This article describes the General Services Administration’s efforts to get a limited number of state and local governments to try login.gov with their federally funded programs.
This academic paper examines predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals. Through this examination, the authors explore how predictive optimization can raise concerns that make its use illegitimate and challenge claims about predictive optimization's accuracy, efficiency, and fairness.
The Electronic Privacy Information Center (EPIC) emphasizes the necessity of adopting broad regulatory definitions for automated decision-making systems (ADS) to ensure comprehensive oversight and protection against potential harms.
Building modular, open-source, human-centered software is necessary to create equitable government services fit for the digital age. Nava emphasizes addressing large scale digital service challenges by building and releasing small, modular software components that are loosely-coupled by well-defined APIs. This enables agencies to quickly and conistently deliver services that help people immediately, whilst also building a flexible foundation for long-term technical evolution.
The New Mexico Human Services Department and Department of Health, as part of the Coordinating SNAP & Nutrition Supports program, leveraged data sharing to align SNAP, Medicaid, TANF, and WIC.
American Public Human Services Association (APHSA)
