Using Generative Agents to Create Tip Sheets for Investigative Data Reporting
This addresses the need for automated leads in investigative journalism, but it is incremental as it builds on existing generative AI methods for a specific domain.
The paper tackles the problem of generating tip sheets for investigative data reporting by using a system of three specialized generative AI agents, which produced more newsworthy and accurate insights compared to a baseline model, though with some variability across stories.
This paper introduces a system using generative AI agents to create tip sheets for investigative data reporting. Our system employs three specialized agents--an analyst, a reporter, and an editor--to collaboratively generate and refine tips from datasets. We validate this approach using real-world investigative stories, demonstrating that our agent-based system generally generates more newsworthy and accurate insights compared to a baseline model without agents, although some variability was noted between different stories. Our findings highlight the potential of generative AI to provide leads for investigative data reporting.