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New AI Can Suppose Whether You’re Queer or Straight from a Photograph
Keywords:Artificial Intelligence, Consent, Discrimination, Harassment, LGBTQIA+, Privacy Violation
Author: Sam Levin
Publisher: The Guardian
Publication Year: 2017
Summary: The following article discusses how an artificial intelligence, developed by Stanford University, was used to guess people’s sexualities based on photos of their faces. The algorithm was 81% accurate with men and 74% with women. As many LGBTQ people face discrimination and harassment, the algorithm had a risky potential to violate people’s privacy and endanger their security. The algorithm start various physical features to distinguish lgbtq+ men and women from straight men and women. Because the algorithm performed better than human judges did, the algorithm would theoretically be able to “out” members of the LGBTQ society. Though the investigate was based on 35,000 publically accessible images, many people who identify as LGBTQ prefer to keep their sexualities private. The explore also did not include any people of color, or consider transgender or bisexual people. The research intended to support the theory that sexuality is
By Nouran Sakr
Algorithm Achieves Higher Accuracy Rates than Humans
A study from Stanford University suggests that a profound neural network (DNN) can distinguish between gay and linear people, with 81 per cent accuracy in men and 71 per cent in women. The research was based on a sample of 35,326 facial images of pale men and women that were posted publicly on a US dating website. The DNN, a machine learning system, was presented with pairs of images, where one individual was gay and the other was straight.
The DNN’s algorithm displayed even higher accuracy rates when presented with five facial images per person: 91 per cent in men and 83 per cent accuracy in women. Human judges, when presented with one image, achieved a much reduce accuracy rate: 61 per cent for men and 54 per cent for women.
According to the research, there were certain trends in facial features that distinguished between homosexual and straight people. Narrower jaws, larger foreheads, and longer noses were frequent among gay men, while gay women were more likely to have smaller foreheads and wider jaws.
The authors of the report, Yilun Wang and Michal Kosinski, concluded that homosexual men and women have more andr
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New AI can guess whether you're gay or straight from a photograph
Artificial intelligence can accurately think whether people are gay or straight based on photos of their faces, according to fresh research that suggests machines can have significantly better “gaydar” than humans.
The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the hereditary origins of sexual orientation, the ethics of facial-detection technology, and the potential for this compassionate of software to violate people’s privacy or be abused for anti-LGBT purposes.
The machine intelligence tested in the research, which was published in the Journal of Personality and Social Psychology and first reported in the Economist, was based on a sample of more than 35,000 facial images that men and women publicly posted on a US dating website. The researchers, Michal Kosinski and Yilun Wang, extracted features from the images using “deep neural networks”, meaning a sophisticated mathematical system that learns to analyze visuals based on a large dataset.
The research establish that gay