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DEEP STATE AI ALGORITHMS WILL SCAN FACES TO DETERMINE CRIMINALITY

[1/28/17]  The deep state is now trying to determine if someone is a criminal based solely on an image of their face. A Cornell University study describes how scientists are using computer generated algorithms to decide if someone should be labeled felonious, completely ignoring the fact that using a computer model which mimics facial features cannot possibly be a legal means with which to label people either criminal or non-criminal.

Nonetheless, scientists used facial images of 1856 real persons, “controlled for race, gender, age and facial expressions, nearly half of whom were convicted criminals, for discriminating between criminals and non-criminals. All four classifiers perform consistently well and produce evidence for the validity of automated face-induced inference on criminality, despite the historical controversy surrounding the topic.”

This means that computers and scientific studies funded by an elite class will now determine if someone is criminal in nature.

In the study titled “Automated Inference on Criminality using Face Images,” scientists Xi Zhang and Xiaolin Wu state,

“Above all, the most important discovery of this research is that criminal and non-criminal face images populate two quite distinctive manifolds. The variation among criminal faces is significantly greater than that of the non-criminal faces. The two manifolds consisting of criminal and non-criminal faces appear to be concentric, with the non-criminal manifold lying in the kernel with a smaller span, exhibiting a law of normality for faces of non-criminals. In other words, the faces of general law-biding public have a greater degree of resemblance compared with the faces of criminals, or criminals have a higher degree of dissimilarity in facial appearance than normal people.”

The absurdity of this claim aside, it is not a new idea. Cesare Lombroso, an Italian criminologist, believed that criminals were “throwbacks” more closely related to apes than law-abiding citizens. He was convinced he could identify them by ape-like features such as a sloping forehead, unusually sized ears and various asymmetries of the face and long arms. Indeed, he measured many subjects in an effort to prove his view although he did not analyze his data statistically.

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