Cheryl Phillips: How AI Is Uncovering Hidden Stories in Local Government

When officials in Santa Clara County (home to Silicon Valley) publicly proclaimed they were not sharing data with U.S. Immigration and Customs Enforcement, they likely did not expect to be caught in a contradiction. Yet behind the scenes, those same officials had recently signed new contracts with the federal agency — a fact that might have remained hidden if not for a new generation of AI tools developed at Stanford University.

This breakthrough was made possible by Big Local News, a Stanford-based initiative using AI to help local journalists uncover stories hidden deep within public records. As local newsrooms grapple with shrinking resources and overwhelming amounts of data, tools like these are helping restore investigative capacity where it’s needed most.

In this episode of Newsroom Robots, Cheryl Phillips, founder and co-director of Big Local News at Stanford University, joins host Nikita Roy to share how her team is building AI-powered tools that support watchdog journalism and make complex data more accessible to reporters across the country.

Key topics include:

• Agenda Watch, a tool that scrapes and indexes public meeting agendas to surface early signals of newsworthy developments across thousands of local agencies.
• DataTalk, an AI assistant that turns natural language questions into campaign finance data queries, simplifying analysis for journalists without coding expertise.
• The use of generative AI and large-scale scraping systems to analyze police misconduct records and create public-facing accountability databases.
• How Big Local News uses Slack-integrated bots to deliver real-time alerts on layoffs and problematic fiscal audits to local newsrooms across the U.S.

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