Concerns over risks from generative artificial intelligence systems have increased significantly over the past year, driven in large part by the advent of increasingly capable large language models. But, how do AI developers attempt to control the outputs of these models? This primer outlines four commonly used techniques and explains why this objective is so challenging.
Center for Security and Emerging Technology (CSET)
This publication seeks to answer one of the most common questions that CIOs ask: “What are other states doing with generative AI and what is the role of the state CIO?”
National Association of State Chief Information Officers (NASCIO)
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.
This executive order establishes governance, values, and oversight structures for the ethical and responsible use of generative AI technologies within the Commonwealth of Pennsylvania.
A publicly-available suite of policy templates and knowledge-sharing tools offered by the GovAI Coalition (via the City of San José) to help public agencies launch or refine responsible AI governance programs.
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 virtual event showcasing how one city applied technology, including artificial intelligence, to streamline municipal code administration and reduce bureaucratic friction.
A collection that provides a comprehensive operational toolkit to help civil servants and public sector organizations deploy artificial intelligence safely, effectively, and securely.
This comprehensive research report evaluates the structural progress, disparities, and operational barriers surrounding artificial intelligence adoption within the United States federal government.
