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.
PolicyEngine US is a Python-based microsimulation model of the US tax and benefit system. It models federal individual income taxes (including credits), major benefit programs, and state income taxes (currently in six states). The PolicyEngine US package can be used as a Python package, via the PolicyEngine API, or via the policyengine.org web app.
At Rules as Code Demo Day we heard from Song Hia of the NYC Mayor’s Office for Economic Opportunity and Ethan Lo of the NYC Office of Technology and Innovation who demoed the NYC Benefits Platform Screening API which provides machine-readable calculations and criteria for benefits screening that power the ACCESS NYC screening questionnaire. This makes it easier for NYC residents to discover multiple benefits they may be eligible for. The City is now extending the API to support the new MyCity platform, a one-stop shop for all services and benefits.
The team explored the performance of various AI chatbots and LLMs in supporting the adoption of Rules as Code for SNAP and Medicaid policies using policy data from Georgia and Oklahoma.
There are frameworks available that could inform the standardization of communicating rules as code for U.S. public benefits programs. The Airtable communicates the differences between the frameworks and tools. Each entry is tagged with different categories that identify the type of framework or tool it is.
Created by Benefits Data Trust, Benefits Launch Express is a high-level eligibility screening and assistance finder available to Philadelphia residents. The tool screens eligibility for 29 programs and is estimated to take up to 10 minutes to complete.
beta.gouv.fr, a French government incubator, developed Mes Aides, an online benefits simulator launched in 2014 to help residents assess their eligibility for various social programs, addressing the issue of unclaimed benefits. The tool, built with open-source technology, enabled users to quickly estimate their potential benefits but was later integrated into a broader platform in 2020 following internal government disputes over authority.
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.
The Policy Rules Database (PRD), developed by the Federal Reserve Bank of Atlanta and the National Center for Children in Poverty, consolidates complex rules for major U.S. federal and state benefit programs and tax policies into a standardized, easy-to-use format. This database allows researchers to model public assistance impacts, simulate policy changes, and analyze benefits cliffs across various household scenarios using common rules and language across different programming platforms.
The Atlanta Fed’s CLIFF tools provide greater transparency to workers about potential public assistance losses when their earnings increase. We find three broad themes in organization-level implementation of the CLIFF tools: identifying the tar- get population of users; integrating the tool into existing operations; and integrating the tool into coaching sessions.
This course from the European Commission aims to provide participants with a comprehensive understanding of Law as Code and its relationship to digital-ready policymaking.
