About
Daniel E. Ho holds multiple prestigious positions at Stanford University:
- William Benjamin Scott and Luna M. Scott Professor of Law
- Professor of Political Science
- Professor of Computer Science (by courtesy)
- Senior Fellow, Stanford Institute for Economic Policy Research
- Senior Fellow, Stanford Institute for Human-Centered Artificial Intelligence
- Faculty Fellow, Center for Advanced Study in the Behavioral Sciences
He serves on the National Artificial Intelligence Advisory Commission (NAIAC), as Senior Advisor on Responsible AI at the U.S. Department of Labor, and as a Public Member of the Administrative Conference of the United States (ACUS).
Ho earned his J.D. from Yale Law School and Ph.D. from Harvard University, completing a clerkship with Judge Stephen F. Williams on the U.S. Court of Appeals for the District of Columbia Circuit.
His research bridges artificial intelligence, law, and public policy with emphasis on:
- Regulatory governance frameworks for AI systems
- Fairness and bias mitigation in algorithmic decision-making
- Environmental enforcement using satellite imagery and computer vision
- Methods for estimating racial disparities without direct demographic data
- Legal AI reliability and statutory research systems
Analysis of his 2025 publications reveals a consistent focus on practical AI governance tools addressing real-world regulatory challenges. Key themes include developing benchmarks for legal applications, mitigating hallucination in legal AI tools, and creating systems for statutory research. His work demonstrates strong integration of technical AI methods with policy implementation, particularly in environmental enforcement and fairness assessment.
As Director of the Regulation, Evaluation, and Governance Lab (RegLab), Ho leads interdisciplinary research partnerships with government agencies. While specific grant details aren't provided, RegLab's operational model indicates substantial research funding for policy-relevant AI projects. No student advisees are mentioned in available materials.
Ho's leadership extends to national advisory roles where he shapes federal AI policy through evidence-based recommendations, particularly regarding environmental protection and civil rights enforcement mechanisms.
