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.
This report poses the question of whether states are prepared to meet the new Medicaid work reporting and renewal mandates introduced by HR 1, given ongoing strain from the post-pandemic “unwinding.”
The Digital Identity Community of Practice kick-off event featured key resources, a new research publication on account creation and identity proofing, and insights from multiple speakers.
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.
This academic paper examines predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals. Through this examination, the authors explore how predictive optimization can raise concerns that make its use illegitimate and challenge claims about predictive optimization's accuracy, efficiency, and fairness.
A blog recap of a FormFest session on improving digital form accessibility, with a focus on accessible error handling and WCAG 2.1 compliance under Title II requirements.
The article examines the impact of digital interfaces on welfare state administration, focusing on the UK's Universal Credit system and the design elements that shape user interactions and behavior in an "interface first" bureaucracy.
Algorithmic impact assessments (AIAs) are an emergent form of accountability for organizations that build and deploy automated decision-support systems. This academic paper explores how to co-construct impacts that closely reflects harms, and emphasizes the need for input of various types of expertise and affected communities.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
