Since the beginning of the 21st century, the surveillance state has utilized technology derived from Silicon Valley, such as facial recognition algorithms, to enhance society’s control.
Authoritarian regimes and unscrupulous corporations are leveraging these technologies to track citizens, stalk criminals, and monitor employees, but what if this technology, rapidly advancing in the last couple of years, can determine a person’s political views?
Imagine this; obviously, the Washington Metropolitan Area is lined with surveillance cameras, with some cameras that may already be employing facial recognition algorithms. Hypothetically speaking, what if these cameras could recognize an angry mob and accurately (to some degree) identify their political views by observing their faces and then alert authorities of potential social unrest in a specific area.
While that technology has yet to be deployed, it may certainly exists.
Researchers have developed a facial recognition algorithm that they claim can determine a person’s political views with reasonable accuracy.
Stanford University’s Michal Kosinski conducted a study published on Monday in the Nature journal Scientific Reports.
“Ubiquitous facial recognition technology can expose individuals’ political orientation, as faces of liberals and conservatives consistently differ,” Kosinski said.
He trained the facial recognition algorithm to accurately guess a person’s political view with an accuracy rating of about 72%. To do this, the researcher trained an algorithm with over one million profiles from social media websites across the US, UK, and Canada.
“Political orientation was correctly classified in 72% of liberal-conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity,” he said.
Kosinski said the algorithm is “high predictability” in determining political views from viewing faces, which implies a notable difference between the facial images of conservatives and liberals.
One of the most significant facial features that differentiate both political parties’ faces – aside from gender, age and race was head orientation and emotional expression. He also said liberals were more likely to stare directly at the camera and more likely to look surprised than disgusted.
Here are the procedures used to predict political orientation from facial images. And by the way, she’s a liberal.
It was also explained that liberals tend to smile “more intensely and genuinely,” leaving them with a different wrinkle pattern as they age. Meanwhile, conservatives “tend to be healthier, drink less alcohol and smoke less, and have a different diet” – attributes that affected the skin’s health and texture.
The thought that algorithms can determine your political views from a quick scan of your face is a frightening one.
Kosinski is known for his work with the data-mining firm Cambridge Analytica ahead of the 2016 US Presidential election.
He also worked as an adviser on Faception, a company that uses facial recognition algorithms to determine if someone is a terrorist, pedophile, or a criminal.
China has been deploying facial recognition cameras for years to monitor its citizens. This sort of surveillance is coming to America – by the way – it’s already here.
Perhaps wearing a face mask could render facial recognition cameras useless…