This report presents evidence on the use of algorithmic accountability policies in different contexts from the perspective of those implementing these tools, and explores the limits of legal and policy mechanisms in ensuring safe and accountable algorithmic systems.
18F, a consultancy within the U.S. General Services Administration, developed a prototype API and pre-screener to model federal SNAP eligibility rules, aiming to simplify benefits access through open-source technology.
In this report, the U.S. Chamber of Commerce Foundation examines benefits cliffs – the loss of eligibility for public safety-net programs and benefits they provide as income rises above eligibility limits.
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.
Closing the Medicaid coverage gap could significantly reduce healthcare disparities as 65% of those affected are people of color, specifically impacting low-wage workers and caregivers who often experience economic and health vulnerabilities.
BenCon 2024 explored state and federal AI governance, highlighting the rapid increase in AI-related legislation and executive orders. Panelists emphasized the importance of experimentation, learning, and collaboration between government levels, teams, agencies, and external partners.
This blog presents a service blueprint that maps how expanded SNAP work requirements will affect the application, eligibility, and maintenance processes—and offers design recommendations to reduce administrative burden.
A report outlining human-centered design strategies to help states implement new federal Medicaid work requirements in ways that minimize coverage loss and administrative burden
During this event, researchers addressed questions with findings from data collected from state UI agencies across the country and focus groups with women who have experienced unemployment.
A comprehensive guide that provides role definitions, hiring guidance, interview materials, and evaluation rubrics for building effective UX design and research teams.
