HAI Associate Director Daniel Ho Garners Awards | Stanford HAI
Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
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
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

newsAnnouncement

HAI Associate Director Daniel Ho Garners Awards

Date
July 22, 2022
Your browser does not support the video tag.

Professor Ho honored for his contributions to AI and Law, and for helping fight the COVID-19 pandemic.

Daniel Ho, William Benjamin Scott and Luna M. Scott Professor of Law, Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence, and Director of the Regulation, Evaluation, and Governance Lab (RegLab), worked with the Santa Clara County Public Health Department in a collaboration that was awarded the Innovative Practice Gold Award for “the highest level of program innovation” to serve “community during the COVID-19 pandemic” by the National Association of County and City Health Officials (NACCHO). Co-authors included Stanford RegLab members Lisa Lu, Benjamin Anderson, Raymond Ha, and Derek Ouyang as well as members of Santa Clara County Public Health Department Alexis D’Agostino and Sarah L. Rudman.

Additionally, a paper co-authored by Ho and RegLab members (Lucia Zheng ’22, Peter Henderson JD ’23, Neel Guha JD ’23, Brandon Anderson) “When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings,” was awarded the 2021 Carole Hafner Best Paper Prize at the International Conference on Artificial Intelligence and Law.

Share
Link copied to clipboard!
Contributor(s)
Stephanie Ashe

Related News

Reading Today’s Headlines Through AI: A Real-Time Audit of Six Commercial Chatbots
Mirac Suzgun and James Zou
Jun 03, 2026
News

In a new study, scholars measured how accurately popular AI chatbots answered questions about the emerging news and found substantial regional disparity, dependence on distinct information ecosystems, and acute fragility under imperfect prompts.

News

Reading Today’s Headlines Through AI: A Real-Time Audit of Six Commercial Chatbots

Mirac Suzgun and James Zou
Communications, MediaGenerative AIJun 03

In a new study, scholars measured how accurately popular AI chatbots answered questions about the emerging news and found substantial regional disparity, dependence on distinct information ecosystems, and acute fragility under imperfect prompts.

AI Coding Agents Fail at Teamwork
Andrew Myers
Jun 01, 2026
News
illustration of two people paddling in opposite directions

Two models working together perform worse than one alone, exposing a critical gap in artificial intelligence capabilities.

News
illustration of two people paddling in opposite directions

AI Coding Agents Fail at Teamwork

Andrew Myers
Generative AIMachine LearningJun 01

Two models working together perform worse than one alone, exposing a critical gap in artificial intelligence capabilities.

State Policymakers Divided Over How To Address AI Job-Loss Fears
San Francisco Examiner
May 30, 2026
Media Mention

HAI Director James Landay discusses historical technological impacts on productivity growth.

Media Mention
Your browser does not support the video tag.

State Policymakers Divided Over How To Address AI Job-Loss Fears

San Francisco Examiner
Workforce, LaborEconomy, MarketsMay 30

HAI Director James Landay discusses historical technological impacts on productivity growth.