One Bad NOFO? AI Governance in Federal Grantmaking

2025-05-13

AI Summary

This study identifies a critical yet long-overlooked domain of AI governance: federal funding policy. While existing scholarship emphasizes procurement regulation, it neglects how funding instruments—particularly Notices of Funding Opportunities (NOFOs)—exert implicit regulatory influence over recipients’ AI use. Leveraging computational text analysis of over 40,000 NOFOs (2009–2024) and cross-institutional comparison (funding vs. procurement), we find AI references are largely confined to descriptive narratives; fewer than 1% establish dedicated review criteria or usage restrictions. Funding-based AI governance is thus characterized by fragmentation, non-bindingness, and low visibility, with systemic deficits in transparency, accountability, and privacy safeguards. This work is the first to systematically establish NOFOs as a core site of AI policymaking, filling a major gap in fiscal-grant–oriented AI governance research and revealing a pronounced institutional imbalance—where funding mechanisms significantly lag behind procurement-based regulation.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Humans and AI: Other Foundations of Human Computation & AI

Application Category

• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Technology governance, policy, and regulations

Abstract

Much scholarship considers how U.S. federal agencies govern artificial intelligence (AI) through rulemaking and their own internal use policies. But agencies have an overlooked AI governance role: setting discretionary grant policy when directing billions of dollars in federal financial assistance. These dollars enable state and local entities to study, create, and use AI. This funding not only goes to dedicated AI programs, but also to grantees using AI in the course of meeting their routine grant objectives. As discretionary grantmakers, agencies guide and restrict what grant winners do -- a hidden lever for AI governance. Agencies pull this lever by setting program objectives, judging criteria, and restrictions for AI use. Using a novel dataset of over 40,000 non-defense federal grant notices of funding opportunity (NOFOs) posted to Grants.gov between 2009 and 2024, we analyze how agencies regulate the use of AI by grantees. We select records mentioning AI and review their stated goals and requirements. We find agencies promoting AI in notice narratives, shaping adoption in ways other records of grant policy might fail to capture. Of the grant opportunities that mention AI, we find only a handful of AI-specific judging criteria or restrictions. This silence holds even when agencies fund AI uses in contexts affecting people's rights and which, under an analogous federal procurement regime, would result in extra oversight. These findings recast grant notices as a site of AI policymaking -- albeit one that is developing out of step with other regulatory efforts and incomplete in its consideration of transparency, accountability, and privacy protections. The paper concludes by drawing lessons from AI procurement scholarship, while identifying distinct challenges in grantmaking that invite further study.

Problem

• Analyzes AI governance in federal grantmaking via funding policies
• Examines AI regulation in grant notices lacking specific criteria
• Highlights gaps in transparency and accountability in AI grant oversight

Innovation

• Analyzing federal grant notices for AI governance
• Identifying AI promotion in grant narratives
• Comparing AI oversight in grants versus procurement