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.
This case study examines how Michigan’s Department of Health and Human Services uses data practices to advance racial equity in child welfare through identity-informed data collection and anonymous decision-making.
U.S. Department of Health and Human Services (HHS)
This is the summary version of a report that 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.
This resource highlights strategies for integrating benefits renewals and correspondence, potentially reducing administrative burdens for both clients and caseworkers.
This brief describes the TANF Data Collaborative (TDC), an innovative approach to increasing data analytics capacity at state Temporary Assistance for Needy Families (TANF) agencies.
The Sprint 2 Report: Michigan UI Claimant Experience by Civilla and New America examines challenges in Michigan’s unemployment insurance (UI) system and provides human-centered design recommendations to improve accessibility, clarity, and user experience.
The Michigan Department of Health and Human Services, together with the Food Bank Council of Michigan and the Michigan Department of Education developed a comprehensive Food Insecurity Map and a closed-loop referral system for nutrition and economic supports.
American Public Human Services Association (APHSA)
