This paper outlines the need for comprehensive reforms to improve the U.S. government's capacity to effectively implement policies, focusing on reducing bureaucratic inefficiencies, enhancing workforce structures, and leveraging digital infrastructure.
This brief examines the treatment of PFML for purposes of state and federal taxation, as well as determining income and eligibility in five means-tested programs.
This brief synthesizes the manner in which the political and social service environments affect the intergenerational stability of non-citizen families, offering insights into programmatic supports.
American Public Human Services Association (APHSA)
This panel discussion from the Academy's 2025 Policy Summit explores the intersection of artificial intelligence (AI) and public benefits, examining how technological advancements are influencing policy decisions and the delivery of social services.
This memo provides information to child and family service agencies on improving support for intersex children, adolescents, and their families through affirming practices, resources, and partnerships.
U.S. Department of Health and Human Services (HHS)
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 guide outlines ethical frameworks and best practices for responsibly collecting and using demographic and other sensitive data to build equitable digital products.
This publication explains the fundamentals of state IEE systems—including the technology, opportunities, risks, and stakeholders involved. It is a resource for state officials, advocates, funders, and tech partners working to implement these systems.
A critical landscape report examining how the AI industry concentrates corporate power, reshapes public institutions, and advances economic and political interests that undermine democracy, labor, and shared prosperity.
A central hub of guidance, standards, and supporting documentation explaining how UK public sector bodies should record and publish information about algorithmic systems to ensure transparency and accountability.
