Newsroom Robots

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

Newsroom Robots

Show Notes

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.

Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy.

Hosted on Acast. See acast.com/privacy for more information.

More from Newsroom Robots

May 30, 2026

For most of journalism’s history, the article has been the atomic unit of news: a fixed container, written once and served the same way to everyone. That’s beginning to change. AI is moving out from behind the scenes, where it quietly powered efficiencies, and into the interface itself, where it can assemble, personalize, and adapt the news to each reader.

Apr 12, 2026

At The Seattle Times, an AI tool identified a new prospect and helped close additional ad revenue in a single day. The Seattle Times is one of 11 news organizations participating in the Lenfest AI Collaborative and Fellowship Program, funded by OpenAI and Microsoft. Through this initiative, AI engineering fellow Rajesh Barade worked with the advertising team to address their challenges and developed a prospecting agent. This tool enables sales representatives to enter a category or focus area, identify businesses spending in that market, find decision-makers, access advertising spend data, and generate personalized outreach.

Mar 13, 2026

For years, the aggregator model was simple: curate the best journalism from thousands of publishers and send audiences their way. Now that contract is being rewritten, and Yahoo News is one of the most interesting places to watch it happen.

Mar 2, 2026

AI is settling in as infrastructure within newsrooms, a layer quietly reshaping how journalists discover information, how stories move through production, and how audiences increasingly expect news to reach them.

Mar 2, 2026

Most major newsrooms have now moved beyond early experimentation with AI. The main challenge now is determining how to govern effectively, scale consistently, and strategically position AI across the entire organization—while maintaining public trust as a central priority.

See all episodes →