PATRICIA PASKOV

Hello! I'm a researcher at RAND focused on frontier AI capability evaluations and policy. I helped launch RAND's Technology and Security Policy Center's EU AI policy workstream and I currently research the science of evaluations, open questions in human uplift studies, and AI autograders. I also serve as a Working Group Chair at the EvalEval Coalition. I'm excited about measuring the societal impacts of AI systems and building solutions to help communities adapt to and thrive with transformitive AI.

Over the past decade, I've worked at the intersection of technology, economics, and social impact across academia, industry, and public policy. Previously, I 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.

I've lived and worked across five continents in countries including Italy, Senegal, Thailand, Peru, and Paraguay. I studied Economics at Barcelona School of Economics and European University Institute, and Applied Economics at the University of Wisconsin-Madison.

I'm based in NYC and excited about growing the city's frontier AI governance and safety community. If this interests you, let's chat.

Selected publications

Human Baselines in Model Evaluations Need Rigor and Transparency

Wei, K.L.*, Paskov, P.*, Dev, S.*, Byun, M.J.* et al. | ICML (Spotlight), 2025

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate?

Bucknall, B.*, Siddiqui, S.* et al. | FaCCT, 2025

Methodological Challenges in Agentic Evaluations of AI Systems

Wei, K. et al. | ICML Technical AI Governance Workshop, 2025

GPAI Evaluations Standards Taskforce: Towards Effective AI Governance

Paskov, P. et al. | NeurIPS RegML and SoLaR Workshops, 2024

Responding to COVID-19 Through Surveys of Public Servants

Schuster, C. et al. | Public Administration Review, 2020

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