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.
This resource appendix is a compilation of useful resources intended as a follow-on to the DSN’s writing on theories of change for digital transformation in government. Practitioners can use these resources to DIY their ToC after reading our essays.
As they transition to providing more services online, there are ways governments can get creative working around talent shortages and entrenched bureaucracies.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
This guide discusses general characteristics shared by organizations that have successfully created accessible content, and includes case studies that showcase characteristics of successful accessible content teams.
The team introduced an AI assistant for benefits navigators to streamline the process and improve outcomes by quickly assessing client eligibility for benefits programs.
The team explored the performance of various AI chatbots and LLMs in supporting the adoption of Rules as Code for SNAP and Medicaid policies using policy data from Georgia and Oklahoma.
The Digital Service Network (DSN) spoke with three staff members from the New York State Executive Chamber—Gabe Paley, Tonya Webster, and, Luke Charde to learn more about the state's efforts to improve residents’ experiences accessing government programs.
In December 2024, the Digital Benefits Network released an updated open dataset on authentication and identity proofing requirements across various public benefits applications to highlight best practices and areas for improvement in identity management.
This mainstage session from FormFest 2024 featured behind-the-scenes stories about the IRS’ work to turn tax forms from static PDFs into a user friendly digital experience.
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.
