Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
AI for Good Seminar Series: AI for Government | Stanford HAI

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

Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
Skip to content
  • About

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

    • Research
    • Fellowship Programs
    • Grants
    • 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
Your browser does not support the video tag.
eventSeminar

AI for Good Seminar Series: AI for Government

Status
Past
Date
Monday, February 03, 2020 4:00 PM - 5:30 PM PST/PDT
Topics
Economy, Markets

AI promises to transform how government agencies work.  Where will it have the biggest impact?  What are some challenges around transparency, privacy, bias, and accountability? This talk will go beyond the headlines and share highlights of a just-completed report on AI in the US Government.

Share
Link copied to clipboard!
Event Contact
kmatthys@stanford.edu

Related Events

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS
WorkshopJul 15, 20262:00 PM - 3:30 PM
July
15
2026

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Event

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS

Jul 15, 20262:00 PM - 3:30 PM

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Empirical Methods in the Age of AI Conference
ConferenceOct 02, 2026
October
02
2026

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Event

Empirical Methods in the Age of AI Conference

Oct 02, 2026

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Speakers 

David Freeman Engstrom - Professor and Associate Dean for Strategic Initiatives, Stanford Law School

David Freeman Engstrom is the Bernard D. Bergreen Faculty Scholar and an Associate Dean at Stanford Law School.  He is an elected member of the American Law Institute and a faculty affiliate at the Stanford Institute for Human-Centered AI, CodeX: The Stanford Center for Legal Informatics, and the Regulation, Evaluation, and Governance Lab (RegLab).  He received a J.D. from Stanford Law School, an M.Sc. from Oxford University, and a Ph.D. in political science from Yale University and clerked for Chief Judge Diane P. Wood on the U.S. Court of Appeals for the Seventh Circuit.  Before joining Stanford's faculty, he practiced law, representing clients before the U.S. Supreme Court and other courts and agencies.

 

Daniel Ho - Professor of Law, Professor of Political Science, Director of the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University

Daniel Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, and Senior Fellow at the Stanford Institute for Economic Policy Research at Stanford University. Dr. Ho received his J.D. from Yale Law School and Ph.D. from Harvard University and clerked for Judge Stephen F. Williams on the U.S. Court of Appeals, District of Columbia Circuit.  He directs the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford, is a Faculty Fellow at the Center for Advanced Study in the Behavioral Sciences, and is an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI).