Patricia Paskov is a researcher at RAND focused on frontier AI capability evaluations and policy. She helped launch the RAND Center on AI, Security, and Technology's EU AI policy workstream, and currently researches the science of evaluations, open questions in human uplift studies, and AI autograders. She is also the Resilience section lead for the 2026 International AI Safety Report and a Working Group Chair at the EvalEval Coalition. Paskov holds experience at the intersection of economics, data science, and social impact across academia, industry, and public policy. Previously, she built machine learning models at Condé Nast and designed and managed large-scale randomized controlled trials with The World Bank and Innovations for Poverty Action on topics including financial inclusion, mental health, education, and local governance. She has lived and worked across five continents in countries including Italy, Senegal, Thailand, Peru, and Paraguay. Paskov studied Economics at Barcelona School of Economics and European University Institute, and Applied Economics at the University of Wisconsin-Madison.
M.Res in economics, European University Institute; M.Sc. in economics, Barcelona Graduate School of Economics; B.Sc. in applied economics, University of Wisconsin-Madison
Spanish
