A visual journey map that outlines the end-to-end steps, roles, and decisions involved in procuring cloud migration support services for modernizing a legacy system.
Explains that government service forms should be designed to reduce anxiety and build trust—especially for marginalized people—by minimizing requests for highly sensitive personal information or explaining clearly why and how such data will be used, making optional fields and alternatives available, and providing context and reassurance throughout the application process.
A virtual event showcasing how one city applied technology, including artificial intelligence, to streamline municipal code administration and reduce bureaucratic friction.
A comprehensive assessment that maps how artificial intelligence is currently being used, governed, and managed across local, state, and federal governments in the United States.
A practical accessibility framework that provides testable heuristics to help designers and developers evaluate and improve the inclusivity of data visualizations and data-driven interfaces.
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.
A practical framework from the UK Infrastructure and Projects Authority that helps government leaders plan, lead, and deliver complex transformation programs.
The team examined how AI, specifically LLMs, could streamline the case review process for SNAP applications to alleviate the burden on case workers while potentially improving accuracy.
There are frameworks available that could inform the standardization of communicating rules as code for U.S. public benefits programs. The Airtable communicates the differences between the frameworks and tools. Each entry is tagged with different categories that identify the type of framework or tool it is.
