This video demonstrates how to use Iowa's Child Care Connect (C3), a centralized data system that integrates near-real-time child care data to support families, providers, policymakers, and economic development efforts across the state.
An overview video describing the Digital Identity Risk Management process outlined in NIST's Digital Identity Guidelines, which organizations can use to develop a risk-based approach to identity management.
These principles and best practices for AI developers and employers to center the well-being of workers in the development and deployment of AI in the workplace and to value workers as the essential resources they are.
This article explores how AI and Rules as Code are turning law into automated systems, including how governance focused on transparency, explainability, and risk management can ensure these digital legal frameworks stay reliable and fair.
This presentation explores the balance between security and user experience in digital benefit account creation and authentication, highlighting insights from a forthcoming playbook focused on SNAP and Medicaid portals.
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 blog discusses a resource developed by the Digital Service at the Centers for Medicare & Medicaid Services (CMS) to assist individuals in navigating mental health, drug, or alcohol issues and connecting with appropriate support services. ​
U.S. Department of Health and Human Services (HHS)
This framework provides practical guidance, detailed reference designs, and example solutions to help organizations securely adopt and operationalize Zero Trust principles across diverse IT environments.
National Institute of Standards and Technology (NIST)
This profile provides a cross-sectoral profile of the AI Risk Management Framework specifically for Generative AI (GAI), outlining risks unique to or exacerbated by GAI and offering detailed guidance for organizations to govern, map, measure, and manage those risks responsibly.
National Institute of Standards and Technology (NIST)
