Facial recognition can predict person’s political orientation with 72% accuracy
There's an avalanche of people commenting on this who didn't bother to check the article before raising their methodological objections, so let's get these out of the way here.- Yes, they controlled for objects appearing in the pictures that might indicate political affiliation. The images are tightly cropped around the face. See Methods.- Yes, this is significantly better than both a coin flip and a human classifier. They gave the same test to humans, who did much worse than the model. See Abstract, Introduction, and Results.- Yes, this is doing more than just detecting a person's race, age, and/or gender. The classifier is still accurate when they compare people with the same race, age, and gender. See Results.If you want to discuss actual limitations in the study, here are some the author points out:- "A more detailed picture could be obtained by exploring the links between political orientation and facial features extracted from images taken in a standardized setting while controlling for facial hair, grooming, facial expression, and head orientation."- "Another factor affecting classification accuracy is the quality of the political orientation estimates. While the dichotomous representation used here (i.e., conservative vs. liberal) is widely used in the literature, it offers only a crude estimate of the complex interpersonal differences in ideology. Moreover, self-reported political labels suffer from the reference group effect: respondents’ tendency to assess their traits in the context of the salient comparison group."