This FormFest profile highlights Riverside County’s pilot of AI-powered interviews that streamline benefit applications, reducing bureaucratic burden on families in crisis while freeing caseworkers to focus on human connection.
This publication summarizes a body of research about how state benefits administering agencies build and maintain integrated eligibility and enrollment (IEE) systems. It is an easy to reference guide for state administrators, legislators, advocates, and delivery partners.
This cheat sheet helps job seekers translate private-sector technology roles and skills into equivalent U.S. government job classifications and titles.
This one-pager introduces Iowa’s Child Care Search tool, a family-friendly application that helps users find real-time child care vacancies based on their commute, preferences, and provider offerings.
This video demonstrates how to use Iowa's Child Care Connect (C3), a centralized data system that integrates near-real-time child care data to support families, providers, policymakers, and economic development efforts across the state.
The article highlights the growing issue of SNAP benefit theft through skimming and advocates for permanent security measures and benefit replacements to protect vulnerable households.
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
An updated guide for public sector and civic data users to embed racial equity and community voice throughout the data life cycle—from planning to dissemination.
This framework provides practical guidance, detailed reference designs, and example solutions to help organizations securely adopt and operationalize Zero Trust principles across diverse IT environments.
National Institute of Standards and Technology (NIST)
This profile provides a cross-sectoral profile of the AI Risk Management Framework specifically for Generative AI (GAI), outlining risks unique to or exacerbated by GAI and offering detailed guidance for organizations to govern, map, measure, and manage those risks responsibly.
National Institute of Standards and Technology (NIST)
