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.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
Building on our February 2022 report Benefit Eligibility Rules as Code: Reducing the Gap Between Policy and Service Delivery for the Safety Net, the Beeck Center’s Digital Benefits Network (DBN) hosted Rules as Code Demo Day on June 28, 2022 where there were eight demonstrations of projects and code followed by a collaborative problem solving session on how to continue advancing rules as code for the U.S. social safety net.
The OECD report explores the concept of "Rules as Code" (RaC), proposing a transformation in government rulemaking by developing machine-consumable regulations alongside human-readable versions.
Organisation for Economic Co-operation and Development (OECD)
Github repository for Policy Rules Database, which encodes up-to-date rules and provisions for all major federal and state public assistance programs, taxes, and tax credits.
In this presentation, Pia Andrews explores how open source legislation as code can be a public utility to increase transparency, and enable better implementation and testing of government systems.
18F, a consultancy within the U.S. General Services Administration, developed a prototype API and pre-screener to model federal SNAP eligibility rules, aiming to simplify benefits access through open-source technology.
Alluma is a nonprofit that provides digital solutions to simplify eligibility screening and enrollment for social benefit programs, supporting cross-benefit access in 45 counties and two states. Their One-x-Connection product suite streamlines Medicaid and SNAP applications using a business rules engine, with a focus on human-centered design and anonymous, simplified eligibility checks, having helped screen over 10 million individuals and submitted over 67 million applications.
The team developed an AI-powered explanation feature that effectively translates complex, multi-program policy calculations into clear and accessible explanations, enabling users to explore "what-if" scenarios and understand key factors influencing benefit amounts and eligibility thresholds.
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.
