This study examines how the 2021 expansion of the Child Tax Credit (CTC) influenced housing affordability and living arrangements for low-income families.
This article explores how AI and Rules as Code are turning law into automated systems, including how governance focused on transparency, explainability, and risk management can ensure these digital legal frameworks stay reliable and fair.
This article explores how legal documents can be treated like software programs, using methods like software testing and mutation analysis to enhance AI-driven statutory analysis, aiding legal decision-making and error detection.
The article analyzes the impacts of Arkansas's Medicaid work requirements, finding that while coverage losses were reversed after the policy was halted, it did not improve employment and led to negative consequences such as increased medical debt and delayed care.
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
This introductory guide explains the core concepts of digital identity and how they apply to public benefits programs. This guide is the first part of a suite of voluntary resources from the BalanceID Project: Enabling Secure Access and Managing Risk in SNAP and Medicaid.
This paper explores how legacy procurement processes in U.S. cities shape the acquisition and governance of AI tools, based on interviews with local government employees.
This paper examines the challenges U.S. state and local digital service teams face in retaining talent and offers strategies to improve retention and team stability.
This report presents new national survey data showing how benefits cliffs and asset limits negatively affect the economic mobility of low-wage workers in the U.S.
