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 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.
Through deeply reported case studies and insights from focus groups, this report provides an in-depth look at the impact of pandemic-era government spending on families.
This paper discusses the country’s chronic underinvestment in children and resulting outcomes, including new data on poverty rates among young children, is inextricable from the prospects of young children; and the remarkably comprehensive pandemic-era response policies, including which changes contributed most to reducing child poverty.
This report explores the role that academic and corporate Research Ethics Committees play in evaluating AI and data science research for ethical issues, and also investigates the kinds of common challenges these bodies face.
