A case study explaining how a predictive, data-driven machine-learning model was developed to detect unauthorized cash benefit withdrawals more quickly and accurately in California.
Louisiana issued an RFI to identify solutions that can provide a technology platform for determining eligibility and managing cases across multiple human services programs.
This resource provides state agencies and their implementation partners with context on how and why to conduct a Digital Identity Risk Management (DIRM) process, as well as a new spreadsheet-based tool to guide agency teams through the process.
This research paper examines how stigma shapes participation in U.S. social safety net programs and influences public support for benefit design and access.
This report analyzes the critical role of SNAP’s "broad-based categorical eligibility" (BBCE) policy and the widespread consequences of its potential elimination by the Trump Administration.
An impact report summarizing how a small public-sector innovation team tested, built, and piloted shared digital services to reduce administrative burden in public benefits delivery.
This report details the use of the historic investment of $1 billion in funding from the American Rescue Plan Act (ARPA) to the Department of Labor and state unemployment (UI) agencies to modernize state UI programs.
This report celebrates 50 years of improving maternal and child health in the U.S. through WIC and offers advancements, challenges, and solutions for the future.
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.
Biometric identification technologies—such as facial recognition and fingerprinting—can affect underserved communities, including low-income and minority communities. GAO interviewed academics, advocacy groups, and technology experts to find out how.
This report by EPIC investigates how automated decision-making (ADM) systems are used across Washington, D.C.’s public services and the resulting impacts on equity, privacy, and access to benefits.
This nine-minute video, produced after the completion of the TANF Data Collaborative (TDC) Pilot, features staff members from the California, Colorado, Minnesota, and Virginia TANF agencies reflecting on their challenges, accomplishments, and general experiences during the pilot. In particular, they describe their research questions and discuss building data capacity, integrating datasets, networking with other states, increasing collaboration between state and county agencies, learning new technical skills, and the benefits of being able to draw from diverse skillsets, all within the context of the TDC Pilot.
