A unified taxonomy and tooling suite that consolidates AI risks across frameworks and links them to datasets, benchmarks, and mitigation strategies to support practical AI governance.
An interactive chatbot that helps SNAP participants and the public ask questions and receive guidance about SNAP work and community engagement requirements in conversational form.
A recap of a community innovation hackathon in Seattle where technologists and students used AI to prototype solutions that help youth discover and access local programs and services.
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, step-by-step guide for government agencies to design, implement, and evaluate community engagement efforts around the use of artificial intelligence.
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.
Public procurement in state governments can be slow and inefficient, but artificial intelligence (AI) offers a solution by automating tasks, improving decision-making, and addressing workforce gaps, as highlighted in a joint brief by NASCIO and NASPO.
National Association of State Chief Information Officers (NASCIO)
The team explored the performance of various AI chatbots and LLMs in supporting the adoption of Rules as Code for SNAP and Medicaid policies using policy data from Georgia and Oklahoma.
The team developed an application to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
