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 ...

AI is riddled by bias, especially in healthcare. Just one well-known example is a study from 2019 that revealed racial bias in a clinical algorithm used by hospitals showing that Black patients had to ...

AI is increasingly finding its way into healthcare decisions, from diagnostics to treatment decisions to robotic surgery. As I’ve written about in this newsletter many times, AI is sweeping the ...

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 ...

Based on the comprehensive findings of a review, investigators outline several crucial policy implications, each designed to address the complex issue of bias mitigation in clinical algorithms ...

A paper published today in JAMA Network Open addresses bias in healthcare algorithms and provides the healthcare community with guiding principles to avoid repeating errors that have tainted the use ...

(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 ...

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 ...