This study examines how individuals assess administrative burdens and how these views change over time within the context of the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC).
Algorithmic impact assessments (AIAs) are an emergent form of accountability for organizations that build and deploy automated decision-support systems. This academic paper explores how to co-construct impacts that closely reflects harms, and emphasizes the need for input of various types of expertise and affected communities.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
Automated decision systems (ADS) are increasingly used in government decision-making but lack clear definitions, oversight, and accountability mechanisms.
This page includes data and observations about authentication and identity proofing steps specifically for online applications that include MAGI Medicaid.
NYC Opportunity collaborated with the Administration for Child Services (ACS) to design a family-centered process for prevention services, addressing confusion and lack of choice in the current system. By creating tools like the Provider Profile and Family Voice booklet, the team empowered families to choose providers based on their needs while ensuring their feedback reaches ACS. The project aims to improve family experiences and communication with ACS, with plans to expand through testing and future innovations like a web portal.
This report explores the role that academic and corporate Research Ethics Committees play in evaluating AI and data science research for ethical issues, and also investigates the kinds of common challenges these bodies face.
This resource describes how different agencies have updated their systems to increase online and mobile access to benefits information and applications, including using text messages to share benefits information with residents.
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.
Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. This academic study presents an approach to evaluate bias present in automated facial analysis algorithms and datasets.
This article discusses the challenges of today’s centralized identity management and investigates current developments regarding verifiable credentials and digital wallets.
This article analyzes the strategic use of public policy as a tool for reshaping public opinion. Though progressive revisionists in the 1990s argued that reforming welfare could produce a public more willing to invest in anti-poverty efforts, welfare reform in the 1990s did little to shift public opinion. This study investigates the general conditions under which mass feedback effects should be viewed as more or less likely.
Digitizing public benefits policy will make the biggest impact for administrators and Americans, but only if it happens at the highest level of government.
