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Another Scientific Incarnation of Selective Correlation
When the 19th century was young, a Viennese physician Franz Joseph Gall got the ball rolling for the "science" of phrenology. (Not to be confused with phenology.) Phrenology believed that the shape and contour of a person's skull revealed their character, and thus could be used by employers and the criminal justice system to identify the lazy and the miscreants with simply a few quick measurements.
It also came in handy to justify slavery in the U.S., as depicted in Tarantino's Django Unchained.
Phrenology never went away, but went on to lurk in spin-offs such as eugenics. And if there were to be an updated incarnation of using a few quick body measurements to find the evil among us, it would have to employ sci/tech terms as "researchers", "algorithms" and "AI".
And so it does: Convict-spotting algorithm criticised
Researchers trained an algorithm using more than 1,500 photos of Chinese citizens, hundreds of them convicts.
They said the program was then able to correctly identify criminals in further photos 89% of the time. But the research, which has not been peer reviewed, has been criticised by criminology experts who say the AI may reflect bias in the justice system. "This article is not looking at people's behaviour, it is looking at criminal conviction..."
So, will AI ever get this god-like?
[Continues...]
AI Can Predict the Future Criminals Based on Facial Features
The bankrupt attempt to infer moral qualities from physiology was a popular pursuit for millennia, particularly among those who wanted to justify the supremacy of one racial group over another. But phrenology, which involved studying the cranium to determine someone's character and intelligence, was debunked around the time of the Industrial Revolution, and few outside of the pseudo-scientific fringe would still claim that the shape of your mouth or size of your eyelids might predict whether you'll become a rapist or thief.
Not so in the modern age of Artificial Intelligence, apparently: In a paper titled "Automated Inference on Criminality using Face Images," two Shanghai Jiao Tong University researchers say they fed "facial images of 1,856 real persons" into computers and found "some discriminating structural features for predicting criminality, such as lip curvature, eye inner corner distance, and the so-called nose-mouth angle." They conclude that "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."
[...] The study contains virtually no discussion of why there is a "historical controversy" over this kind of analysis — namely, that it was debunked hundreds of years ago. Rather, the authors trot out another discredited argument to support their main claims:, that computers can't be racist, because they're computers:
[...] Absent, too, is any discussion of the incredible potential for abuse of this software by law enforcement. Kate Crawford, an AI researcher with Microsoft Research New York, MIT, and NYU, told The Intercept, "I'd call this paper literal phrenology, it's just using modern tools of supervised machine learning instead of calipers. It's dangerous pseudoscience."
(Score: 3, Interesting) by AthanasiusKircher on Sunday November 27 2016, @09:58PM
Certainly subgroups of people, say males 15-35 from ___ group are about 1000% more likely to commit violent crime. That's a little more than the 10-30% you're suggesting.
Actually, I'm pretty sure I also said "perhaps double or triple," i.e., well over 100% more likely. Yes, I didn't go up to 1000%, but I wasn't thinking of age restrictions. I agree that you MIGHT get that high based on pretty crude measures.
What if this narrows it to a subset of 3% that are 100,000% more likely to commit violent crime?
First, I really doubt we could get such precision. But even if we could, what are we measuring, though? There are HUGE numbers of confounding factors here. You have selection bias (as was already pointed out in another post) -- what crimes are reported, which are investigated, which are investigated "more thoroughly," which are charged, which are actively prosecuted vs. pled down until these people don't end up in prison at all. And that's just possible bias created by police and the district attorney. Now introduce various other demographic factors (which might be used -- either implicitly or explicitly -- by the attorneys to argue for conviction), whether the defendant can afford competent defense, what biases juries might have for or against certain "types" of defendants (which, yes, includes how they look), etc., etc.
And that's only selection bias for who gets convicted. Then you have the actual statistical confounding factors, like what I brought up about poverty. If you control for poverty and educational level, the majority of the supposed white/black difference in crime rate disappears. There's still some difference, but it's much smaller (and perhaps could be explained by some other confounding factors). So, if we only look at facial features or other anatomical features, are we really measuring the RELEVANT differences? Or are we merely isolating some groups that have apparent higher crime rates based on appearance (pun intended), while overlooking other significant causes of crime that might not show so readily on a face?
Obviously this isn't justification to toss someone in jail, but it could be useful(though "unpopular") to look at them more closely.
Greater than 99% of people -- whether White, Black, or otherwise are NOT murderers. Greater than 99% of Muslims are NOT terrorists. We clearly live in a culture of fear, rather than judging people rationally.
Oh and for one last example: Greater than 95% of Catholic priests are NOT child molesters. The reason I mention that last stat is because a number of statistical studies have shown that the rate of child molestation doesn't appear to be higher among Catholic priests than it is among Protestant ministers, or Boy Scout leaders, or teachers, or coaches, or whatever. The difference is the Catholic Church kept central records, not that they had a higher incidence than the general population. Lots of things can make incidence appear to be worse among certain populations. (And just in case you try to go this way, note that I am NOT Catholic and have no tie to the church. I just am wary of statistical biases created by perception.)