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)
Automated decision systems (ADS) are increasingly used in government decision-making but lack clear definitions, oversight, and accountability mechanisms.
Little is known about how agencies are currently using AI systems, and little attention has been devoted to how agencies acquire such tools or oversee their use.
This resource provides examples and practical guides that explain how to use existing regulations and data sharing agreements to transfer client information or eligibility status between benefit programs.
This foundational article develops the concept of administrative burden, defining it as the learning, psychological, and compliance costs individuals face when interacting with government, and argues that these burdens are often shaped by political choices.
Journal of Public Administration Research and Theory
This case study explores how the City of Akron developed a community tree map to engage residents in urban forestry efforts, enabling them to identify, grow, and care for trees in their neighborhoods.
