How The New York Times is using generative AI as a reporting tool
LLMs help reporters transcribe and sort through hundreds of hours of leaked audio.
The rise of powerful generative AI models in the last few years has led to plenty of stories of corporations trying to use AI to replace human jobs. But a recent New York Times story highlights the other side of that coin, where AI models simply become a powerful tool aiding in work that still requires humanity’s unique skillset.
The NYT piece in question isn’t directly about AI at all. As the headline “Inside the Movement Behind Trump’s Election Lies” suggests, the article actually reports in detail on how the ostensibly non-partisan Election Integrity Network “has closely coordinated with the Trump-controlled Republican National Committee.” The piece cites and shares recordings of group members complaining of “the left” rigging elections, talking of efforts to “put Democrats on the defensive,” and urging listeners to help with Republican turnout operations.
To report the piece, the Times says it sifted through “over 400 hours of conversations” from weekly meetings by the Election Integrity Network over the last three years, as well as “additional documents and training materials.” Going through a trove of information that large is a daunting prospect, even for the team of four bylined reporters credited on the piece. That’s why the Times says in a note accompanying the piece that it “used artificial intelligence to help identify particularly salient moments” from the videos to report on.