Fraud and Improper Payments: Data Quality and a Skilled Workforce Are Essential for Realizing Artificial Intelligence’s Benefits

BIAS: Center
RELIABILITY: Very High

Political Bias Rating

This rating indicates the source’s editorial stance on the political spectrum, based on analysis from Media Bias/Fact Check, AllSides, and Ad Fontes Media.

Far Left / Left: Progressive editorial perspective
Lean Left: Slightly progressive tendency
Center: Balanced, minimal editorial slant
Lean Right: Slightly conservative tendency
Right / Far Right: Conservative editorial perspective

Current source: Center. Stories with cross-spectrum coverage receive elevated prominence.

Reliability Rating

This rating measures the source’s factual accuracy, sourcing quality, and journalistic standards based on third-party fact-checking assessments.

Very High: Exceptional accuracy, rigorous sourcing
High: Strong factual reporting, minor issues rare
Mixed: Generally accurate but occasional concerns
Low: Frequent errors or misleading content
Very Low: Unreliable, significant factual issues

Current source: Very High. Higher reliability sources receive elevated weighting in story prioritization.

GAO
15:38Z

What GAO Found The federal government has tools and resources to help agencies combat fraud and improper payments. GAO has recommended improvements to the use of these tools and resources. For example, Congress should consider making permanent the Social Security Administration’s requirement to share its full death data with the Do Not Pay system to help prevent fraud and improper payments.

Further, GAO has identified leading practices for managing fraud risks at federal agencies and has made recommendations to agencies to implement these practices. For example, in 2024, GAO recommended that the Department of Defense revise its Fraud Risk Management Strategy to include data analytics as a method to address fraud. Further, by implementing GAO’s recommendation, the Small Business Administrat

Continue reading at the original source

Read Full Article at GAO →