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.
For the past year, modernization teams at the Department of Labor (DOL) have been helping states identify opportunities to automate rote, non-discretionary, manual tasks, with the goal of helping them speed up the time that it takes to process claims. This post provides more context on Robotic Process Automation (RPA) and potential use cases in unemployment insurance.
This report summarizes progress made with agencies and members of the public to identify and reduce burdens that individuals, families, and small businesses face every day when interacting with government programs.
This report explores the Maine Department of Labor’s (MDOL) remarkable response to this layoff through collaboration with the Peer Workforce Navigator project—a coalition of community-based organizations in partnership with the MDOL—which made a huge difference in the lives of these laid off workers. The report also examines aspects of the state’s unemployment insurance (UI) system that might be improved to account for similar situations in the future.
This quarterly research update aims to highlight key learnings related to improving unemployment insurance (UI) systems in the areas of equity, timeliness, and fraud, and monitor for model UI legislation and policy related specifically to technology. Subscribe to receive future editions.
This proposal recommends a set of new federal performance standards that would measure and improve UI access. The proposal is intended to supplement existing federal UI standards, but all UI standards and metrics should be periodically reevaluated and updated as the conditions facing unemployed workers and benefit delivery change.
This kit contains a collection of styles, components, and building blocks to quickly create action-forward emails for Unemployment Insurance programs within the U.S.
This GitHub repository includes resources that users of the UI wage data toolkit may find helpful. It covers a variety of topics, including equity, data security, programming, and data QC tips. It also serves as a place for our team to continue to post information that the TANF Data Collaborative (TDC) pilot sites found useful during our partnerships with them.
