This brief highlights key takeaways from APHSA’s work on young families, starting with an overview of the young families work and its early years, followed by key takeaways and highlights from its final year, ending with opportunities for future work in the young families space.
American Public Human Services Association (APHSA)
This article reviews two examples of how Nava has used open-source technologies to bring human-centered testing practices to government services software.
This piece highlights promising design patterns for account creation and identity proofing in public benefits applications. The publication also identifies areas where additional evidence, resources, and coordinated federal guidance may help support equitable implementations of authentication and identity proofing, enabling agencies to balance access and security.
This booklet is designed to help procurement officers and other stakeholders ensure continuity of service, enable seamless future technology upgrades, and plan for contingencies. You can use it to evaluate a prospective vendor contract or bid, or to document how a project went.
Governments and leaders are required to regulate change while mitigating risk, so IFTF's Governance Futures Lab developed this decision-making guide for them. In a world where technologies are transforming faster than we can keep up, anticipatory governance is crucial in order to safeguard against both the intended and unintended effects of technological advances.
The US General Services Administration announces that it is seeking a limited number of state and local government partners to take advantage of login.gov to administer their federally funded programs.
This blog introduces Code for America’s new service blueprint for Medicaid work requirements, highlighting how it can help states map system changes, identify pain points, and prioritize human-centered design.
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.
