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Why do libs claim to love science, but completely ignore/hate stats about race?
| Blathering garrison | 12/11/17 |
| Blathering garrison | 12/11/17 |
| Lascivious trump supporter | 12/11/17 |
| zippy church building becky | 03/26/18 |
| electric charcoal hairy legs idea he suggested | 12/11/17 |
| Blathering garrison | 03/26/18 |
Poast new message in this thread
Date: December 11th, 2017 9:23 PM Author: Blathering garrison And in general, I think it's going to be an increasingly important question about the way that we handle protected classes generally, and maybe race specifically, in data science models of this type. Because otherwise it’s like: okay, you can’t directly model if a person is black. Can you use their zip code? Can you use the racial demographics for the zip code? Can you use things that correlate with the racial demographics of their zip code? And at what level do you draw the line?
And we know what we're doing for mortgage lending—and the answer there is, frankly, as a data scientist, a little bit offensive—which is that we don't give a shit where your house is. We just lend. That's what Rocket Mortgages does. It’s a fucking app, and you're like, “How can I get a million dollar loan with an app?” And the answer is that they legally can't tell where your house is. And the algorithm that you use to do mortgages has to be vetted by a federal agency.
That's an extreme, but that might be the extreme we go down, where every single time anybody gets assessed for anything, the actual algorithm and the inputs are assessed by a federal regulator.
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I think it's the same thing where it's like, okay, you can't look at race, but can you look at correlates of race? Can you look at correlates of correlates of race? How far do you go down before you say, "Okay, that's okay to look at?”
--- You can load in tons and tons of demographic data, and it's disturbing when you see percent black in a zip code and percent Hispanic in a zip code be more important than borrower debt-to-income ratio when you run a credit model. When you see something like that, you're like, “Ooh, that's not good.” Because the frightening thing is that even if you remove those specific variables, if the signal is there, you're going to find correlates with it all the time, and you either need to have a regulator that says, “You can use these variables, you can't use these variables,” or, I don't know, we need to change the law. |
Date: December 11th, 2017 9:24 PM Author: Blathering garrison The other thing that happened recently was the San Bernardino shootings—apparently the guns that were used were financed by a loan from Prosper, which is another peer-to-peer lender. And you just think about where this is going to go. Are we eventually going to get to the point where we have the credit models to assess and not give that guy a loan because of the risk that he could be a Muslim terrorist? Is that the society that we will be living in?
Maybe. But we're going to get there with the data. |
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Date: December 11th, 2017 9:25 PM Author: Lascivious trump supporter LJL at the tremendous malinvestment of enforced ignorance
Time to move to China |
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Date: March 26th, 2018 8:12 PM Author: zippy church building becky (http://www.autoadmit.com/thread.php?thread_id=3825418&forum_id=2#35695389) |
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Date: December 11th, 2017 9:27 PM Author: electric charcoal hairy legs idea he suggested I Fucking Love Science*
*when it furthers my agenda |
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Date: March 26th, 2018 8:08 PM Author: Blathering garrison (http://www.autoadmit.com/thread.php?thread_id=3825418&forum_id=2#35695358) |