In December 2024, the Digital Benefits Network released an updated open dataset on authentication and identity proofing requirements across various public benefits applications to highlight best practices and areas for improvement in identity management.
This report summarizes findings and observations on the implementation of Phase 1 of the U.S. Department of Labor’s Open UI Initiative, highlighting effective strategies, challenges, opportunities, and recommendations for supporting states’ UI modernization efforts.
Led by the Digital Benefits Network in partnership with Public Policy Lab, the Digital Doorways research project amplifies the lived experiences of beneficiaries to provides new insights into people’s experiences with digital identity processes and technology in public benefits. This executive summary gives an overview of the project’s findings.
The Digital Benefits Network at the Beeck Center for Social Impact + Innovation at Georgetown University and Public Policy Lab co-hosted a webinar presenting breaking research on beneficiary experiences with digital identity processes in public benefits.
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.
This report provides detailed guidance for states on how to verify compliance with and exemptions from Medicaid work reporting requirements established under H.R. 1.
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.
An interactive dashboard that enables users to explore and monitor key metrics of the Supplemental Nutrition Assistance Program (SNAP) Quality Control (QC) system.
A unified taxonomy and tooling suite that consolidates AI risks across frameworks and links them to datasets, benchmarks, and mitigation strategies to support practical AI governance.
