jm + bias + crime   2

Artificial intelligence is ripe for abuse, tech researcher warns: 'a fascist's dream' | Technology | The Guardian
“We should always be suspicious when machine learning systems are described as free from bias if it’s been trained on human-generated data,” Crawford said. “Our biases are built into that training data.”

In the Chinese research it turned out that the faces of criminals were more unusual than those of law-abiding citizens. “People who had dissimilar faces were more likely to be seen as untrustworthy by police and judges. That’s encoding bias,” Crawford said. “This would be a terrifying system for an autocrat to get his hand on.” [...]

With AI this type of discrimination can be masked in a black box of algorithms, as appears to be the case with a company called Faceception, for instance, a firm that promises to profile people’s personalities based on their faces. In its own marketing material, the company suggests that Middle Eastern-looking people with beards are “terrorists”, while white looking women with trendy haircuts are “brand promoters”.
bias  ai  racism  politics  big-data  technology  fascism  crime  algorithms  faceception  discrimination  computer-says-no 
march 2017 by jm
Founder of Google X has no concept of how machine learning as policing tool risks reinforcing implicit bias
This is shocking:
At the end of the panel on artificial intelligence, a young black woman asked [Sebastian Thrun, CEO of the education startup Udacity, who is best known for founding Google X] whether bias in machine learning “could perpetuate structural inequality at a velocity much greater than perhaps humans can.” She offered the example of criminal justice, where “you have a machine learning tool that can identify criminals, and criminals may disproportionately be black because of other issues that have nothing to do with the intrinsic nature of these people, so the machine learns that black people are criminals, and that’s not necessarily the outcome that I think we want.”
In his reply, Thrun made it sound like her concern was one about political correctness, not unconscious bias. “Statistically what the machines do pick up are patterns and sometimes we don’t like these patterns. Sometimes they’re not politically correct,” Thrun said. “When we apply machine learning methods sometimes the truth we learn really surprises us, to be honest, and I think it’s good to have a dialogue about this.”


"the truth"! Jesus. We are fucked
google  googlex  bias  racism  implicit-bias  machine-learning  ml  sebastian-thrun  udacity  inequality  policing  crime 
october 2016 by jm

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