Working with TANF administrators and human services leaders across the country, the American Public Human Services Association (APHSA) embraces the call to reimagine how TANF can work in support of the families it serves and has established a set of TANF Modernization Core Principles to guide our vision for the future of TANF. Grounded in these Core Principles, APHSA’s members have laid out a legislative framework to unlock the potential of TANF. We call upon Congress to use this framework as a starting point to build common ground to achieve a TANF reauthorization that promotes a more equitable and prosperous future for all Americans.
American Public Human Services Association (APHSA)
Based on user interviews with families across the United States who navigated the Medicaid renewal process, this report offers insights and recommendations for improving the experience of renewing Medicaid and other benefits.
BenCon 2024 explored state and federal AI governance, highlighting the rapid increase in AI-related legislation and executive orders. Panelists emphasized the importance of experimentation, learning, and collaboration between government levels, teams, agencies, and external partners.
The study investigates how state agencies administering SNAP comply with Title VI of the Civil Rights Act by providing language access for individuals with limited English proficiency (LEP).
This section of the Building Resilience plan outlines strategies to help states modernize outdated unemployment insurance (UI) IT systems, making them more modular, secure, fraud-resistant, and user-centered.
This policy brief outlines how extending postpartum Medicaid and CHIP coverage can improve maternal health outcomes, reduce disparities, and strengthen continuity of care during the critical first year after childbirth.
A report that defines what effective “human oversight” of AI looks like in public benefits delivery and offers practical guidance for ensuring accountability, equity, and trust in algorithmic systems.
A practical toolkit that helps human services agencies coordinate programs and benefits to better support whole families through aligned policies, processes, and service delivery.
This research explores how software engineers are able to work with generative machine learning models. The results explore the benefits of generative code models and the challenges software engineers face when working with their outputs. The authors also argue for the need for intelligent user interfaces that help software engineers effectively work with generative code models.
