Two Stanford University researchers have reported startling accuracy in predicting sexual orientation using computer technology. Dr. Michal Kosinski and Yilun Wang, whose research will be published by the Journal of Personality and Social Psychology, say that AI can distinguish between the face of a heterosexual man and a homosexual man in 81 percent of cases. For women, the predictive accuracy is 71 percent. The average human is less adept at identifying between straight and gay people purely based on an image: We are only able to guess correctly in 61 percent of cases for men and 54 percent for women. When scientists presented the algorithm with five facial images of a single person, the accuracy increased to 91 percent for men and 83 percent for women. Kosinski and Wang used "deep neural networks" to sample 35,326 facial images of men and women taken from a dating website. The findings advance discussion about the biological factors that may determine one's sexual orientation. However, Kosinski tells The Economist, the research is not intended to be used to profile or "out" homosexual men and women. Rather, it is designed to demonstrate - or even warn - that technological advances can be used for such means and could pose a threat to our privacy, given that digital information is so easily accessible. The researchers argue the "digitalization of our lives and rapid progress in AI continues to erode the privacy of sexual orientation and other intimate traits."