One of the most controversial psychological studies in recent memory appeared last month as an advance release of a paper that will be published in the Journal of Personality and Social Psychology. Yilun Wang and Michal Kosinsky, both of the Graduate School of Business at Stanford University, used a deep neural network (a computer program that mimics complex neural interactions in the human brain) to analyze photographs of faces taken from a dating website and detect the sexual orientation of the people whose images were shown. The algorithm correctly distinguished between straight and gay men 81 percent of the time. When it had five photos of the same person to analyze, the accuracy rate rose to 91 percent. For women, the score was lower: 71 percent and 83 percent, respectively. But the algorithm scored much higher than its human counterparts, who guessed correctly, based on a single image, only 61 percent of the time for men and 54 percent for women.
