This academic article develops a framework for evaluating whether and how automated decision-making welfare systems introduce new harms and burdens for claimants, focusing on an example case from Germany.
This report presents evidence on the use of algorithmic accountability policies in different contexts from the perspective of those implementing these tools, and explores the limits of legal and policy mechanisms in ensuring safe and accountable algorithmic systems.
On December 5, 2022, an expert panel, including representatives from the White House, unpacked what’s included in the AI Bill of Rights, and explored how to operationalize such guidance among consumers, developers, and other users designing and implementing automated decisions.
This report explores technologies that have the potential to significantly affect employment and job quality in the public sector, the factors that drive choices about which technologies are adopted and how they are implemented, how technology will change the experience of public sector work, and what kinds of interventions can protect against potential downsides of technology use in the public sector. The report categories technologies into five overlapping categories including manual task automation, process automation, automated decision-making systems, integrated data systems, and electronic monitoring.
In early 2023, Wired magazine ran four pieces exploring the use of algorithms to identify fraud in public benefits and potential harms, deeply exploring cases from Europe.
In this interview, Code for America staff members share how client success, data science, and qualitative research teams work together to consider the responsible deployment of artificial intelligence (AI) in responding to clients who seek assistance with three products.
This benefits protection toolkit is a step-by-step guide to develop and integrate a benefits protection strategy into your Direct Cash Transfer (DCT) program design. This toolkit includes a set of customizable templates, letters, and other tools which should be downloaded and modified for your pilot and local context.
This report aims to help congressional leaders understand AI, and provide key terms and definitions that would be important in crafting or understanding potential legislation on the topic.
In collaboration with the private and public sectors, NIST has developed a framework to better manage risks to individuals, organizations, and society associated with artificial intelligence (AI). The framework is intended for voluntary use and to improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.
