Location: Michigan (MI)
-
Human Centered Design to Improve Civil Court Form Accessibility in Michigan: A FormFest 2025 Profile
This FormFest profile highlights Rachael Zuppke and Molly Graham’s work to redesign Michigan’s civil court forms using human-centered design, making them more accessible for people who must represent themselves in critical cases like eviction, family law, and guardianship.
-
Michigan Unemployment Insurance Agency’s (UIA) Economic Dashboard
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.
-
TANF Data Collaborative Pilot: Analyzing Application Denial Rates in Michigan
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.
-
Integrating Renewals and Correspondence
This resource highlights strategies for integrating benefits renewals and correspondence, potentially reducing administrative burdens for both clients and caseworkers.
-
MDHHS-1171 Assistance Application and Program Supplements
Michigan Department of Health and Human Service's benefits application form.
-
Four Lessons from Our Journey to Deliver Human-Centered Integrated Benefits
Code for America partnered with the CBPP, Civilla, and Nava to launch the Integrated Benefits Initiative, testing and piloting human-centered approaches to improve outcomes and learn what an optimal safety net could look like. This article describes key takeaways from short-term pilots implemented as part of this project.
-
AI-Powered Rules as Code: Experiments with Public Benefits Policy
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.