This report reviews global AI governance tools, highlighting their importance in ensuring trustworthy AI, while identifying gaps and risks in their effectiveness, and offering recommendations to improve their development, oversight, and integration into policy frameworks.
The strategic plan outlines intentions to responsibly leverage artificial intelligence (AI) to enhance health, human services, and public health by promoting innovation, ethical use, and equitable access across various sectors, while managing associated risks.
U.S. Department of Health and Human Services (HHS)
These guidelines provide UK government organizations with best practices for responsibly and effectively procuring artificial intelligence (AI) systems.
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
Executed on March 28, 2024, this memorandum establishes new agency requirements and guidance for AI governance, innovation, and risk management, including through specific minimum risk management practices for uses of AI that impact the rights and safety of the public.
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 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 FormFest profile highlights Riverside County’s pilot of AI-powered interviews that streamline benefit applications, reducing bureaucratic burden on families in crisis while freeing caseworkers to focus on human connection.
This strategy document establishes a governance framework and roadmap to ensure responsible, trustworthy, and effective AI use across Canadian federal institutions.
This research explores how software engineers are able to work with generative machine learning models. The results explore the benefits of generative code models and the challenges software engineers face when working with their outputs. The authors also argue for the need for intelligent user interfaces that help software engineers effectively work with generative code models.
