Machine Learning Reporting Grants
The Pulitzer Center's Machine Learning Reporting Grants support journalists using machine learning for ambitious, data-driven investigations that uncover systemic issues and complex patterns.
Funder: Pulitzer Center
Due Dates: Rolling
Funding Amounts: Flexible; typically up to $20,000, varies by project scope and needs.
Summary: Supports journalists worldwide to use machine learning in ambitious, data-driven investigations revealing systemic issues.
Key Information: Open to staff and freelance journalists globally; proposals must center machine learning in methodology.
Description
The Pulitzer Center’s Machine Learning Reporting Grants empower journalists to leverage machine learning as a core tool in their reporting, particularly for ambitious, data-intensive investigations. These grants are part of the Pulitzer Center’s AI Accountability Network and are designed to support innovative approaches that combine algorithmic analysis with traditional investigative methods. Funded projects have mapped environmental changes, forecast industrial risks, and revealed complex corporate ownership structures, demonstrating how machine learning can illuminate patterns and impacts that are otherwise difficult to detect.
The program encourages proposals that use advanced computational techniques—such as machine learning models, geospatial analysis, and satellite imagery—alongside established journalistic practices. The goal is to uncover systemic patterns, large-scale impacts, or hidden dynamics within complex datasets, especially on issues related to technology, environment, accountability, and social equity.
