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.
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.
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.
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 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)
Code for America helped expand GetCalFresh (a service that guides Californians through the SNAP application process and helps government deliver food assistance to people in need) from a small pilot into a statewide service. They also recently concluded a similar pilot in Michigan along with Civilla and the Michigan Department of Health and Human Services.
This case study highlights Michigan’s integrated, data-driven approach to reducing food insecurity through cross-agency collaboration, referral tracking, and targeted outreach.
American Public Human Services Association (APHSA)
