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 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.
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 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 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.
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.
At Rules as Code Demo Day Executive Director Zareena Mayn and Chief Technology Officer Dize Hacioglu of mRelief demoed the code for their Supplemental Nutrition Assistance Program (SNAP) eligibility screener. mRelief is a women-led team that provides a web-based and text message-based SNAP eligibility screener to all 53 states and territories that participate in SNAP. They demonstrated how they have modularized their code to host federal program rules and state-specific rules.
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 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.
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.
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.
