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Michael L. Chen
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Clear filters to view everything →Indie dev, Wanderer
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Organizing global AI ethics think tank for dynamic AI research updates and framework for AI safety policies implementation and humanity income support
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Computer scientist specializing in machine learning and deep learning, co-founder of OpenAI and Safe Superintelligence Inc., known for major contributions such as AlexNet, sequence-to-sequence learning and GPT models, and formerly serving as OpenAI's chief scientist.
This grant is funding a 6-month stipend for Bilal Chughtai to work on a mechanistic interpretability project
12 week 0.6FT upskilling stipend for technical governance research management
AI ethics specialist and education researcher who serves as Training and Pedagogy Lead for Intelligence Rising, with an MPhil in Ethics of AI from the University of Cambridge and experience bridging theoretical frameworks and practical implementation in educational settings.
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Michael C. George is Head of AI, Labor and the Economy at Partnership on AI, where he leads research and policy work on how AI affects workers and labor markets. Previously he served as a senior advisor to the Deputy Commissioner of the U.S. Internal Revenue Service, focusing on modernizing IRS technology and implementing major legislation, and he has an academic background in government and economics as a Marshall Scholar.
Adam Goldstein is a co-founder of Softmax and serves as a board member and founder emeritus, after co-founding the travel startup Hipmunk and working as a visiting scientist in Michael Levin’s lab at Tufts on cell signaling, bioelectricity, and basal cognition; he is also described as Co-founder, Chairman, and Head of Research for Softmax in external profiles.
PhD in Computer Science working on AI-safety
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Asterisk is a quarterly journal of clear writing and clear thinking about things that matter.
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Alexander Iosad is Director of Government Innovation Policy at the Tony Blair Institute for Global Change, leading policy research on governing in the age of AI and how political leaders can use digital technologies to improve public services. He has deep expertise in education policy, has worked with ministers and international agencies across Africa and Europe, previously worked in edtech venture capital and public-sector innovation consulting, and holds a DPhil in history of science from the University of Oxford.
NLP researcher and data scientist with experience at Stanford University’s School of Engineering, Pr(Ai)2R Group, and Microsoft, focusing on understanding how AI models learn and process language.
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Anna Ek has served as a career counselor for Effective Altruism Sweden, supporting the organisation’s career support and coaching programmes for people seeking higher‑impact work.
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Humanities researcher and engineer, building the global AI governance & safety layer.
Mike McCormick is the founder and CEO of Halcyon Futures, a nonprofit grant fund and venture capital fund dedicated to ensuring that AI is developed in ways that are safe, secure, and beneficial for humanity, and he serves as a board member at the AI Verification and Evaluation Research Institute (AVERI).
Executive Director of the Safe AI Forum (SAIF). Previously a research scholar at the Centre for the Governance of AI (GovAI) studying technical AI progress and AI policy in China, and a researcher on Chinese data and technology policy at Sinolytics, Trivium China, and the Mercator Institute for China Studies; he holds a BA in Politics, Philosophy and Economics from the University of Warwick.
Assistant Professor of Computer Science at the University of Rhode Island and director of the ML4STS Lab, previously a Data Science Initiative postdoc at Brown University and a Chancellor’s Postdoctoral Fellow at UC Berkeley, with BS, MS, and PhD degrees in electrical/electrical and computer engineering from Northeastern University.
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Stipend for a master’s thesis and paper on technical alignment research: mechanistic interpretability of attention
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Peter Schmidt-Nielsen is a hardware and machine learning engineer working on FPGA-accelerated servers at Saturn Data, building high-memory, high-bandwidth systems for workloads such as vector search. He previously worked as an ML engineer at Redwood Research and is a co-author of the NeurIPS 2022 paper "Adversarial Training for High-Stakes Reliability" on adversarial training methods for high-stakes AI reliability.
Danielle Goldfarb is a CIGI senior fellow and economist specializing in trade, real‑time data and the digital economy; she co‑directs the Canadian AI Adoption Initiative and holds fellowships at the Munk School of Global Affairs and Public Policy and the Asia Pacific Foundation of Canada.
Updates, additional resources and promotion for a 4-week introductory syllabus that looks at interventions to help prevent future pandemics.
Running the initial online version of a 4-week biosecurity course for 20-50 participants
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6 month AI alignment internship stipend top-up
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Academic at Deakin University’s School of Information Technology whose research spans reinforcement learning and related areas, officially affiliated with the Machine Intelligence Lab and the Australian Responsible Autonomous Agents Collective (ARAAC), and who serves on program committees or as area chair for major AI conferences such as NeurIPS and AAMAS.
LLMs often know when they are being evaluated. We’ll do a study comparing various methods to measure and monitor this capability.
Mario Peng Lee is an AI engineer at nexos.ai, a Vilnius-based enterprise AI platform, where he works on AI orchestration. He graduated from UCLA in 2024 with degrees in Linguistics and Computer Science and Psychology, and a minor in Data Science Engineering. Born in Chile to Taiwanese parents and raised in China, Taiwan, and Argentina, he is fluent in three languages. At UCLA he co-founded AI Safety at UCLA in 2022, a student research community that grew to over 100 members within a year and received funding from Open Philanthropy; the group developed its own AI safety curriculum and incubated student-directed projects. He also conducted undergraduate research in machine learning behavioral interpretability and natural language processing, co-authored a paper on the Diverse Names Generator in the Proceedings of the Linguistic Society of America, and co-organized a UCLA EA AI Timelines Retreat. He received a grant from the Long-Term Future Fund to cover tuition for the Stanford Artificial Intelligence Professional Program as well as funding for AI safety research in Berkeley.
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