The examples in this guide describe how peer-to-peer training and updated interview scripts can help connect residents to the benefits they are eligible for.
A case study on how North Carolina leveraged human-centered design, interagency collaboration, and data-sharing strategies to improve cross-enrollment in SNAP, WIC, and Medicaid, aiming to reduce administrative burden and better serve families.
American Public Human Services Association (APHSA)
AI resources for public professionals on responsible AI use, including a course showcasing real-world applications of generative AI in public sector organizations.
This report 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 the U.S. federal government can enhance the efficiency and equity of benefit delivery by simplifying eligibility rules and using a Rules as Code approach for digital systems.
This brief outlines the U.S. federal government’s framework to identify, reduce, and address administrative burdens through a series of executive orders, legislative actions, and updated policies focused on improving customer experience and increasing access to government benefits.
