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.
This report examines how recent federal spending cuts and policy changes are shifting costs onto county governments, potentially burdening local budgets and services.
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.
In this updated primer, the DBN introduces the concept of digital identity, and provides brief snapshots of digital identity-related developments internationally and in the U.S.
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.
This paper outlines the need for comprehensive reforms to improve the U.S. government's capacity to effectively implement policies, focusing on reducing bureaucratic inefficiencies, enhancing workforce structures, and leveraging digital infrastructure.
This report examines how governments use AI systems to allocate public resources and provides recommendations to ensure these tools promote equity, transparency, and fairness.
