This framework provides a structured approach for ensuring responsible and transparent use of AI systems across government, emphasizing governance, data integrity, performance evaluation, and continuous monitoring.
When people hit the moment in the HealthCare.gov sign-up process where they need in-person help, they’re likely frustrated and at risk of abandoning the process altogether. To help, Ad Hoc designers on the Centers for Medicare & Medicaid Services (CMS) Find Local Help team extensively researched user pain points and used human-centered design to create a tool that respects the stress users may experience and delivers the information they need as quickly and simply as possible.
This session from FormFest 2024 focused on improving service delivery by hearing about work in multiple cities to rapidly digitize service delivery and work by the Department of Veteran Affairs around implementing service design principles in form revisions.
This session from FormFest 2024 focused on how to help people get the assistance they need from the U.S. Department of Health and Human Services’ work on the Low Income Home Energy Assistance Program (LIHEAP) and the Maryland Social Services Administration’s work to improve welfare support for kinship caregivers.
This annotated bibliography compiles key resources on data linkage and integration for research and statistical purposes, focusing on best practices, governance, and technical considerations.
This memo provides guidance on conducting usability testing under the Paperwork Reduction Act (PRA), clarifying when PRA approval is required, and offering strategies for quickly implementing improvements based on usability feedback for federal forms and websites.
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 case study details the development of a document extraction prototype to streamline benefits application processing through automated data capture and classification.
This strategy document establishes a governance framework and roadmap to ensure responsible, trustworthy, and effective AI use across Canadian federal institutions.
