The report examines how current remote identity proofing methods can create barriers to Medicaid enrollment and suggests improvements to ensure equitable access for all applicants.
Annual Computers, Software, and Applications Conference (COMPSAC)
The article examines the effects of Arkansas’s Medicaid work requirements, finding substantial coverage losses and no significant increase in employment, compounded by widespread confusion among beneficiaries about the policy.
An academic research paper introducing SHADES, a multilingual benchmark designed to evaluate how large language models (LLMs) generate and reinforce stereotypes across different languages and cultural contexts.
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 study examines public attitudes toward balancing equity and efficiency in algorithmic resource allocation, using online advertising for SNAP enrollment as a case study.
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 paper concludes that the substantial COVID-19 unemployment insurance expansion had limited disincentive effects on job searches, particularly among lower-income individuals, despite high wage replacement rates.
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.
Medicaid and SNAP have reduced racial and ethnic disparities in healthcare access and food security, but some administrative and eligibility policies continue to create inequitable barriers.
This article explores how integrating behavioral science into public administration can improve government effectiveness, equity, and trust by redesigning public services with human behavior in mind.
This article investigates how users' "metamemory"—specifically their anxiety regarding their own memory capabilities—drives insecure password behaviors.
