Patricia Paskov

Director of Standards, AVERI

  • I am the Director of Standards at the AI Verification and Evaluation Research Institute (AVERI), a nonprofit building the independent third-party auditing layer for frontier AI. I'm also an Adjunct Researcher at RAND and a Research Affiliate at the Oxford Martin AI Governance Initiative.

    My research on frontier AI evaluations and governance has appeared in top machine learning venues including ICML, Science, and FAccT and policy venues including Carnegie, RAND, and The World Bank and has been covered by media outlets including Al Jazeera, the Financial Times, Fortune, MIT Technology Review China, and TIME. I led the Resilience section of the 2026 International AI Safety Report, co-founded NYC AI Governance & Safety, and serve as Faculty at the International Programme on AI Evaluation. As of Fall 2026, I am a DPhil candidate in Engineering Science at the University of Oxford.

    Previously I built machine learning models at Condé Nast and designed large-scale randomized controlled trials with the World Bank and Innovations for Poverty Action. I completed degrees in economics at the University of Wisconsin–Madison, the Barcelona School of Economics, and the European University Institute.

    • AI Evaluators Forum expansion and governance strategy

    • Open questions in frontier AI auditing

    • Standards for access, auditing governance, and conflict of interest

    • Building a PCAOB/FINRA analogue for AI auditing

    • Ecosystem intelligence — a living repository or recurring flagship report covering auditing regulations, ISO and standards, licensing and credentials, and auditing orgs.

    • Analytical writing

    • Built structured knowledge systems from unstructured domains (databases, taxonomies, ontologies, ecosystem maps, papers)

    • Disseminates work to audiences that use it

    • Builds for an audience — knows who it's for and what it should change

    • Independent with proactive communication

    • Manages external partnerships

    • Knows the frontier AI evaluation/auditing ecosystem

    • CS/ML or hands-on evals experience

    • Auditing or adjacent assurance regime experience

    • Background in standards bodies, trade orgs, professional self-regulation, credentialing

    • Shipped public work others used.