Through our research understanding the government digital service field and what workers in this field need, we want to help strengthen those existing roles and establish more pathways for promotion and career support, as well as help other teams recognize the value of these skills and create new roles.
There are frameworks available that could inform the standardization of communicating rules as code for U.S. public benefits programs. The Airtable communicates the differences between the frameworks and tools. Each entry is tagged with different categories that identify the type of framework or tool it is.
In this updated primer, the DBN introduces the concept of digital identity, and provides brief snapshots of digital identity-related developments internationally and in the U.S.
This Urban Institute report highlights how immigrant and mixed-status families continued to avoid safety net programs in 2023 due to lingering fears around the public charge rule.
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.
This handbook provides local governments with practical guidelines, best practices, and ethical considerations for adopting and using AI tools, emphasizing transparency, human oversight, and risk management.
This panel discussion from the Academy's 2025 Policy Summit explores the intersection of artificial intelligence (AI) and public benefits, examining how technological advancements are influencing policy decisions and the delivery of social services.
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
