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" "Why isn't my face being detected? We have to look at how we give machines sight," she said in a TED Talk late last year. "Computer vision uses machine-learning techniques to do facial recognition. You create a training set with examples of faces. However, if the training sets aren't really that diverse, any face that deviates too much from the established norm will be harder to detect.""

"In 2019, Genevieve (co-author of this article) and her husband applied for the same credit card. Despite having a slightly better credit score and the same income, expenses, and debt as her husband, the credit card company set her credit limit at almost half the amount. "

"Assigning female genders to digital assistants such as Apple's Siri and Amazon's Alexa is helping entrench harmful gender biases, according to a UN agency."

"The unique approach to 'deception detection' analyses the micro-gestures of travellers to figure out if the interviewee is lying."

"Apart from biases in the training databases, it's hard to know how well face-recognition systems actually perform in the real world, in spite of recent gains. Anil Jain, a professor of computer science at Michigan State University who has worked on face recognition for more than thirty years, told me, "Most of the testing on the private venders' products is done in a laboratory environment under controlled settings. In real practice, you're walking around in the streets of New York. It's a cold winter day, you have a scarf around your face, a cap, maybe your coat is pulled up so your chin is partially hidden, the illumination may not be the most favorable, and the camera isn't capturing a frontal view.""

"Admission algorithms can make or break your academic plans. A Washington Post investigation found 44 schools use prediction software to give applicants a score out of 100 for its admissions process. The score considers different aspects of a student's application from test scores, home address, transcripts, and even what websites they've visited. That's all calculated to rate how strong of a match a student is for a school."