Global AI challenge to transform investigative journalism : For Journalists

A contest led by Northwestern University aims to build AI “agent skills” to enhance investigative journalism processes, encouraging journalists, data scientists, developers, and technologists to create AI bundles to streamline investigations.
The contest, named the Agentic AI Investigative Journalism Challenge, seeks to make investigative reporting faster, cheaper, and more transparent. It launches on May 15 and ends on July 15.
The event emphasizes that while AI aims to support journalists, it should not replace them, instead providing insights and suggesting leads and patterns from large datasets.
Competing teams will use the model Claude AI on a provided dataset involving U.S. House and Senate lobbying disclosures and press releases to develop replicable workflows.
Successful submissions will need to include interaction traces, a detailed README, and assessment of potential legal violations to ensure transparency.
The goal is to demonstrate the practicality and repeatability of these workflows for various datasets and investigative pursuits, fostering collaboration among journalists.
This initiative is part of a larger effort to establish responsible generative AI practices in news production, funded by a $1 million grant from the Knight Foundation and collaborating with Northwestern’s School of Communication and Medill School of Journalism.