Proud that our team at Stanford RegLab, in partnership with the NY Governor's Office, is demonstrating what responsible AI reform looks like---as @KathyHochul notes, the "opposite" of DOGE. Thanks @gr_ashford for the great coverage at nytimes.com/2026/07/08/nyr…!
Research Director at the Regulation, Evaluation, and Governance Lab (reglab.stanford.edu), Executive Director of City Systems (city.systems).
- Let's say you're trying to understand racial health disparities in the U.S. Does it matter which source of administrative race/ethnicity information you use? We analyzed a dataset of 5M+ patients with linked electronic health records and Census Bureau microdata to find out. 🧵👇
- The EPA receives thousands of tips annually from the public about environmental violations. 80% of them shouldn’t even be going to the EPA, and the rest often get sent to the wrong division. We’ve built an LLM-based system to assist with tip routing. aclanthology.org/2025.emnlp-mai…
- Thanks @KelseyTuoc for referencing our ADU study! Couldn't have said it better: "I don’t think we need better enforcement that would prevent this housing from getting built — we need fewer rules for people building much-needed housing!" RegLab is working on this with cities!I wrote for the Argument today about all the ways our society is set up to reward cheating: strict rules, not really enforced, because we lack the will either to enforce them or to change them. theargumentmag.com/p/the-honesty-…
- The term "Asian American", developed in the 60s for political purposes, can unfortunately mask significant within-group disparities. We just published a dataset + code in Nature Scientific Data to assist with Asian disaggregation for equity assessments.


