This factsheet outlines the Administration for Children and Families’ (ACF) 2024 initiatives to promote health equity across its programs by embedding equity into funding, service delivery, and community engagement.
U.S. Department of Health and Human Services (HHS)
This impact report showcases the office's initiatives and achievements in enhancing state government services through innovative, user-centered approaches.
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)
Outlines recommendations from the U.S. House of Representatives for the responsible adoption, governance, and oversight of artificial intelligence technologies across state agencies.
Bipartisan House Task Force on Artificial Intelligence
This report analyzes the current state of digital identity in the United States, outlines challenges such as privacy concerns, fragmented systems, and lack of standards, and proposes policy and technology solutions to build a secure, interoperable, and user-friendly national digital identity framework.
Information Technology & Innovation Foundation (ITIF)
This brief explores the relationship between economic hardship and child welfare involvement, examining how direct cash transfers (DCTs) can reduce child maltreatment and strengthen family stability.
An overview of direct cash programs and innovations in the U.S., exploring how unconditional cash transfers promote economic stability, mobility, and well-being.
This report provides an overview of the task force’s work in assessing, guiding, and recommending policies for the safe, ethical, and effective use of generative AI across Alabama’s executive-branch agencies.
State of Alabama Generative Artificial Intelligence (GenAI) Task Force
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
Through deeply reported case studies and insights from focus groups, this report provides an in-depth look at the impact of pandemic-era government spending on families.
The second event in the Digital Service Network’s summer event series, Let’s Get Digital, focused on the City of Boston’s transformative journey to streamline its procurement processes.
