David Manheim

Rehovot, Israel

Bio

Updated 03/22/26

David Manheim is the founder and head of research and policy at ALTER (Association for Long Term Existence and Resilience), an academic research and advocacy organization based in Israel, and a visiting lecturer at the Technion - Israel Institute of Technology. He holds a PhD in risk analysis and decision theory from the Frederick S. Pardee RAND Graduate School and an undergraduate degree in mathematics from Lander College. Before pivoting to policy research, he worked in equity derivatives risk at an investment bank and built reinsurance terrorism risk models. His research focuses on mitigating large-scale risks to humanity, with particular emphasis on AI governance and safety, biosecurity and pandemic prevention, systemic risks, and geopolitical and technological forecasting. He is widely known in the AI safety community for co-authoring the influential paper "Categorizing Variants of Goodhart's Law" with Scott Garrabrant, and for his work on multiparty dynamics and failure modes for machine learning systems. He is a Superforecaster with Good Judgement Inc. and was one of the original participants in the Good Judgement Project IARPA forecasting competition. He has received grants from the Long-Term Future Fund for research on AI risk structure and multi-model approaches to x-risk mitigation, and advises organizations including Bluedot Impact, the Foresight Institute grant program, and the Unjournal.