Accounting for the strong effects of health care access, this study finds that SNAP is associated with reduced hospitalization in dually eligible older adults. Policies to increase SNAP participation and benefit amounts in eligible older adults may reduce hospitalizations and health care costs for older dual eligible adults living in the community.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
This article explores how anticipatory logics—drawing from foresight, futures thinking, and design—are shaping the future of government by creating space for innovative policy approaches, public participation, and proactive governance.
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 study investigates how administrative burdens influence differential receipt of income transfers after a family member loses a job, looking at Unemployment Insurance, Temporary Assistance for Needy Families, and the Supplemental Nutrition Assistance Program.
Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. This academic study presents an approach to evaluate bias present in automated facial analysis algorithms and datasets.
This article analyzes the strategic use of public policy as a tool for reshaping public opinion. Though progressive revisionists in the 1990s argued that reforming welfare could produce a public more willing to invest in anti-poverty efforts, welfare reform in the 1990s did little to shift public opinion. This study investigates the general conditions under which mass feedback effects should be viewed as more or less likely.
This study examines the adoption and implementation of AI chatbots in U.S. state governments, identifying key drivers, challenges, and best practices for public sector chatbot deployment.
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)
An article examining how automation and AI are being used in welfare systems, arguing that digital benefits administration often reproduces longstanding patterns of surveillance, exclusion, and inequality.
This guide is a practical introduction to Digital Service Teams (DSTs) for state and local governments. It is designed to help leaders interested in standing up new government DSTs understand what they are, why they exist, and how they are structured, staffed, funded, and more.
