Errors in administrative processes are costly and burdensome for clients but are understudied. Using U.S. Unemployment Insurance data, this study finds that while automation improves accuracy in simpler programs, it can increase errors in more complex ones.
This post explores the lessons learned and opportunities for improvement from USDR's research on families' experiences as they navigate the child care journey.
To improve the .gov registrar, 18F and CISA created customer panels to gather feedback, opinions, and suggestions. Using a customer-centric approached enabled 18F and CISA to identify areas for improvement, build a product roadmap, and establish relationships with users.
This workshop summary provides practical guidance for web developers and designers on implementing accessible web design practices, emphasizing the importance of inclusivity and usability for all users.
The team developed an AI-powered explanation feature that effectively translates complex, multi-program policy calculations into clear and accessible explanations, enabling users to explore "what-if" scenarios and understand key factors influencing benefit amounts and eligibility thresholds.
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.
