Guidance from Washington Technology Solutions (WaTech) outlining the state’s framework for responsibly procuring, deploying, and monitoring generative AI technologies across government agencies.
Prepared by the Washington State Office of Financial Management’s State Human Resources Division under Executive Order No. 24-01, this report examines the potential effects of GenAI on state employees across sectors including education, IT, and law enforcement.
Washington State Office of Financial Management (OFM)
A practical, plain-language guide offering public-sector procurement and technology teams actionable tools and best practices for procuring AI responsibly and effectively.
This course is designed to help public professionals accelerate the process of finding and implementing urgently-needed evidence-based solutions to public problems.
This policy supports the appropriate development, deployment, and use of generative artificial intelligence (GenAI) systems, products, services, tools, and content within consolidated state agencies in Colorado.
Colorado Governor's Office of Information Technology (OIT)
This session from FormFest 2024 walked attendees through some of the major changes AI is bringing to form design. Learn about the National Head Start Association’s use of AI to reduce administrative burden and the Canadian Digital Service’s tips for protecting government applications systems from AI.
Learn how to use generative AI to quickly create unemployment insurance translations that are accurate, easy to understand, and tailored to your state.
A virtual event showcasing how one city applied technology, including artificial intelligence, to streamline municipal code administration and reduce bureaucratic friction.
A case study describing how a 90-day generative AI (GenAI) pilot using Google’s Gemini tool was conducted across state agencies to assess productivity, creativity, and responsible use in government work.
Colorado Governor's Office of Information Technology (OIT)
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.
