A public summary of findings from an AI trust study showing how Canadians perceive and trust different AI designs on the official government website, particularly preferring custom, transparent AI experiences over general third-party AI tools.
This report documents the key lessons learned from the UK Universal Credit Programme between 2010 and 2025, reflecting on the program’s management, implementation, and development over its lifecycle.
A TLDR of the State CDO Archetypes report—covering how state CDO offices operate and the six archetypes that define them. Written for event attendees and government staff: governor's office, IT and budget leadership, legal and data officials, and legislators who oversee CDO funding and establishment.
This workshop summary synthesizes key takeaways from a convening of nearly 40 research and data analytics staff from 15 states focused on SNAP Quality Control (QC) data modeling.
This analysis explores the potential reduction in poverty rates across all U.S. states if every eligible individual received full benefits from seven key safety net programs, highlighting significant decreases in overall and child poverty.
This report outlines a dozen fintech and civic tech organizations working across fourteen safety net programs to show what’s possible when modern technology is married to a consumer insights perspective.
This issue brief describes the Pennsylvania case study, outlines the historical context, and offers strategies and recommendations for successfully implementing Fast Track.
This report examines how the U.S. federal government can enhance the efficiency and equity of benefit delivery by simplifying eligibility rules and using a Rules as Code approach for digital systems.
Through our research understanding the government digital service field and what workers in this field need, we want to help strengthen those existing roles and establish more pathways for promotion and career support, as well as help other teams recognize the value of these skills and create new roles.
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.
This report recommends updating the methodology used by the Census Bureau to calculate the Supplemental Poverty Measure (SPM) to reflect household basic needs and replace the current Official Poverty Measure as the primary statistical measure of poverty. The report assesses the strengths and weaknesses of the SPM and provides recommendations for updating its methodology and expanding its use in recognition of the needs of most American families such as medical care, childcare, and housing costs.
National Academies of Sciences, Engineering, and Medicine
