This report outlines the team's achievements in enhancing state digital services through human-centered design, agile development, and cross-agency collaboration from its inception through 2024.
Colorado Governor's Office of Information Technology (OIT)
This framework provides voluntary guidance to help employers use AI hiring technology in ways that are inclusive of people with disabilities, while aligning with federal risk management standards.
This action plan outlines Oregon’s strategic approach to adopting AI in state government, emphasizing ethical use, privacy, transparency, and workforce readiness.
This user guide provides step-by-step instructions for families in Iowa to find licensed child care providers online based on location, schedule, and program preferences.
This one-pager introduces Iowa’s Child Care Data Dashboards, which provide near real-time insights into child care supply, demand, and vacancies to support data-informed planning across the state.
This report analyzes how proposed state cost-sharing requirements for SNAP would impact benefit access and poverty during a recession, projecting significant risks to low-income households if states are unable to maintain SNAP funding.
This guide introduces privacy-enhancing technologies (PETs) and provides practical guidance for government agencies on selecting and implementing them to securely use, share, and protect sensitive data.
An updated guide for public sector and civic data users to embed racial equity and community voice throughout the data life cycle—from planning to dissemination.
The Digital Benefits Network's second Digital Identity Community of Practice quarterly call centered exploring client support models in digital identity and an update on the Balance ID project.
This case study details the development of a document extraction prototype to streamline benefits application processing through automated data capture and classification.
The AI RMF Playbook offers organizations detailed, voluntary guidance for implementing the NIST AI Risk Management Framework to map, measure, manage, and govern AI risks effectively.
National Institute of Standards and Technology (NIST)
