This report offers a detailed assessment of how AI and emerging technologies could impact the Social Security Administration’s disability benefits determinations, recommending guardrails and principles to protect applicant rights, mitigate bias, and promote fairness.
The team explored using LLMs to interpret the Program Operations Manual System (POMS) into plain language logic models and flowcharts as educational resources for SSI and SSDI eligibility, benchmarking LLMs in RAG methods for reliability in answering queries and providing useful instructions to users.
A guide to navigating New York City’s public services. It was made with and for families of students living in temporary housing or experiencing homelessness and the NYC Department of Education’s Office of Students in Temporary Housing (STH).
The NYC Benefits Screening API provides machine-readable calculations and criteria for benefits screening that power the ACCESS NYC screening questionnaire.
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.
This resource provides guidance on streamlining enrollment across public benefit programs to improve efficiency, reduce administrative burdens, and enhance access for eligible individuals and families.
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.
The Advancing Economic Mobility for Low-Income Families report, published by the National Governors Association (NGA) Center for Best Practices, provides policy options for governors to strengthen economic security, workforce participation, and wealth-building opportunities for low-income families.
