A case study of the Hawai‘i Career Acceleration Navigator — an accessible, data-driven and full-service government platform for unemployed people and other jobseekers to search for jobs and access supportive service benefits.
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to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
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 article discusses key takeaways from BenCon 2023, highlighting the importance of creating equitable and ethical public benefits technology. It emphasizes the need for tech solutions that address systemic inequalities, ensure accessibility, and promote inclusivity for underserved communities in accessing public services.
The exclusion of agricultural and domestic workers—predominantly African Americans—from the 1935 Social Security Act's unemployment insurance program is analyzed as a result of international policy diffusion rather than solely domestic racial politics.
This presentation shares user experience research on the challenges, priorities, and opportunities for improving the journey of Bay Area residents seeking affordable housing.
