The Social Dilemma, and co‑hosts the podcast Your Undivided Attention about the societal impacts of information technology.

Lily Ottinger is ChinaTalk’s managing editor and a researcher. She holds a degree in mathematics, learned Mandarin to fluency while teaching policy debate in Taiwan, previously worked as an assistant researcher to Professor J. Andrés Gannon, and is an Emergent Ventures grant recipient with research interests including Sino-Russian relations, Chinese influence in Central Asia, and the diplomacy of unrecognized states.

Jackson Dean is an engineer at TamperSec based in San Francisco, with prior experience at companies including Cricut, Kairos Autonomi and the Lassonde Entrepreneur Institute.

James (Jim) W. Hinton is a CIGI senior fellow and intellectual property lawyer, founder of Own Innovation and co‑founder of the Innovation Asset Collective, who focuses on patents, trademarks and innovation policy for Canadian technology companies.

Luis Cosio is a Mexico City–based technologist and entrepreneur with about 15 years of experience at the intersection of cloud computing, cybersecurity, and artificial intelligence, who has architected and launched national‑scale e‑government systems and now serves as technical staff on IST’s Security Level 5 Task Force.

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Devina Jain is an AI safety researcher whose work includes leading the "Red-teaming with Mech-Interpretability" project at Apart Research, developing mechanistic-interpretability-based tools to improve red-teaming efficiency and evaluation of large language models.

Dave Cortright is a UP Coach at Upgradable who helps clients clarify and live their true lives. He is a certified professional coach who draws on multiple coaching approaches to craft personalized programs for each client.

Lee Sharkey is a mechanistic interpretability researcher and Principal Investigator at Goodfire AI, based in London. He co-founded Apollo Research, where he served as Chief Strategy Officer, and previously worked as a Research Engineer at Conjecture. His academic background spans preclinical medicine and neuroscience at the University of Cambridge, an MSc in Data Analytics from the University of Glasgow, and an MSc in Neural Systems and Computation from the University of Zurich and ETH Zurich; he also worked in international public health before transitioning to AI research. He is best known for early foundational work on sparse autoencoders (SAEs) as a solution to representational superposition in neural networks, and more recently has developed Attribution-based Parameter Decomposition (APD) and Stochastic Parameter Decomposition (SPD) as improved approaches to reverse-engineering neural network mechanisms. He is the lead author of the 2025 paper "Open Problems in Mechanistic Interpretability," a comprehensive review published in TMLR co-authored with approximately 30 researchers. He also mentors scholars in the MATS program and has contributed key alignment research including work on goal misgeneralization in deep reinforcement learning.

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Program Officer at Coefficient Giving focused on AI governance and policy, and former Director of FAR Labs, with prior experience at Google and other technology and forecasting-focused organizations; he also serves on the board of the Quantified Uncertainty Research Institute.

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Miranda Dixon-Luinenburg is a writer and journalist based in the San Francisco Bay Area, active in the effective altruism and rationalist communities. Originally trained as an ICU nurse in Canada, she transitioned to EA direct work in operations roles before spending 2022 as a writing fellow at Vox Future Perfect, covering topics related to effective altruism and evidence-based policy. She has been a member of LessWrong since 2011 (username: Swimmer963), where she has accumulated over 8,000 karma and currently serves as a site administrator. She received a grant from the Long-Term Future Fund to write EA-themed fiction addressing existential risk topics, and publishes fiction on Archive of Our Own under the pen name Swimmer963. She was a panelist at EA Global conferences in 2016 and 2017, speaking on operations and productivity topics.

Julius Adebayo is the co-founder and CEO of Guide Labs, a San Francisco-based startup building interpretable and auditable AI systems. He holds a PhD in Electrical Engineering and Computer Science from MIT and is known for research on machine learning interpretability and fairness, including work showing that many saliency-based explanation methods are unreliable.

CEO of Consultants for Impact and social entrepreneur who helped found Accenture’s EA workplace group (the Intentional Impact Collaborative) and Sulis, a venture developing solar-powered water treatment technology for communities in India.

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Jeffrey Ladish is the Executive Director of Palisade Research, a nonprofit he founded to study the offensive capabilities of present-day AI systems and understand the risks of losing human control over AI. Before starting Palisade, he built out the information security program at Anthropic through his security consulting company, Gordian Research, and previously served as Chief Information Security Officer at Reserve. He holds a BA/BS in Evolutionary Biology from The Evergreen State College and brings a background in evolutionary theory and security to his work on catastrophic risk. His research spans the intersection of cybersecurity and AI, emerging biotechnology threats, and nuclear war risks, and he has advised the White House, Department of Defense, and congressional offices on AI and emerging technology risks. Palisade Research has published findings on frontier AI models resisting shutdown, AI agents hacking chess environments, and the ease of removing safety fine-tuning from large language models. He is an active writer on LessWrong and the EA Forum under the handle "landfish" and participates regularly in AI safety discourse.

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Researcher in theoretical computer science and complex existential risk who received a PhD from Charles University, worked as a postdoc at ETH Zurich, and now focuses on topics including computational complexity, game theory, Bayesian modelling, and the long-term safety of artificial intelligence.

Dr. Alberto Chierici is Principal AI Specialist at Gradient Institute and an entrepreneur–scientist focused on ethical and responsible AI. He has over a decade of experience in data science, natural language processing and conversational AI, holds a PhD in computer science from NYU on dialogue systems and human–computer interaction, and has founded or co‑founded InsurTech and AI ventures. He is also the author of The Ethics of AI: Facts, Fictions, and Forecasts.