This report contributes to the quantitative measurement of psychological burdens by examining a case study of a single social program: the Supplemental Nutrition Assistance Program, by considering new quantitative measures of the psychological burdens faced by SNAP applicants.
This research brief summarizes the ideas and recommendations from sessions with dozens of cross-sector stakeholders within the technology ecosystem to identify conditions for better, healthier, more secure digital ecosystems that could help guide the next generation of open protocols and platforms.
This article analyses ‘digital distortions’ in Rules as Code, which refer to disconnects between regulation and code that arise from interpretive choices in the encoding process.
This guide is intended to provide everything else, with a focus on the basics of UI technology projects, guidance on standards for equitable uses of technology, and strategies for how to have a positive impact on these projects.
This plan promotes responsible AI use in public benefits administration by state, local, tribal, and territorial governments, aiming to enhance program effectiveness and efficiency while meeting recipient needs.
U.S. Department of Health and Human Services (HHS)
This framework outlines USDA’s principles and approach to support States, localities, Tribes, and territories in responsibly using AI in the implementation and administration of USDA’s nutrition benefits and services. This framework is in response to Section 7.2(b)(ii) of Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.
