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.

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.

(The Conversation is an independent and nonprofit source of news, analysis and commentary from academic experts.) Carey K. Morewedge, Boston University (THE CONVERSATION) Algorithms are a staple of ...

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 ...

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 ...

Despite some progress, gender discrimination in hiring remains a challenge. Women are judged more harshly than men, with a broad assumption of less competence. Only 15 percent of CEOs at Fortune 500 ...

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 ...