What exactly are the differences between generative AI, large language models, and foundation models? This post aims to clarify what each of these three terms mean, how they overlap, and how they differ.
Center for Security and Emerging Technology (CSET)
This paper describes the policy choices, business practices, and technology innovations that the State of New Jersey is employing to ensure that the right people get benefits — accurately and on time.
On May 19, 2023, the Digital Benefits Network published a new, open dataset documenting authentication and identity proofing requirements across online SNAP, WIC, TANF, Medicaid, child care (CCAP)applications, and unemployment insurance applications. This page includes data and observations about authentication and identity proofing steps specifically for online unemployment insurance applications.
Created for use in the Digital Doorways research project, this design stimuli shows the steps of submitting an application, sharing personal information, and verifying identity for New York's integrated online application that includes SNAP and Medicaid.
This interview template includes questions designed to help teams conduct exploratory, semi-structured interviews with government stakeholders involved in program delivery to gather information that can help them evaluate the status quo of digital delivery in their organization.
This paper describes results from fieldwork conducted at a social services site where the workers evaluate citizens' applications for food and medical assistance submitted via an e-government system. These results suggest value tensions that result - not from different stakeholders with different values - but from differences among how stakeholders enact the same shared value in practice.
CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The Increasing Stimulus Payment Take-up in California report by the California Policy Lab examines barriers to accessing federal stimulus payments and provides strategies to increase take-up among eligible Californians, particularly low-income and non-filers.
This paper introduces a method for auditing benefits eligibility screening tools in four steps: 1) generate test households, 2) automatically populate screening questions with household information and retrieve determinations, 3) translate eligibility guidelines into computer code to generate ground truth determinations, and 4) identify conflicting determinations to detect errors.
This guide consolidates learning and spotlights principles, insights, and emerging practices to guide municipal leaders and public-private partnerships interested in designing basic income programs that are ethical, equitable, rigorous, informative, and consequential for local, state and national policymaking.
