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 framework provides voluntary guidance to help employers use AI hiring technology in ways that are inclusive of people with disabilities, while aligning with federal risk management standards.
This article explores how AI and Rules as Code are turning law into automated systems, including how governance focused on transparency, explainability, and risk management can ensure these digital legal frameworks stay reliable and fair.
This report highlights key findings from the Rules as Code Community of Practice, including practitioners' challenges with complex policies, their desire to share knowledge and resources, the need for increased training and support, and a collective interest in developing open standards and a shared code library.
