This report examines how governments use AI systems to allocate public resources and provides recommendations to ensure these tools promote equity, transparency, and fairness.
This 11x17 service blueprint visualizes every step, system, and policy decision involved in implementing Medicaid work requirements under H.R. 1—from application to renewal—identifying pain points, questions, and opportunities for states to streamline and humanize the process
This report summarizes insights from interviews with seven states on how they are adapting integrated eligibility and enrollment (IEE) systems in response to sweeping federal changes to SNAP and Medicaid under H.R. 1.
This is a government catalog of reusable digital service components, templates, and patterns designed to help public sector teams build services more efficiently and consistently.
This framework provides a structured approach for ensuring responsible and transparent use of AI systems across government, emphasizing governance, data integrity, performance evaluation, and continuous monitoring.
This report analyzes how administrative burdens in SNAP caused one in eight working-age adults to lose benefits in 2024, with future federal policy changes expected to worsen disruptions
An in-depth report that examines how states use automated eligibility algorithms for home and community-based services (HCBS) under Medicaid and assesses their implications for access and fairness.
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 report outlining human-centered design strategies to help states implement new federal Medicaid work requirements in ways that minimize coverage loss and administrative burden
A report that reviews what has been learned from guaranteed income pilot projects in Massachusetts and situates those findings within the broader national evidence base.
