This factsheet outlines the Administration for Children and Families’ (ACF) 2024 initiatives to promote health equity across its programs by embedding equity into funding, service delivery, and community engagement.
U.S. Department of Health and Human Services (HHS)
This article advises government agencies to prioritize cybersecurity methods over AI-driven approaches when combating identity fraud in benefits programs, highlighting potential risks that automated systems pose to legitimate applicants.
Executed April 3, 2025, this memo provides federal agencies with government-wide guidance for accelerating AI adoption through innovation, governance, and public trust.
This guide helps UK public bodies understand how to responsibly procure, develop, and use AI while meeting their legal duties to prevent discrimination and promote equality under the Public Sector Equality Duty (PSED).
This report highlights the agency's role in transforming federal digital services through human-centered design, agile technology, and cross-agency collaboration.
The AI RMF Playbook offers organizations detailed, voluntary guidance for implementing the NIST AI Risk Management Framework to map, measure, manage, and govern AI risks effectively.
National Institute of Standards and Technology (NIST)
This is a searchable tool that compiles and categorizes over 4,700 policy recommendations submitted in response to the U.S. government's 2025 Request for Information on artificial intelligence policy.
This is a modular, dynamic roadmap guides the U.S. HHS's ongoing implementation of open data policies while inviting public collaboration and feedback.
U.S. Department of Health and Human Services (HHS)
Federal guidelines for digital identity services, outlining technical and procedural requirements for identity proofing, authentication, and federation.
National Institute of Standards and Technology (NIST)
This report warns that federal data collection is being undermined by budget cuts, political interference, and leadership changes that threaten the reliability of core economic and social statistics.
This framework provides a structured approach for ensuring responsible and transparent use of AI systems across government, emphasizing governance, data integrity, performance evaluation, and continuous monitoring.
