This past weekend, the Brown Institute at Columbia and Hacks/Hackers, a nonprofit, put on a three-day event called the Open Source AI Hackathon. The idea, according to Burt Herman, the board chair of Hacks/Hackers and one of the founders of the organization, was to get journalists and coders into a room to talk about what they could build together. There were students, reporters, engineers, and AI-curious participants of different stripes. Some came with specific ideas about things they wanted to build. Others just wanted to find people with complementary skill sets and learn about building tools with AI.
Much has been made of the impact that AI-powered technologies could have (and, in some cases, are already having) on newsrooms. The technology has raised concerns among journalists about whether text-generating machines could produce — or at least passably mimic — what human professionals do. But there is something different about the challenge for the news media, an industry already casting around for any kind of foothold. The thesis of the Hackathon was that large-language-model tools actually have many potential applications in journalism. Broadly, the projects fell into two categories: those exploring the ways AI can be used as a journalistic or investigative tool and those experimenting with new ways of delivering media to consumers.
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