The team developed an application to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
The team developed an AI solution to assist benefit navigators with in-the-moment program information, finding that while LLMs are useful for summarizing and interpreting text, they are not ideal for implementing strict formulas like benefit calculations, but can accelerate the eligibility process by leveraging their strengths in general tasks.
The team introduced an AI assistant for benefits navigators to streamline the process and improve outcomes by quickly assessing client eligibility for benefits programs.
At Rules as Code Demo Day Seth Hartig from the National Center for Children in Poverty (NCCP) and Bank Street College demoed the Policy Rules Database (PRD), a collaborative effort between the Federal Reserve Bank of Atlanta and the NCCP. The primary purpose of the PRD is to simplify the interpretation of all programs by creating a common structure and a common terminology. The repository allows for research on public assistance programs and tax policies, and helps users model benefits cliffs on career pathways. The PRD is supported by a technical manual with pseudocode that helps guide integration and usage in other platforms.
We kicked off Rules as Code Demo Day with Alex Soble of 18F and Mike Gintz of 10x presenting their Eligibility APIs Initiative that explores whether APIs and rules as code might improve the efficiency and effectiveness with which federal public benefits programs communicate their policy to states. They demonstrated their original prototype, and how the open source code has now been extended into several initiatives.
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) recently held a convening to share progress and potential in digitizing benefits eligibility and to begin addressing how a national approach could be started.
The Policy2Code Prototyping Challenge explored utilizing generative AI technology to translate U.S. government policies for public benefits into plain language and code, culminating in a Demo Day where twelve teams showcased their projects for feedback and evaluation.
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.
We continued Rules as Code Demo Day with Daniel Singer and Preston Cabe from Benefits Data Trust. Benefits Data Trust provides benefit outreach and application assistance services in seven states. Using Benefits Launch, their in-house interview and rules engine, they support two hundred contact center employees as they screen and apply thousands of clients each year. They also offer a self-service screener, Benefits Launch Express. Additionally, they offer an eligibility API to integrate with other services.
The team examined how AI, specifically LLMs, could streamline the case review process for SNAP applications to alleviate the burden on case workers while potentially improving accuracy.
