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 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 conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
The study investigates how state agencies administering SNAP comply with Title VI of the Civil Rights Act by providing language access for individuals with limited English proficiency (LEP).
This article explores how AI and Rules as Code are turning law into automated systems, including how governance focused on transparency, explainability, and risk management can ensure these digital legal frameworks stay reliable and fair.
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.
Government leaders discuss how to ensure seamless access to public benefits through breaking down silos, user-friendly digital identities, and privacy-focused security measures.
NYC's My File NYC and New Jersey's unemployment insurance system improvements demonstrate how successful digital innovations can be scaled across various programs, leveraging trust-building, open-source technology, and strategic partnerships.
This research study analyzes the structural and budgetary layout of eleven US-based Digital Service Teams (DSTs) at the municipal, county, and state levels. In doing so, it sets out to answer the research question: “How are digital service teams structured and funded?”
Presentation covering the findings of a research study analyzing the structural and budgetary layout of of eleven US-based Digital Service Teams (DSTs) at the municipal, county, and state levels.
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.
Michigan's UIA director, Julia Dale, is leading the agency through transition by prioritizing lived experience, hope, grit, and values. Virginia's SNAP Program Manager, Michele Thomas, highlighted the success of Sun Bucks, a summer EBT child nutrition program that fed over 700,000 kids in its first year.
