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Suresh Venkatasubramanian
Works at U. Utah
Attended Stanford
Lives in Salt Lake City
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Very well put. I could not agree more. 
 
This is one of those ideas which is superficially good and becomes terrible if you look at it more closely. The concept is that in sentencing, we should do a risk assessment, based on objective criteria rather than on the prejudices of the individuals in the court, and use that to influence the decision. Those more likely to re-offend, in this system, would receive harsher and longer sentences.

The first problem with this is that if you build a 100% honest model of re-offending probability, what you're building is a model of your own system, not of the person. For example: If you lock someone in prison for a few years, offering them no training or rehabilitation, and then upon release have various penalties on them which basically prevent them from getting a job -- ranging from the simple "nobody wants to hire someone with a conviction record" to "explicit legal bars to their getting certain kinds of job, living in certain areas, etc" -- then it will probably not surprise you that this person is significantly more likely to turn to a professional life of crime. A model which correctly recognized and predicted this would therefore conclude that the only solution is to lock this person up for life, since at any point after they're released, they're simply likely to become criminals again.

This highlights the deeper problem in such a model, of course, which is that its basic design parameters, where the only variable it controls is "imprison more" or "imprison less," create a false dichotomy: rather than asking "which course of action is most likely to lead to the person no longer engaging in crime," it only considers one possible course of action, and that action (again, by the design of the system) most often increases the probability of future crime. 

The criticism of this system that it will end up encoding implicit racial biases is only sort-of correct. This model will definitely end up having a strong racial component; even if you eliminate race as an input, your race is so strongly correlated to other things like where you live that the system will end up modeling your race, and basing its decisions upon that, one way or the other. And that will, indeed, end up increasing sentences for Black and Latino offenders, for all the reasons specified above.

But in this case, the racial biases which the system would acquire are simply one manifestation of the even deeper and more profound problem that this model is simply designed to optimize for throwing people into prison.

If you want a variation on this which actually works, give the model access to a wide range of possible consequences, and ask it which of those will minimize the odds of re-offense, presumably balanced against various costs. You'll almost certainly find that rehabilitation, training, and treatment overwhelmingly work best to minimize that. (And in the cases where they don't, your best bet is likely to simply take them out and shoot them)

I would actually quite strongly favor such a project, because it would require its creators to make very explicit the thing for which they are trying to optimize. You can't lie to a computer about what you want it to do; if you want to minimize the chance of re-offense, you have to tell it to do so. If you instead want to optimize the system for retribution, or to cow a broad population into submission, or to maximize revenue, the model will absolutely be able to do that as well -- but you would have to tell it explicitly to do so, and it's very hard to lie to yourself about that.

h/t +Amy Quispe over on Twitter for prompting me to actually write about this one.
Interactive graphics by Matthew Conlen, Reuben Fischer-Baum and Andy Rossback This story was produced in collaboration with The Marshall Project. Criminal sentencing has long been based on the pres…
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RT Tim Hopper: FWIW, I wrote up some notes on the Dirichlet distribution and Dirichlet Process
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I've always thought universities should hire faculty like in the draft. This takes it one better.
 
