Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Fei-Fei Li's Testimony Before the Senate Committee on Homeland Security and Governmental Affairs | Stanford HAI
Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Research Programs
    • Grants
    • Marlowe (opens in new tab)
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

policyTestimony

Fei-Fei Li's Testimony Before the Senate Committee on Homeland Security and Governmental Affairs

Date
September 14, 2023
Topics
Government, Public Administration
International Affairs, International Security, International Development
Read Paper
abstract

In this testimony presented to the Senate Committee on Homeland Security and Governmental Affairs, Fei-Fei Li urges the need to demystify AI, safeguard its use with privacy and fairness measures, and lead through transparent procurement and strong public AI research investment.

Read Paper
Share
Link copied to clipboard!
Authors
  • fei fei li headshot
    Fei-Fei Li

Related Publications

The 2026 US Talent Report: Benchmarking America’s STEM Pipeline Amid the Great Talent Competition
Emerson Johnston, Amy Zegart
Quick ReadSep 28, 2026
White Paper

This report assesses America's ability to develop, attract, and retain STEM talent and warns that its advantages over China are narrowing rapidly.

White Paper

The 2026 US Talent Report: Benchmarking America’s STEM Pipeline Amid the Great Talent Competition

Emerson Johnston, Amy Zegart
Workforce, LaborInternational Affairs, International Security, International DevelopmentQuick ReadSep 28

This report assesses America's ability to develop, attract, and retain STEM talent and warns that its advantages over China are narrowing rapidly.

Making Local Law Legible: LLM-Assisted Detection of Discrimination
Dan Bateyko, Yasmine Mabene, Derek Ouyang, Daniel E. Ho
Quick ReadSep 08, 2026
Policy Brief

This brief demonstrates the potential of LLM-assisted review to accelerate legal reform.

Policy Brief

Making Local Law Legible: LLM-Assisted Detection of Discrimination

Dan Bateyko, Yasmine Mabene, Derek Ouyang, Daniel E. Ho
Government, Public AdministrationEthics, Equity, InclusionQuick ReadSep 08

This brief demonstrates the potential of LLM-assisted review to accelerate legal reform.

The Commercial Landscape of AI Sovereignty Offerings
Caroline Meinhardt, Juan N. Pava, Caroline Yee, James Landay
Deep DiveJul 15, 2026
Issue Brief

This brief surveys the commercial AI sovereignty market and argues that policymakers should focus on calibrating interdependence rather than pursuing full self-sufficiency.

Issue Brief

The Commercial Landscape of AI Sovereignty Offerings

Caroline Meinhardt, Juan N. Pava, Caroline Yee, James Landay
International Affairs, International Security, International DevelopmentIndustry, InnovationDeep DiveJul 15

This brief surveys the commercial AI sovereignty market and argues that policymakers should focus on calibrating interdependence rather than pursuing full self-sufficiency.

How Can AI Support Language Digitization and Digital Inclusion?
Juan N. Pava, Thomas S. Mullaney, Caroline Meinhardt, Audrey Gao, Diyi Yang
Deep DiveFeb 26, 2026
White Paper

This white paper analyzes the varying ways AI tools can advance language digitization work, and provides recommendations for responsibly realizing the potential of AI in supporting the digital inclusion of digitally disadvantaged languages.

White Paper

How Can AI Support Language Digitization and Digital Inclusion?

Juan N. Pava, Thomas S. Mullaney, Caroline Meinhardt, Audrey Gao, Diyi Yang
Ethics, Equity, InclusionInternational Affairs, International Security, International DevelopmentNatural Language ProcessingDeep DiveFeb 26

This white paper analyzes the varying ways AI tools can advance language digitization work, and provides recommendations for responsibly realizing the potential of AI in supporting the digital inclusion of digitally disadvantaged languages.