Technology enables governments to engage in “pilot” projects to see where they are headed and course-correct along the way, as opposed to evaluating the results over the course of multiple years. Delivery-driven government utilizes technology and “pilot” projects to see institutions and processes through the eyes of users, allowing for more effective service delivery.
This toolkit provides guidance for state and local WIC agencies on implementing digital tools to enhance participant engagement and streamline program operations.
Accessing safety net benefits can involve complicated and duplicative processes that create barriers to access. Using cross-enrollment strategies can minimize the difficulties community members face in getting access to life-saving resources.
The article outlines NYC Opportunity's "Designed by Community" program, which funds and empowers local leaders to create solutions for challenges in marginalized communities. Initially focused on government projects, the program pivoted during the pandemic to support community-led initiatives, with projects ranging from mentorship programs to tech tools for public housing residents.
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.
PolicyEngine is a nonprofit that provides a free, open-source web app enabling users in the US and UK to estimate taxes and benefits at the household level, while also simulating the effects of policy changes. By combining tax and benefits data, PolicyEngine helps individuals and policymakers better understand the impacts of existing policies and proposed reforms, using microsimulation models built from legislation and enhanced survey data.
In our research announcement on theories of change (ToC) for digital government, the Digital Service Network shared our belief that all Digital Service (DS) teams should work to develop a ToC.
The team developed an AI solution to assist benefit navigators with in-the-moment program information, finding that while LLMs are useful for summarizing and interpreting text, they are not ideal for implementing strict formulas like benefit calculations, but can accelerate the eligibility process by leveraging their strengths in general tasks.
