A recent study from Stanford University found that a computer algorithm could correctly identify the sexuality of a person through face recognition. This sparked a debate of whether this kind of software violates peoples’ privacy:
Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research that suggests machines can have significantly better “gaydar” than humans.
Deep neural networks are more accurate than humans at detecting sexual orientation from facial images.
We show that faces contain much more information about sexual orientation than can be perceived and interpreted by the human brain. We used deep neural networks to extract features from 35,326 facial images. These features were entered into a logistic regression aimed at classifying sexual orientation.