Library
Discover the latest innovations, learn about promising practices, and find out what’s coming next with best-in-class resources from trusted sources.
Is there something missing from our library?
Search for the topic or resource you're looking for, or use the filters to narrow down results below.
-
Digitizing Policy + Rules as Code Policy2Code Demo Day at BenCon 2024
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.
-
Digitizing Policy + Rules as Code Code The Dream at Policy2Code Demo Day at BenCon 2024
The team introduced an AI assistant for benefits navigators to streamline the process and improve outcomes by quickly assessing client eligibility for benefits programs.
-
Digitizing Policy + Rules as Code MITRE at Policy2Code Demo Day at BenCon 2024
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.
-
Digitizing Policy + Rules as Code Policy Pulse at Policy2Code Demo Day at BenCon 2024
The team introduced "Policy Pulse," a tool to help policy analysts understand laws and regulations better by comparing current policies with their original goals to identify implementation issues.
-
Digitizing Policy + Rules as Code Hoyas Lex Ad Codex at Policy2Code Demo Day at BenCon 2024
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.
-
Digitizing Policy + Rules as Code Tech2i Tralblazers at Policy2Code Demo Day at BenCon 2024
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to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
-
Digitizing Policy + Rules as Code Team ImPROMPTu at Policy2Code Demo Day at BenCon 2024
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to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
-
Digitizing Policy + Rules as Code POMs and Circumstance at Policy2Code Demo Day at BenCon 2024
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.
-
Digitizing Policy + Rules as Code The RAGTag SNAPpers at Policy2Code Demo Day at BenCon 2024
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.
-
Digitizing Policy + Rules as Code mRelief at Policy2Code Demo Day at BenCon 2024
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
-
Digitizing Policy + Rules as Code Nava Labradors at Policy2Code Demo Day at BenCon 2024
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.
-
Digitizing Policy + Rules as Code PolicyEngine at Policy2Code Demo Day at BenCon 2024
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.