AI Use by the US Government

2026-06-17 · Source: Schneier on Security · Field: Government & Public Sector — Public Policy & Governance, Digital Government & E-Government, Public Safety & Security · Depth: Fundamental Awareness, medium

Summary

The Trump administration's Office of Management and Budget (OMB) disclosed 3,611 active or planned AI use cases across the US federal government on April 14, a 70% increase from the Biden administration's final year. This expansion includes concerning applications like HHS using Palantir to scan grant applications for ideological alignment, the Federal Bureau of Prisons assessing inmate misconduct risk, and the Department of Veterans Affairs evaluating suicide risk from crisis calls. While some uses, such as the Department of Energy controlling nuclear reactors or Customs and Border Protection's 70 AI translation systems, could be implemented responsibly, the current disclosure lacks crucial context and public consultation. The inventory's minimal information and inconsistent "high impact" labeling hinder public understanding and trust, despite AI's potential for improving government efficacy and accessibility.

Key takeaway

For policy makers and agency leaders evaluating AI integration, the US government's rapidly expanding AI use, now at 3,611 cases, demands immediate attention to transparency and public consultation. You should implement robust algorithmic impact assessments and mandatory public comment periods, mirroring models from France or Canada, to build trust and ensure equitable, safe AI deployment across federal and state agencies.

Key insights

Government AI use is rapidly expanding, necessitating robust transparency and public consultation to ensure responsible and trusted deployment.

Principles

• AI can enhance government efficacy, efficiency, and accessibility.
• Transparency and public dialogue are critical for building AI trust.
• Algorithmic impact assessments are essential for safe AI deployment.

Method

Implement algorithmic impact risk assessment procedures and public comment processes to facilitate safe, trusted, and equitable transformation of government agencies with AI.

In practice

• Examine Washington D.C. and California's public engagement models.
• Review France's Digital Republic Act for algorithm transparency.
• Study Canada's AI use case registry and impact assessment process.

Topics

• AI Governance
• Government AI Use Cases
• Algorithmic Transparency
• Public Consultation
• AI Policy
• Algorithmic Impact Assessment

Code references

• ombegov/2025-Federal-Agency-AI-Use-Case-Inventory

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Policy Maker, AI Ethicist, Tech Journalist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Schneier on Security.