AI Algorithms Can Help Predict a Person’s “Political Ideology” Based on Their Facial Characteristics, A Study Conducted in Denmark Found
NEW – AI algorithms can help predict a person’s “political ideology” based on their facial characteristics, a study conducted in Denmark found.
“Both male and female right-wing composites appeared happier than their left-wing counterparts,” the study found.
AI can predict person’s politics by their looks, whether they Smile in Pics: Study
Danish study found AI is 61% accurate at predicting person’s political ideology based on facial features
Artificial intelligence algorithms can help predict a person’s political ideology based on their facial characteristics, a study conducted in Denmark found.
The tech found right-wing politicians were more likely to have happy facial expressions in photos while people pictured with neutral facial expressions were more likely to identify as left-wing, the study said.
The study, “Using deep learning to predict ideology from facial photographs: expressions, beauty, and extra-facial information,” found that AI can predict a person’s political ideology with 61% accuracy when analyzing a photo of a person.
Deep learning, a method in AI where computer scientists teach computers to learn and process information similar to humans, can be used to make predictions about people based on photographs alone, the researchers explained in their paper, which was published in Scientific Reports.
The scientists tried to pin down exactly “what information contributes to the predictive success of these techniques,” according to researchers.
Humans are able to read another person’s face and make judgments almost immediately about personality, intelligence and even political ideology. Study author Stig Hebbelstrup Rye Rasmussen of Arhus University and his colleagues explored if computational neural networks – algorithms that mimic the structure and function of human brains – can predict a person’s political ideology based on a single photo alone.
The scientists trained the neural network with thousands of photos of politicians from the nation’s 2017 municipal elections, noting the elections were not highly polarized nor competitive, and referred to the politicians as the “last amateurs in politics.”
They did away with any photos of candidates who were not explicitly left- or right-wing, were not of European ethnic origin or had been photographed with a beard. The photos only depicted the facial features of the candidates, not photos with backgrounds that could alter predictions. The researchers were then left with 4,647 photos of political candidates, 1,442 of which depicted female politicians.