This report documents best practices and lessons learned from project streamlined data sharing between SNAP and WIC, enhancing cross-enrollment processes
American Public Human Services Association (APHSA)
This report on the use of Generative AI in State government presents an initial analysis of the potential benefits to individuals, communities, government and State government workers, while also exploring potential risks.
This report summarizes 19 SNAP policy options (in effect as of Oct. 1, 2023) and waivers (implemented as of July 1, 2023) chosen by SNAP state agencies (50 states, the District of Columbia, Guam, and Virgin Islands) in federal fiscal year (FY) 2023.
This report provides specific actions the federal government could take to reduce identity fraud and establish a whole-of-government victim redress approach.
This study evaluates the use of RPA technology by three states to automate SNAP administration, focusing on repetitive tasks previously performed manually.
This paper describes the policy choices, business practices, and technology innovations that the State of New Jersey is employing to ensure that the right people get benefits — accurately and on time.
This report details findings and lessons from a project to develop a calculator to help people anticipate how a change in earnings from employment would affect their net income and information on their estimated effective marginal tax rate.
U.S. Department of Health and Human Services (HHS)
In May 2020, Stanford's HAI hosted a workshop to discuss the performance of facial recognition technologies that included leading computer scientists, legal scholars, and representatives from industry, government, and civil society. The white paper this workshop produced seeks to answer key questions in improving understandings of this rapidly changing space.
This report explores how despite unresolved concerns, an audit-centered algorithmic accountability approach is being rapidly mainstreamed into voluntary frameworks and regulations.
This guidebook offers an introduction to the risks of discrimination when using automated decision-making systems. This report also includes helpful definitions related to automation.
