Through our research understanding the government digital service field and what workers in this field need, we want to help strengthen those existing roles and establish more pathways for promotion and career support, as well as help other teams recognize the value of these skills and create new roles.
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.
This article explores innovative strategies to improve access to public benefits by reducing administrative barriers and leveraging technology for a more user-friendly experience.
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
HOME-STAT partners existing homeless response and prevention programs with new innovations designed to better identify, engage, and transition homeless New Yorkers to appropriate services and, ultimately, permanent housing.
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.
The SDCI User Research Participant Compensation Policy establishes guidelines for providing honoraria to user research participants, ensuring equitable, ethical, and inclusive engagement in SDCI’s UX research.
Seattle Department of Construction & Inspections (SDCI)
This video documents the Digital Benefits Network's Digital Identity Community of Practice launch, covering mission review, 2025 goals, California authentication innovations, and peer networking for equitable and effective digital identity in public benefits.
This article examines how the City of Long Beach, California, collaborated with TOPC to develop a digital tool aimed at enhancing community engagement and expanding urban tree canopy coverage.
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
