AI can determine a person’s political affiliation based on their photo with 70% accuracy

Stanford research, which hit headlines in 2017 to design an AI that uses “facial milestones” to determine a person’s sexual preference, has returned with what could be another controversial system.

Dr. Michal Kosinski claims to have a facial recognition algorithm capable of identifying whether a person is liberal or conservative based on a single photo and with more than 70% accuracy.

The technology, which is based on the 2017 AI, was formed with more than a million images from dating websites and Facebook and was programmed to focus on expressions and postures.

Although Kosinski and his team were unable to identify the exact characteristics of the algorithm associated with a political preference, they found some trends such as head orientation and emotional expression in images.

Some examples include people looking directly at the camera who were labeled as liberals and those who showed disgust considered themselves more conservative.

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The technology was formed with more than a million images from dating websites and Facebook and was programmed to focus on expressions and postures. The machine learning system cultivates and resizes the face to reduce the capture of non-facial features

The study, published in Nature, states that when humans are asked to distinguish two faces, one conservative and one liberal, they are correct about 55 percent of the time.

“Because humans may miss or misinterpret some of the keys, their low accuracy does not necessarily represent the limit of what algorithms could achieve,” the study says.

Algorithms are excellent at recognizing patterns in large data sets that no human could process and are increasingly surpassing us in visual tasks ranging from skin cancer diagnosis to facial recognition to judgments based on face of intimate attributes such as sexual orientation (76% vs. 56%) 7, personality (64% vs. 57%; derived from Pearson’s rs) and, as shown here, political orientation. ‘

The researchers used a sample of 1,085,795 participants from the U.S., Canada, and the United Kingdom, along with their self-reported political orientation, age, and gender.

Stanford research that made headlines in 2017 to design an AI that uses “facial milestones” to determine a person’s sexual preferences (pictured) has returned with what could be another controversial system

The study notes that its ethnic diversity included more than 347,000 non-white participants.

The machine learning system cultivates and resizes the face to reduce the capture of non-facial features.

When it came to identifying images of the United States, AI had an accuracy of 72%.

A similar accuracy was observed in the Canadian sample, 71%, and in the United Kingdom, with 70%.

The researchers used a sample of 1,085,795 participants from the U.S., Canada, and the United Kingdom, along with their self-reported political orientation, age, and gender. When it came to identifying US images, AI was 72% accurate. A similar accuracy was observed in the sample of Canada, 71%, and in the United Kingdom, with 70%.

Head orientation (58%) provided the highest predictive power, followed by emotional expression (57%).

Liberals tended to face the camera more directly, were more likely to express surprise and less likely to express disgust; those with a disgusted look were labeled conservatives.

“In other words, a single facial image reveals more about a person’s political orientation than their responses to a fairly long personality questionnaire, including many items seemingly related to political orientation (e.g.,“ Treat All people alike ”or“ I think a lot of tax money is also spent on supporting artists, ”the study says.