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.
Drawing on the Beeck Center’s research on government, nonprofit, academic, and private sector organizations that are working to improve access to safety net benefits, this report highlights best practices for creating accessible benefits content.
This Urban Institute report highlights how immigrant and mixed-status families continued to avoid safety net programs in 2023 due to lingering fears around the public charge rule.
Presentation covering the findings of a research study analyzing the structural and budgetary layout of of eleven US-based Digital Service Teams (DSTs) at the municipal, county, and state levels.
The Policy2Code Prototyping Challenge explored utilizing generative AI technology to translate U.S. government policies for public benefits into plain language and code, culminating in a Demo Day where twelve teams showcased their projects for feedback and evaluation.
This bill authorizes the U.S. Digital Service to make a grant to a state, Indian tribe, or local government to establish or support a team of relevant experts dedicated to modernizing the delivery of government services to the public through information technology. A state, tribe, or local government may receive up to two such grants.
This page includes data and observations about authentication and identity proofing steps specifically for online applications that include MAGI Medicaid.
