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Facial Recognition Study ‘Creepy’

by our Editors in General , 25 november 2017

Dit artikel is ook in het Nederlands beschikbaar


Researchers at Stanford University in the US claim they can determine whether someone is lesbian or gay with relative certainty through facial recognition. COC president Tanja Ineke speaks of ‘creepy’ research. Ineke continues: “What are the benefits of this study? Let them study how to tackle homophobia!”

“It is horrifying to think that this kind of technique could fall into the wrong hands, for instance the regimes in Chechnya or Iran, countries where LGBTIs are oppressed. As far as we are concerned, human rights organisations, governments and social media must put a stop to these techniques, in order to limit the dangers of this technology as much as possible.”

The COC president pointed out that researchers in the past have thought to have found a method to determine whether someone is LGBTI, but this was proven to be incorrect. Ineke points out the shortcomings of this study. They only looked at Caucasians that have come ‘out of the closet,’ and the study does not seem to include bisexuals.

Researchers Michal Kosinski and Yilan Wang of Stanford University supposedly discovered that a computer algorithm developed by them can correctly recognize gay men in 81 percent, and lesbians in 74 percent of all cases. With this result, the computer algorithm shows a better score than people, as only 61 percent of people detect a homosexual man, and 54 percent detect a homosexual woman. The computer program scores even better the more photographs are available of those people being identified as homosexual. In those cases, the algorithm scores 91% for homosexual men, and 83% for homosexual women. This study used 35,000 photos of faces of predominantly Caucasian men and women from American dating sites.

The researchers themselves have also come to the conclusion that their results could endanger the privacy and security of LGBTIs, as companies and states increasingly use computer algorithms to map people's private lives and personal views.
 



 







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