The city attorney who used AI to find the reports nobody was reading
San Francisco, CA, USA · David Chiu, Daniel Ho, Andrea Bruss, Bilal Mahmood
Published July 14, 2026
San Francisco's 16-million-word municipal code had quietly grown hundreds of mandatory reports that almost no one read. City Attorney David Chiu and Stanford's RegLab built a tool to find them all, made his own staff check every one by hand, and the Board of Supervisors just voted on what to do about it.
The story
The person and the place
David Chiu, City Attorney of San Francisco, working with Daniel Ho, Faculty Director of Stanford's Regulation, Evaluation, and Governance Lab.
The problem
the city's code had swelled to nearly 16 million words and roughly doubled its mandatory reporting requirements since 2000, to the point that, in Chiu's own words, "that makes systemic reform daunting."
The decision
instead of accepting the code as unreadable, Chiu's office partnered with RegLab, which pointed a legal-research AI tool at the entire code to surface every reporting requirement buried in it, "at scale, in a way that just would be infeasible for humans to do manually," per Ho. Then the office required every single AI-flagged item to be individually verified by a human before it went into a bill, per Director of Government Legal Reform Andrea Bruss.
the tool surfaced 528 reporting requirements, of which 488 could legally be changed. Chiu's office introduced a 351-page ordinance in June 2025 proposing to delete or consolidate 174 of them, 36% of everything on the table. The bill grew to 362 pages after a year of amendments, and on July 14, 2026 the Board of Supervisors passed it 7-4, with Board President Rafael Mandelman and six others in favor and Supervisors Myrna Melgar, Connie Chan, Jackie Fielder, and Shamann Walton against. In the final two weeks, amendments restored several requirements the AI review had flagged for removal, including domestic-violence data sharing, sexual-harassment reporting, and small-business case-manager reporting, after named officials raised concerns; a surveillance-technology audit requirement was changed from annual to every five years over Supervisor Fielder's objection.
"This is really a way to use AI to identify these forms of policy sludge. The power of this technology is the ability to do something like this at scale, in a way that just would be infeasible for humans to do manually." (Daniel Ho, Faculty Director, Stanford RegLab)
Verified sources
Sources
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