New research shows that people recognize more of their biases in algorithms' decisions than they do in their own -- even when those decisions are the same. Algorithms were supposed to make our lives ...

Algorithms are a staple of modern life. People rely on algorithmic recommendations to wade through deep catalogs and find the best movies, routes, information, products, people and investments.

In recent years, employers have tried a variety of technological fixes to combat algorithm bias — the tendency of hiring and recruiting algorithms to screen out job applicants by race or gender. They ...

When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm's output matches reality.

To combat algorithmic bias in healthcare, including race and ethnicity is critical, a new study says. Algorithms are used to make healthcare decisions, and can often be more accurate than a clinical ...

The Department of Health and Human Services will research algorithm bias as part of the Biden administration’s efforts to prioritize equitable health outcomes nationally, FedScoop reported April 13.

YouTube has two billion active monthly users and uploads 500 hours of content every minute. Twenty five percent of U.S. adults get their news from YouTube, and 60% of regular users “use the platform ...

Algorithms were supposed to make our lives easier and fairer: help us find the best job applicants, help judges impartially assess the risks of bail and bond decisions, and ensure that health care is ...