This paper argues that a human rights framework could help orient the research on artificial intelligence away from machines and the risks of their biases, and towards humans and the risks to their rights, helping to center the conversation around who is harmed, what harms they face, and how those harms may be mitigated.
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 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 study describes the potential of human-centered design principles to identify burdens, reducing the effects of what we label as administrative checkpoints.
This paper analyzes the unique challenges of conducting participatory design in large-scale public projects, focusing on stakeholder management, fostering engagement, and integrating participatory methods into institutional transformation.
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 article discusses the challenges of today’s centralized identity management and investigates current developments regarding verifiable credentials and digital wallets.
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.
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.