Key and Peele imagine: If we valued teaching as much as we value sports... "being a teacher has never looked so sexy." http://www.slate.com/blogs/browbeat/2015/07/28/key_and_peele_sportscenter_teacher_parody_new_sketch_imagines_teachers_as.html
By now, the lament for the way in which our culture privileges athletics over education is an old, common sentiment—but Key & Peele has breathed new life into the apt observation in their latest sketch, “TeachersCenter.” A spot-on parody of SportsCenter’s hyperbole-laden talking heads, busy CGI ticker screens, and obsessive play-by-plays, the...
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totally, completely, 100% hilarious -and so to the point! No wonder people are starting to follow Comedy Central to get their news...
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Very neat: visualization of the sonic space of poetry. From +Miriah Meyer and her group. For bonus points, they use the word 'topology' :)
Poemage is a visualization system for exploring the sonic topology of a poem. We define sonic topology as the complex structures formed via the interaction of sonic patterns — words connected through some sonic or linguistic resemblance — across the space of the poem. Poemage was developed at ...
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Is it really this hard to receive user input from the keyboard in Swift ? 
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But it's object-oriented, so it's got to be okay. Not like those wacko functional people with their monads and stuff.
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Everyone on the planet: "I hate ranking schemes, but that one that makes me/my university look good ? That one is good". Cc +Arnab Paul
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I hate your ranking scheme of ranking schemes.  Mine is much better.
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apparently using safari gives you an extra hour on a macbook vs chrome. Not to mention not burning my legs
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Sadly, I had to move away from Chrome as it is just too memory and CPU intensive. On one recent Dell laptop, Chrome brought the whole PC to a crawl. When I uninstalled it, it asked whether I uninstalled because it slowed down the computer... I am curious as to what makes Chrome so intense... c.c. +Philippe Beaudoin
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" prices shooting up by around 25% by 2050 according to Bunn’s calculations for his PhD thesis. " I can survive that. [:-)]
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A long-ish review of the 2nd FATML workshop at ICML. 
I was one of the organizers of the 2nd workshop on Fairness, Accuracy and Transparency in Machine Learning (FATML) at ICML 2015, and in my alternate career as moderator of data mining panels, I moderated the closing panel. The panelists were Fernando Diaz from MSR New York, Sorelle Friedler from ...
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I have mixed feelings about such efforts. Removing human bias is good. But replacing it with another form of bias that we understand even less is not great. 

http://fairness.haverford.edu/jekyll//hiring/culture/2015/07/28/culture.html
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+David Eppstein It isn't and that's the problem. The claim being made is that it IS a big change towards being "fairer/more objective"
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It is reassuring that UW's academic freedom policy “includes the right to speak or write—as a private citizen or within the context of one’s activities as an employee of the university—without institutional discipline or restraint on matters of public concern as well as on matters related to professional duties, the functioning of the university, and university positions and policies.” And it is as good as it should get.
Sara Goldrick-Rab is a tenured professor of sociology and education policy at the University of Wisconsin–Madison. She is an outspoken public scholar with a prolific social media presence, and she is devastated about Wisconsin Gov. Scott Walker’s recent changes to tenure and shared faculty governance at her place of employ....
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Academic humor :-)

A recently deceased psychologist arrived at the pearly gates, where St. Peter greeted him and promptly
offered him the choice of heaven or hell. Taken aback, all the psychologist could manage to say was, “Well, may I at least have a look at each before deciding?” “Of course,” said St. Peter, and so guided the psychologist down a long escalator. At the bottom of the ride, the psychologist saw row upon row of desks in an airplanehanger–sized room, each attended by a hunched academic, furiously typing on a laptop. “Yes, that’s pretty grim,” agreed the psychologist. “I can’t imagine spending an eternity like that; let me see heaven.” Riding up the long escalator, his excitement began to build. However, his mouth fell open when at the top of it he again stared out at a vast hall of identical academics, all pounding away on keyboards. “I don’t understand,” was all he could manage to say. “But don’t you see?” said St. Peter, “Its completely different. These scholars are getting their papers published.”
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  • U. Utah
    Associate professor, present
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Salt Lake City
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Aarhus, DK - Stanford, CA - Philadelphia, PA - Morristown, NJ - New Delhi, India - Berkeley, CA
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CS prof, interested in algorithms, geometry, data mining, clustering
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  • Stanford
  • IIT Kanpur
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geomblog
That this restaurant has an overall rating less than 4 is a travesty. Skip Finca's overrated food and preserve your ear drums: Cafe Madrid is a much more intimate (read: quiet and charming) Spanish fine dining experience, with possibly the best service I've ever had in Salt Lake City. Call ahead if you want the paella: it's worth it.
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