This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
An America where no one experiences poverty is possible. Already, the U.S. has programs with the potential to make this vision a reality, including programs that provide cash assistance, like Temporary Assistance for Needy Families (TANF). The current TANF program provides very little cash assistance and is marked by stark racial disparities, but it has the potential to reduce child poverty, increase economic security, and advance racial equity. This report offers a vision for an anti-racist approach to the TANF program, with new statutory goals and policy recommendations to advance racial justice.
This kit contains a collection of styles, components, and building blocks to quickly create action-forward emails for Unemployment Insurance programs within the U.S.
The Better Government Lab at the McCourt School of Public Policy at Georgetown University has developed a new scale for measuring the experience of burden when accessing public benefits. They offer both a three-item scale and a single-item scale, which can be utilized for any public benefit program. The shorter scales provide a less burdensome way to measure by requiring less information from users.
This guide discusses general characteristics shared by organizations that have successfully created accessible content, and includes case studies that showcase characteristics of successful accessible content teams.
This book is an in-depth exploration of federal programs and controversial legislation demonstrating that administrative burden has long existed in policy design, preventing citizens from accessing fundamental rights. Further discussion of how policymakers can minimize administrative burden to reduce inequality, boost civic engagement, and build an efficient state.
Professor Don Moynihan discusses how administrative burden is an effective tool to make it difficult for people to access certain types of benefits, noting that this is particularly harmful to communities of color.
This paper introduces a framework for algorithmic auditing that supports artificial intelligence system development end-to-end, to be applied throughout the internal organization development lifecycle.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
Little is known about how agencies are currently using AI systems, and little attention has been devoted to how agencies acquire such tools or oversee their use.
