New Israeli facial imaging claims to identify terrorists and pedophiles
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Faception 'can match an individual with various personality traits and types with a high level of accuracy'

New Israeli facial imaging claims to identify terrorists and pedophiles

Tel Aviv start-up Faception says its face 'classifiers' can spot criminals and even great poker players in a split second, but the experts are not convinced

An image taken from a May 2016 presentation by Faception co-founder Shai Gilboa (screen capture: YouTube)
An image taken from a May 2016 presentation by Faception co-founder Shai Gilboa (screen capture: YouTube)

A Tel-Aviv based start-up company says it has developed a program to identify personality types such as terrorists, pedophiles, white collar offenders and even great poker players from facial analysis that takes just a fraction of a second.

Faception claims it has signed a contract with a homeland security agency to help identify terrorists, the Washington Post reported Tuesday.

Furthermore, it says it successfully identified nine of the terrorists involved in November’s terror attacks in Paris, according to the Daily Mail.

And it asserts that its technology was able to accurately classify 25 out of 27 facial images of poker players and non-poker players in a blind test.

Claiming that the human face reflects a person’s DNA, Faception has developed 15 “classifiers,” each of which describes a certain personality type or trait.

These classifiers are used to encode facial images taken from video streams, cameras and on- and offline databases to “match an individual with various personality traits and types with a high level of accuracy,” according to the company’s website.

But experts warn that the technology is limited and that ethical issues arise.

Princeton psychology professor Alexander Todorov, an expert in facial perception, told the Washington Post: “The evidence that there is accuracy in these judgments is extremely weak.”

Washington University’s Prof. Pedro Domingos, who wrote “The Master Algorithm,” asked rhetorically: “Can I predict that you’re an ax murderer by looking at your face and therefore should I arrest you?… You can see how this would be controversial.”

He questioned the link between artificial intelligence systems and the markers employed, giving the example of a colleague who developed a nearly 100 percent successful system that differentiated between dogs and wolves, but relied on the fact that all the wolves were pictured against a background of snow.

Domingos told the Washington Post: “If somebody came to me and said ‘I have a company that’s going to try to do this,’ my answer to them would be ‘Nah, go do something more promising.’”

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