An article examining how automation and AI are being used in welfare systems, arguing that digital benefits administration often reproduces longstanding patterns of surveillance, exclusion, and inequality.
This discussion paper advocates for states to use the implementation of OBBBA (One Big Beautiful Bill Act) as a catalyst to build integrated, cross-agency data systems.
This article provides an overview of the Medicaid Payment Error Rate Measurement (PERM) program and examines how the 2025 budget reconciliation law introduces new federal funding reductions for states that exceed specific eligibility error thresholds.
This page provides a U.S. Web Design System pattern for collecting pronoun information in user profiles in a way that respects identity, supports data standards, and promotes inclusion.
A practical guide for advocates that explains how automated benefit notices are generated, where common notice failures originate, and how to push for effective fixes.
This report highlights the agency's role in transforming federal digital services through human-centered design, agile technology, and cross-agency collaboration.
In accordance with Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government, Federal agencies began publishing their first annual inventories of artificial intelligence (AI) use cases in June 2022.
The Digital Service Network is publishing two essays to kick-start new (or super-charge existing) theories of change for government Digital Service teams.
Applicants to federal aid programs face numerous barriers in accessing benefits they are eligible for. The Centers for Medicaid and Medicare conducted an extensive qualitative user research study to better understand applicant experience in enrolling in public assistance programs. Based on the results, the study emphasizes the need for simplified, streamlined and less burdensome application processes.
This video shows you how to get started with using Generative AI tools, including Bard, Bing, and ChatGPT, in your work as public sector professionals.
This study examines how individuals assess administrative burdens and how these views change over time within the context of the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC).
