The AI RMF Playbook offers organizations detailed, voluntary guidance for implementing the NIST AI Risk Management Framework to map, measure, manage, and govern AI risks effectively.
National Institute of Standards and Technology (NIST)
DSN Spotlights are short-form project profiles that feature exciting work happening across our network of digital government practitioners. Spotlights celebrate our members’ stories, lift up actionable takeaways for other practitioners, and put the resources + examples we host in the Digital Government Hub in context.Â
This hub introduces the UK government's Algorithmic Transparency Recording Standard (ATRS), a structured framework for public sector bodies to disclose how they use algorithmic tools in decision-making.
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
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)
This toolkit provides guidance to protect participant confidentiality in human services research and evaluation, including legal frameworks, risk assessment strategies, and best practices.
U.S. Department of Health and Human Services (HHS)
This strategy document establishes a governance framework and roadmap to ensure responsible, trustworthy, and effective AI use across Canadian federal institutions.
The report examines how AI deployment across state and local public administration such as chatbots, voice transcription, content summarization, and eligibility automation are reshaping government work.
This report analyzes the growing use of generative AI, particularly large language models, in enabling and scaling fraudulent activities, exploring the evolving tactics, risks, and potential countermeasures.
