This session from FormFest 2024 features the South Carolina Early Childhood Advisory Council’s work developing a single portal to integrate applications for publicly funded programs and services, and the office of Federal Student Aid’s work on the FAFSA form.
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to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
Sarah Bargal provides an overview of AI, machine learning, and deep learning, illustrating their potential for both positive and negative applications, including authentication, adversarial attacks, deepfakes, generative models, personalization, and ethical concerns.
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 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.
The team introduced an AI assistant for benefits navigators to streamline the process and improve outcomes by quickly assessing client eligibility for benefits programs.
This presentation explores the balance between security and user experience in digital benefit account creation and authentication, highlighting insights from a forthcoming playbook focused on SNAP and Medicaid portals.
