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 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.
In June 2022, Legal Aid of Arkansas won a significant victory in their ongoing work to compel Arkansas’ employment agency to disclose crucial details about how it uses automated decision-making systems to detect and adjudicate fraud.
Little is known about how agencies are currently using AI systems, and little attention has been devoted to how agencies acquire such tools or oversee their use.
Directed at government practitioners, this resource addresses common misconceptions about artificial intelligence (AI) and explains the current state of technology.
This article suggests that a lack of clear, shared definitions makes it harder for the public and policymakers to evaluate and regulate technical systems that may have significant impacts on communities and individuals by shaping access to benefits, opportunities, and liberty. It presents and evaluates a definition for automated decision systems, developed through workshops with interdisciplinary scholars and practitioners.
This post argues that for the types of large-scale, organized fraud attacks that many state benefits systems saw during the pandemic, solutions grounded in cybersecurity methods may be far more effective than creating or adopting automated systems.
This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court.
The White House Office of Science and Technology Policy has identified five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence. These principles help provide guidance whenever automated systems can meaningfully impact the public’s rights, opportunities, or access to critical needs.
