This essay explains why the Center on Privacy & Technology has chosen to stop using terms like "artificial intelligence," "AI," and "machine learning," arguing that such language obscures human accountability and overstates the capabilities of these technologies.
his document defines key terms, acronyms, and data elements used in Hawaii's SNAP and WIC data integration project to support cross-program collaboration and data standardization.
This MOA outlines Hawai'i's legal data sharing agreement between the Women, Infants and Children Services Branch of the Department of Health (DOH/WIC), and the Benefit, Employment and Support Services Division of the Department of Human Services (DHS/BESSD) to exchange SNAP and WIC data.
This white paper documents Hawai'i's journey and lessons learned from their 18-month Coordinating SNAP and Nutrition Supports project which laid the foundation for interagency data-sharing and built capacity to analyze administrative data across nutrition programs--specifically SNAP and WIC.
Government agencies at all levels collect administrative data in the course of their day-to-day operations. While such information has been used to determine effectiveness through program evaluations for many years, program administrators view it increasingly as a valuable resource that can also be used to improve program performance. For example, administrative data from employment and public benefits programs such as Temporary Assistance for Needy Families (TANF) can offer insights into families’ unmet needs and ways to improve services.
Temporary Assistance for Needy Families (TANF) leaders, policymakers, and researchers all recognize the need for TANF agencies to use the data they collect to better understand how well their programs are working and how to improve them, given the impact on the families they serve. It is often difficult, however, for agencies already stretched to capacity to prioritize and execute data use and analytics. State TANF leaders are seeking roadmaps for how to transform their organizations and become data-driven.
