The team aimed to automate applying rules efficiently by creating computable policies, recognizing the need for AI tools to convert legacy policy content into automated business rules using Decision Model Notation (DMN) for effective processing and monitoring.
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.
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to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
Jennifer Pahlka, Deputy CTO in President Obama’s Administration and author, shares her new book, Recoding America on how government must be equipped for digital delivery in order to meet ambitious policy goals. This video was recorded at the Digital Benefits Conference (BenCon) at Georgetown University on June 14, 2023.
Code for America CEO introduces the Safety Net Innovation Lab in a TED Talk, their initiative to work with state governments to reimagine and rebuild delivery of accessible and equitable benefits. This article also includes the video of Renteria’s talk and a transcript.
BenCon 2024 explored state and federal AI governance, highlighting the rapid increase in AI-related legislation and executive orders. Panelists emphasized the importance of experimentation, learning, and collaboration between government levels, teams, agencies, and external partners.
The team introduced an AI assistant for benefits navigators to streamline the process and improve outcomes by quickly assessing client eligibility for benefits programs.
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.
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to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
This session from FormFest 2024 featured the Department of Homeland Security and the United States Digital Service talking about their work to reduce form burdens for internal and external users.
