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In the science fiction short story and 2002 film "Minority Report" (also a short-lived series with Megan Good), by the legendary Philip K. Dick, using psychics (you can get away with that in science fiction) as "PreCogs," they could apprehend citizens guilty of "PreCrime." In other words before you even THINK you're going to commit a crime, you are guilty before proven innocent. I guess civil liberties go out the window in 2054.
One part of this report gave me some pause:
With the advent of photography, a tiny fraction of 19th-century scientists believed they could develop methods of accurately identifying criminals by their facial features. While their hypotheses were eventually discredited, new artificial intelligence technology suggests their claims might’ve been valid after all.
Xiaolin Wu and Xi Zhang from Shanghai Jiao Tong University in China have resurrected this facial recognition tradition and built a neural network that can supposedly pick out criminals by simply looking at their faces.
To accomplish this, the researchers used an array of machine-vision algorithms to examine a series of facial juxtapositions between photos of criminals and non-criminals with the goal of finding out whether a neural network can reliably tell them apart.
As MIT Technology review explains, there are three defining facial features the neural network factored in to make its classifications:
[T]he curvature of upper lip which is on average 23 percent larger for criminals than for noncriminals; the distance between two inner corners of the eyes, which is 6 percent shorter; and the angle between two lines drawn from the tip of the nose to the corners of the mouth, which is 20 percent smaller.
I might have such an upper lip, as may many other ethnicities.
Artificial intelligence like its original biological intelligence model could be taught by condition and repetition: biased prejudice in service of the state. 😨
The Next Web:
This scary artificial intelligence has learned how to pick out criminals by their faces