A Trustworthy AI Assistant for Investigative Journalists | Stanford HAI
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A Trustworthy AI Assistant for Investigative Journalists
Date, December 01, 2025, Topics
Communications, Media
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Gathering and analyzing data require time and expertise — two resources that cash-strapped newspapers often don’t have. Can AI help?
In 2023, an average of 2.5 local newspapers shut down every week. More than half of U.S. counties now have little or no reliable local news coverage, and the trend is accelerating.
This is a business problem. It is also, arguably, a democracy problem. For centuries, local journalism has kept voters engaged in local politics and politicians accountable to those voters. Small papers with investigative tenacity have also routinely broken stories of national importance — the Patriot-News uncovering Penn State’s Jerry Sandusky scandal, for instance.
The answer to this crisis? “Everybody says, ‘Let’s use AI to help,’ ” replies Monica Lam, a professor of computer science at Stanford University. The problem with this, she adds, is that most AI tools aren’t reliable. She cites a 2025 study conducted by the BBC in which the media outlet used major AI models to analyze news content on its website. Over half of answers from the AI had “significant issues,” according to the BBC, including factual errors and fabricated quotations.
“It’s not so easy,” says Lam.
Now, Lam is working with technologists and journalists to develop a more useful tool for the news industry. With Cheryl Phillips, the founder of Stanford’s Big Local News, along with seed funding from the Stanford Institute for Human-Centered AI and a grant from the Brown Institute for Media Innovation at Stanford and Columbia, Lam created DataTalk, a chatbot specifically designed to help investigative journalists and cash-strapped newsrooms do their work more efficiently without sacrificing factual accuracy. DataTalk is built on top of a large language model and designed to retrieve and analyze information kept in big, sometimes unruly, public databases.
“Journalism is losing a lot of people and deep investigative work is harder than ever,” Lam says. “If more people know about the tool we’re building, and if we can keep improving it and keep generating success stories, then our hope is to bolster this type of journalism into the future.”
What is DataTalk?
Investigative journalists often rely on knowledge of database languages like SQL and the expertise of data scientists to unearth important stories. With DataTalk, they could instead simply type their question into a chat window and get an answer within a few seconds.
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