Intended Audience: Federal/National Government: Legislative Branch
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“I Used to Get WIC . . . But Then I Stopped”: How WIC Participants Perceive the Value and Burdens of Maintaining Benefits
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).
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Policy A Safety Net with 100 Percent Participation: How Much Would Benefits Increase and Poverty Decline?
Research examining how much poverty would decrease—overall, by age, and by race and ethnicity—and how much benefits would increase if all people eligible for safety net programs received the full benefits they qualify for in each of the 50 states and DC.
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Automation + AI Access Denied: Faulty Automated Background Checks Freeze Out Renters
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
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Automation + AI Algorithmic Accountability for the Public Sector
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.
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Automation + AI Artificial Intelligence: Background, Selected Issues, and Policy Considerations
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.
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Automation + AI Algorithmic Accountability: A Primer
The primer–originally prepared for the Progressive Congressional Caucus’ Tech Algorithm Briefing–explores the trade-offs and debates about algorithms and accountability across several key ethical dimensions, including fairness and bias; opacity and transparency; and lack of standards for auditing.
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Automation + AI Introduction to the AI Guide for Government
A guide from the General Service Administration to help government decision makers clearly see what AI means for their agencies and how to invest and build AI capabilities.
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Human-Centered Design Administrative Burden Scale
The Better Government Lab at the McCourt School of Public Policy at Georgetown University has developed a new scale for measuring the experience of burden when accessing public benefits. They offer both a three-item scale and a single-item scale, which can be utilized for any public benefit program. The shorter scales provide a less burdensome way to measure by requiring less information from users.
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Management Hiring Question Bank for Digital Service Teams
A toolkit with interview questions for digital service teams hiring digital talent to leverage.
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Human-Centered Design Preparing for Human-Centered Redesign
The Beeck Center for Social Impact + Innovation at Georgetown University and the nonprofit design studio Civilla teamed up to co-author a set of guides to prepare for human-centered redesign
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Engineering + Software Development Low-Code/No-Code Tools: Implementation and Insights from the Field
An overview on how U.S. Digital Response has used low-code/no-code tools internally as well as with our government partners
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User Research Digital.gov Research Resources
Resources from Digital.gov on research