This news release highlights Pennsylvania’s first-in-the-nation Generative AI pilot under Governor Shapiro, showcasing its positive impact on state employees and commitment to responsible, ethical AI use.
A growing observatory of examples of how open data from official sources and generative artificial intelligence (AI) are intersecting across domains and geographies.
A training course on using artificial intelligence (AI) tools to de-jargonize government language, with a tutorial on turning a complex piece of government writing into simpler and easier-to-understand language for government employees and residents alike.
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 report examines how governments can effectively build, attract, and retain AI talent to responsibly integrate artificial intelligence into public service delivery.
Best practices for procuring and developing accessible tools that utilize artificial intelligence (AI) and how to ensure that they are in compliance with the Web Content Accessibility Guidelines (WCAG) 2.1 Level A and Level AA.
The Commonwealth of Massachusetts Executive Office of Technology Services and Security (EOTSS)
Sarah Bargal provides an overview of AI, machine learning, and deep learning, illustrating their potential for both positive and negative applications, including authentication, adversarial attacks, deepfakes, generative models, personalization, and ethical concerns.
Public procurement in state governments can be slow and inefficient, but artificial intelligence (AI) offers a solution by automating tasks, improving decision-making, and addressing workforce gaps, as highlighted in a joint brief by NASCIO and NASPO.
National Association of State Chief Information Officers (NASCIO)
This article explores how legal documents can be treated like software programs, using methods like software testing and mutation analysis to enhance AI-driven statutory analysis, aiding legal decision-making and error detection.
