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"Researchers at Columbia University sought to shed light on the problem by tasking 400 AI engineers with creating algorithms that made over 8.2 million predictions about 20,000 people. In a study accepted by the NeurIPS 2020 machine learning conference, the researchers conclude that biased predictions are mostly caused by imbalanced data but that the demographics of engineers also play a role."

"But it also raises uncomfortable questions: is AI technology helping marginalized people overcome bias, or just perpetuating the biases that make their lives hard in the first place?"

"A Taiwanese American model says a well-known fashion designer uploaded a digitally altered runway photo that made her appear white. In a TikTok about the incident that has been viewed 1.8m times in the last week, Shereen Wu says Michael Costello, a designer who has worked with Beyoncé, Jennifer Lopez, and Celine Dion, posted a photo to his Instagram from a recent Los Angeles fashion show. The photo depicts Wu in the slinky black ballgown that she walked the runway in - but her face has been changed, made to appear as if she is a white woman."

"On inbuilt bias in algorithms, Sharkey said: "There are so many biases happening now, from job interviews to welfare to determining who should get bail and who should go to jail. It is quite clear that we really have to stop using decision algorithms, and I am someone who has always been very light on regulation and always believed that it stifles innovation."

"But users began to spot flaws in the feature over the weekend. The first to highlight the issue was PhD student Colin Madland, who discovered the issue while highlighting a different racial bias in the video-conference software Zoom. When Madland, who is white, posted an image of himself and a black colleague who had been erased from a Zoom call after its algorithm failed to recognise his face, Twitter automatically cropped the image to only show Madland."

"Concerns have been growing about AI's so-called "white guy problem" and now scientists have devised a way to test whether an algorithm is introducing gender or racial biases into decision-making."