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19-Jul-2020 22:21

The suggests that the same approach could be used to try to identify other qualities, such as IQ or political leaning.

The phenomenon is, clearly, troubling to those who hold privacy dear—especially if the technology is used by authoritarian regimes where even a suggestion of homosexuality or criminal intent may be viewed harshly.

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But some recent technologically impressive advances are causing more of a stir.

Late last week, Amarjot Singh from Cambridge University and his colleagues in India published a study on the ar Xiv showing that in many cases it is possible to identify a person using facial recognition even when their face is obscured.

When people are wearing a hat, scarf, and glasses to cover their faces, their algorithms were able to identify people with around 55 percent accuracy.

Earlier this week, Michal Kosinski and Yilun Wang from Stanford University posted a paper on the Psy Arxiv preprint servers, soon to be published by the , which shows that facial recognition AI is more accurate than humans at detecting sexual orientation from pictures of people.

Trained on 130,741 images taken from dating sites where people explain their sexual orientation, the pair’s neural networks can distinguish between gay and heterosexual men in 81 percent of cases from just a single photo.

But some recent technologically impressive advances are causing more of a stir.

Late last week, Amarjot Singh from Cambridge University and his colleagues in India published a study on the ar Xiv showing that in many cases it is possible to identify a person using facial recognition even when their face is obscured.

When people are wearing a hat, scarf, and glasses to cover their faces, their algorithms were able to identify people with around 55 percent accuracy.

Earlier this week, Michal Kosinski and Yilun Wang from Stanford University posted a paper on the Psy Arxiv preprint servers, soon to be published by the , which shows that facial recognition AI is more accurate than humans at detecting sexual orientation from pictures of people.

Trained on 130,741 images taken from dating sites where people explain their sexual orientation, the pair’s neural networks can distinguish between gay and heterosexual men in 81 percent of cases from just a single photo.

(The same numbers for women are 71, 54, and 83, respectively.) The approach is reminiscent of work described last year by researchers from Shanghai Jiao Tong University in China, who trained neural networks using photographs of known criminals and non-criminals.