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 quarterly research update aims to highlight key learnings related to improving unemployment insurance (UI) systems in the areas of equity, timeliness, and fraud, and monitor for model UI legislation and policy related specifically to technology. Subscribe to receive future editions.
EBT theft has deeply damaged the lives of the lowest-income Americans. The following insights reveal a system that leaves people in the dark and fails to protect a crucial lifeline.
Handbook by 18F designed for executives, budget specialists, legislators, and other “non-technical” decision-makers who fund or oversee state government technology projects that receive federal funding and implement the necessary technology to support federal programs. It aids in setting projects up for success by asking the right questions, identifying the right outcomes, and equally important, empowering decision-makers with a basic knowledge of the fundamental principles of modern software design.
This course is designed to help public professionals accelerate the process of finding and implementing urgently-needed evidence-based solutions to public problems.
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.
