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to Section One | to Arts & Entertainment
posted Friday, September 15, 2017 - Volume 45 Issue 37
Queer groups condemn study claiming computers can tell if you're Gay from photos
Section One
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Queer groups condemn study claiming computers can tell if you're Gay from photos

by Shaun Knittel - SGN Associate Editor

Can computers have so-called 'gaydar'?

Does AI count as a trusted source in reporting who is Gay and who is not?

These questions would've seemed a bit 'early' one or two years ago, but in 2017 LGBTQ folks are faced with finding answers, because a Stanford University study claims to have used artificial intelligence to help determine a person's sexuality with remarkable accuracy by looking at their face.

LGBTQ advocacy groups have denounced the study as 'dangerous and flawed.'

The study, currently in draft form, has been accepted by the Journal of Personality and Social Psychology. It reportedly used 'deep neural networks to extract features' from more than 35,000 facial images that men and women had posted on an unidentified dating website.

Researchers Michal Kosinski and Yilun Wang said they used an algorithm that could correctly identify Gay men 81% of the time, The Economist reported Friday.

Similarly, they claimed the tool was accurate for 74% of the women it tested.

The obvious critique is that it's unclear what benefits, if any, the research would provide. So why do it in the first place?

Kosinski and Wang disagree. They say their work is a 'preventative measure' that highlights the safety risks many LGBTQ people could face if such technology becomes widely available. It was with that in mind that they chose not to disclose the dating website used in their research in an effort to discourage copycats.

'Tech companies and government agencies are well aware of the potential of computer vision algorithm tools,' says the study. 'In some cases, losing the privacy of one's sexual orientation can be life-threatening. The members of the LGBTQ community still suffer physical and psychological abuse at the hands of governments, neighbors, and even their own families.'

The research was first revealed by The Economist, and soon it made global headlines, with Newsweek, The Guardian, MIT Technology Review, and other publications each running their own takes. Officials at GLAAD and the Human Rights Campaign (HRC) quickly condemned the research, noting that the study relied on 'myriad flaws' and 'had not been peer reviewed.'

It is their argument that Stanford University took online information at face value, and also assumed that one's sexuality did not differ at all from the sexual activity they choose to engage in.

It is important to note that the study did not look at any non-white individuals.

GLAAD's Chief Digital Officer Jim Halloran said the technology used in Kosinski and Wang's study had simply shown that 'a small subset of out white gay and lesbian people on dating sites' look similar.

'This research isn't science or news, but it's a description of beauty standards on dating sites that ignore huge segments of the LGBTQ community, including people of color, transgender people, older individuals, and other LGBTQ people who don't want to post photos on dating sites,' he said. 'At a time [when] minority groups are being targeted, these reckless findings could serve as weapon to harm both heterosexuals who are inaccurately outed, as well as gay and lesbian people who are in situations where coming out is dangerous.'

Ashland Johnson, HRC's Director of Public Education and Research, said the 'dangerously bad' research was 'likely to be taken out of context' and could potentially 'threaten the safety and privacy of LGBTQ and non-LGBTQ people alike.

'Imagine for a moment the potential consequences if this flawed research were used to support a brutal regime's efforts to identify and/or persecute people they believed to be gay,' he said. 'Stanford should distance itself from such junk science rather than lending its name and credibility to research that is dangerously flawed and leaves the world - and this case, millions of people's lives - worse and less safe than before.'

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