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 handbook provides local governments with practical guidelines, best practices, and ethical considerations for adopting and using AI tools, emphasizing transparency, human oversight, and risk management.
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 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.
Michigan's UIA director, Julia Dale, is leading the agency through transition by prioritizing lived experience, hope, grit, and values. Virginia's SNAP Program Manager, Michele Thomas, highlighted the success of Sun Bucks, a summer EBT child nutrition program that fed over 700,000 kids in its first year.
Michigan's UIA director, Julia Dale, is leading the agency through transition by prioritizing lived experience, hope, grit, and values. Virginia's SNAP Program Manager, Michele Thomas, highlighted the success of Sun Bucks, a summer EBT child nutrition program that fed over 700,000 kids in its first year.
This dashboard provides a comprehensive view of underlying trends in unemployment across Michigan. It serves as an invaluable resource for understanding the impacts of unemployment on various industries, occupations, and communities. By providing detailed insights into sectors experiencing layoffs, claimant demographics, and the regions most affected, the dashboard equips us with the data needed to develop targeted solutions tailored to the needs of Michiganders.
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 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. The goal of these initiatives was to leverage cross-sector data to inform policy decisions, streamline access to food assistance, and reduce administrative burden. This report documents lessons learned and outcomes of their project.
American Public Human Services Association (APHSA)
