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The Minority Report a Reality!!!!!!!!!

Started by 11B4V, May 23, 2016, 07:33:49 PM

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grumbler

Quote from: Jacob on May 24, 2016, 06:35:51 PM
I think what I've been exposed to is people who talk the talk you just talked there, and who wielded spreadsheets and data to advance their arguments; but they have done so in areas where the proper application of algorithms is not well understood or where they themselves have no real understanding of the data they are wielding.

... cargo-cult and/or management fad applications of algorithms, as it were.

Yes. people who build models are frequently shockingly ignorant of the real-world constraints that limit their models, especially on the margins. I remember a briefing by representatives of [corporation name redacted] at one of the annual ASW strategic games my company hosted; they claimed that the SSN-21 class would have a 350-1 kill ratio against 4th generation Soviet subs (this was back when there was a Soviet Union) and that one Seawolf had a 50% chance of sinking every Northern Fleet submarine in 90 days.  They had neglected the fact that the Seawolf didn't carry the 200 or so torpedoes necessary for that task, as well as the fact that their kill ratios were simply unbelievable.
The future is all around us, waiting, in moments of transition, to be born in moments of revelation. No one knows the shape of that future or where it will take us. We know only that it is always born in pain.   -G'Kar

Bayraktar!

CountDeMoney

Quote from: derspiess on May 24, 2016, 08:28:10 AM
And get rid of them goddamned Glocks and go back to the humble, trusty .38 revolver, amirite??

Would've saved more than one locker room sink from the ignominy of an accidental discharge.  :lol:

CountDeMoney

Quote from: Jacob on May 24, 2016, 06:35:51 PM
... cargo-cult and/or management fad applications of algorithms, as it were.

That's all it is:  management fads.  Oh boy oh boy oh boy, how can we import Agile project management into gang violence mitigation? 

We had algorithms back in my day, you know.  Analog 2D mainframes, mounted directly on the wall. The black pins were shootings, the red pins were homicides, the green pins were drug arrests, etc.  We algorithmed the shift's patrols where the pins were all bunched together, all algorithmically and shit. 

DGuller

Quote from: CountDeMoney on May 24, 2016, 07:57:27 PM
Quote from: Jacob on May 24, 2016, 06:35:51 PM
... cargo-cult and/or management fad applications of algorithms, as it were.

That's all it is:  management fads.  Oh boy oh boy oh boy, how can we import Agile project management into gang violence mitigation? 

We had algorithms back in my day, you know.  Analog 2D mainframes, mounted directly on the wall. The black pins were shootings, the red pins were homicides, the green pins were drug arrests, etc.  We algorithmed the shift's patrols where the pins were all bunched together, all algorithmically and shit.
Predictive modeling has made some strides in recent years.  Quite a few, in fact.

Berkut

Quote from: CountDeMoney on May 24, 2016, 07:57:27 PM
Quote from: Jacob on May 24, 2016, 06:35:51 PM
... cargo-cult and/or management fad applications of algorithms, as it were.

That's all it is:  management fads.  Oh boy oh boy oh boy, how can we import Agile project management into gang violence mitigation? 

We had algorithms back in my day, you know.  Analog 2D mainframes, mounted directly on the wall. The black pins were shootings, the red pins were homicides, the green pins were drug arrests, etc.  We algorithmed the shift's patrols where the pins were all bunched together, all algorithmically and shit. 

And there was probably some old timer bitching about how these new fangled pins and such was destroying real police work.

What I find amusing about this is that what you describe is in fact using data modelling and alogirthmic predictions to target high risk areas and individuals. The cop on the beat, learning his neighborhood, he is doing the *exact same thing* except he is doing so with a human being the data collection and analysis tool. And you know what? Humans are actually really fucking good at that. In fact, the human brains ability to put disparate data together isn't even well understood yet - it manages to put data together in ways that come to useful conclusions that are beyond our ability to rationally understand at times.

Of course, it is also rather good at putting data together in ways that lead to radically incorrect conclusions. See around a million easy to cite examples of police putting innocent people in jail based on jumping to conclusions about what they "know" to be true, that turns out to not be true at all, and fuck any evidence to the contrary.

Bitching about data modelling and non-human data analysis is idiotic. We cannot function without collecting data and interpreting it - hell, you could argue that that is the fundamental computational activity of all police work. No matter how you collect the data, and how you store the data, and how you analyze the data, if you do any of those steps poorly, you will lead to poor conclusions and poor outcomes.

Arguing that one particular method is inherently not to be trusted because it is new is just rank Ludditism. It is no different than people X years ago complaining that cops have no business being in cars, or having radios, or whatever.
"If you think this has a happy ending, then you haven't been paying attention."

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Monoriu

A programme isn't perfect, but has the potential to be better than humans.

The Minsky Moment

Quote from: DGuller on May 24, 2016, 05:45:45 PM
You validate the model when you build it, not after deploying it. 

If the model is being used to generate policy responses in the real world, then validation requires correctly anticipating behavioral response across a broad domain.  I.e. pre-validation will not be effective.
The purpose of studying economics is not to acquire a set of ready-made answers to economic questions, but to learn how to avoid being deceived by economists.
--Joan Robinson

DGuller

Quote from: The Minsky Moment on May 25, 2016, 10:52:51 AM
Quote from: DGuller on May 24, 2016, 05:45:45 PM
You validate the model when you build it, not after deploying it. 

If the model is being used to generate policy responses in the real world, then validation requires correctly anticipating behavioral response across a broad domain.  I.e. pre-validation will not be effective.
In that case, you go sit in a corner and sob about the futility of it all.

CountDeMoney

Quote from: Berkut on May 25, 2016, 10:14:19 AM
And there was probably some old timer bitching about how these new fangled pins and such was destroying real police work.

That's goddamned right, what with ruining perfectly good maps with holes like that.