Patricia Paskov

Patricia Paskov is a technology and security policy fellow at RAND. She is an applied researcher at the intersection of AI, economics, and policy, with an interest in AI safety and ethics. She holds experience in experimentation, causal inference, data science, and machine learning across industry, academia, government, and international organizations. Previously, she worked as an industry data scientist, building machine learning models in Python on distributed computing systems, and as an analyst with the World Bank's Bureaucracy Lab (DIME, Governance Global Practice), where she contributed to the design, launch, and management of a EU-funded civil service research portfolio in collaboration with policymakers and academics. Paskov also carries on-the-ground field research experience in Peru (Innovations with Poverty Action) and Paraguay (University of Wisconsin), where she contributed to experimental research and data collection on financial inclusion, civil service corruption, and education in both rural and urban settings. Paskov holds a M.Sc. in economics from Barcelona School of Economics, a M.Res. in economics from European University Institute, and a B.S. in applied economics and Latin American studies from the University of Wisconsin-Madison.