News  |  ,   |  March 5, 2019

The infamous AI gaydar study was repeated – and, no, code can’t tell if you’re straight or not just from your face

News article by Katyanna Quach.
Published by The Register.


The controversial study that examined whether or not machine-learning code could determine a person’s sexual orientation just from their face has been retried – and produced eyebrow-raising results.

John Leuner, a master’s student studying information technology at South Africa’s University of Pretoria, attempted to reproduce the aforementioned study, published in 2017 by academics at Stanford University in the US. Unsurprisingly, that original work kicked up a massive fuss at the time, with many skeptical that computers, which have zero knowledge or understanding of something as complex as sexuality, could really predict whether someone was gay or straight from their fizzog.

The Stanford eggheads behind that first research – Yilun Wang, a graduate student, and Michal Kosinski, an associate professor – even claimed that not only could neural networks suss out a person’s sexual orientation, algorithms had an even better gaydar than humans. [ . . . ]