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Staff from the Department of Government Efficiency (DOGE) used ChatGPT to screen National Endowment for the Humanities (NEH) grant descriptions for 'DEI' content. The AI's outputs, which included bizarre and inaccurate classifications, were used to justify the termination of over 1,000 grants, resulting in over $100 million in clawed-back funding and the closure of various humanities projects. Lawsuits filed by academic and professional organizations allege that these actions were unconstitutional, discriminatory, and violated the separation of powers.
Department of Government Efficiency (DOGE) staff reportedly fed National Endowment for the Humanities grant descriptions into ChatGPT to determine whether projects were "DEI," then allegedly used those outputs to help compile a list of grants to terminate. Beginning in April 2025, NEH canceled awards and clawed back funding, reportedly disrupting humanities organizations and projects nationwide after officials allegedly relied on a purportedly flawed, insufficiently vetted AI screening process.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Users anthropomorphizing, trusting, or relying on AI systems, leading to emotional or material dependence and inappropriate relationships with or expectations of AI systems. Trust can be exploited by malicious actors (e.g., to harvest personal information or enable manipulation), or result in harm from inappropriate use of AI in critical situations (e.g., medical emergency). Overreliance on AI systems can compromise autonomy and weaken social ties.
Also classified as
The automated screening process directly resulted in the systematic defunding of projects focusing on marginalized groups, which plaintiffs argue constitutes systemic discrimination.
ChatGPT exhibited a lack of capability and robustness by generating bizarre and inaccurate classifications, such as labeling a museum HVAC system as DEI.
The DOGE employees exhibited extreme overreliance on ChatGPT, blindly accepting its bizarre classifications to terminate over 1,000 federal grants without human verification or domain expertise.
Human
Due to a decision or action made by humans
Intentional
Due to an expected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The incident was primarily caused by the intentional decision of DOGE employees to use ChatGPT to automate high-stakes grant termination decisions, representing a human action.
Added categories peak at 2: Minor (Epistemic Harm, Direct)
DOGE staff used ChatGPT to screen and subsequently terminate over 1,000 NEH grants worth over $100 million, leading to massive staffing cuts and constitutional lawsuits. This represents a significant disruption of government functions and administrative processes through extreme overreliance on unverified AI classifications.
ChatGPT was used to analyze text and provide classifications ('Yes' or 'No' with brief explanations) to assist the DOGE employees in their screening task, requiring human oversight which was unfortunately neglected.
Risk Level 3. Limited Risk: The system used was ChatGPT, which is a chatbot, a category explicitly defined as posing moderate risk and requiring specific transparency obligations.
The AI system was explicitly used to evaluate and screen federal grant applications to determine their compliance with specific policy criteria.
The reports provide extensive, consistent details from court filings, depositions, and emails of the key actors (DOGE staff, NEH administrators, and plaintiffs). The specific prompt used, the exact responses from ChatGPT, and the financial/organizational impacts are thoroughly documented across multiple independent news sources.
One could argue the primary driver was political directive rather than AI failure, but the central role of ChatGPT in automating the selection of over 1,000 grants makes it a clear AI safety and overreliance incident.
Technology
Unconstrained LLM Classification
ChatGPT classified DEI without a defined taxonomy or safe operational limits.
Overbroad Algorithmic Logic
AI linked basic HVAC building upgrades to DEI through spurious logical leaps.
Data Inputs
Inadequate Input Summaries
Sourced short internet summaries instead of analyzing full grant proposals.
Lack of Defined DEI Criteria
No explicit definition of 'DEI' was provided in the prompt to guide the AI.
Human Factors
Automation Bias
DOGE employees accepted ChatGPT's classifications without critical questioning.
Lack of Domain Expertise
DOGE staff lacked humanities background to evaluate the validity of AI flags.
Process and Methods
Haphazard Screening Process
Used a chatbot to bypass established, rigorous scholarly peer-review processes.
Lack of Quality Control
No verification or review of AI outputs was conducted before cutting funds.
Rushed Evaluation Timeline
Extreme time pressure forced rapid, unverified algorithmic decision-making.
Management
Abdication of Leadership
NEH leadership yielded decision-making authority to unqualified outside staff.
Prioritizing Speed Over Rigor
Management prioritized rapid budget cuts over accurate policy implementation.
Regulatory Environment
Vague Executive Orders
Political directives banning DEI lacked clear legal or operational definitions.
Lack of AI Governance Rules
No federal rules governed using commercial LLMs for critical public funding.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
