For more than a decade, journalists and researchers have been writing about the dangers of relying on algorithms to make weighty decisions: who gets locked up, who gets a job, who gets a loan — even ...

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 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 ...

New research by Questrom’s Carey Morewedge 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 ...

LONDON – Twitter says it’s investigating why its picture-cropping algorithm sometimes prefers white faces to Black ones. The investigation comes after Twitter users noticed Black faces were less ...

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.

Understanding bias in hiring algorithms and ways to mitigate it requires us to explore how predictive technologies work at each step of the hiring process. Though they commonly share a backbone of ...

Artificial intelligence (AI) is transforming every aspect of our lives. Humans can now reduce complex and mundane tasks while focusing on core working requirements, significantly increasing workforce ...

Zalis is a pioneer for online research, movement leader, and champion of gender equality. She is an internationally renowned entrepreneur, speaker, mentor, and CEO of The Female Quotient. In our ...

Health systems rely on commercial prediction algorithms to identify and help patients with complex health needs. We show that a widely used algorithm, typical of this industry-wide approach and ...