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Make Algorithms Accountable

nytimes.com

21–30 of 33 posts

Re: Make Algorithms Accountable

#21

I would love—assuming Congress had their heads in the right place—to make a small council (council to prevent Luddite or crazy Presidents/Congresses from completely wreaking havoc) that would understand tech stuff like we do. People who just comment "Yea that's not how this works," or "hey techies think this is a good idea." Because I give a lot of governments good credit on tech stuff (and especially local governmen…

Technology isn't special. Politicians are also uneducated on every other industry and area of life. It's just that when they misunderstand technology you notice.

Well I notice it about a couple areas but in a ton of those areas we have specific branches of the executive to deal with the nitty gritty but not really one for technology. Similar in UK where they have white wall ministries to deal with things that parliamentarians should not be expected to have a deep knowledge of.

Re: Make Algorithms Accountable

#22

It's tremendously disheartening to see the mainstream media repeating ProPublica's lies. They ran a statistical analysis. Their R-script said that bias was statistically insignificant. So they repeated a bunch of anecdotes in the story and left that part of the analysis out. Reporting null results won't get you cited by the NYT, I guess. https://www.chrisstucchio.com/blog/2016/propublica_is_lying.... The power of the…

I might be misunderstanding the article you linked, but it seems very misleading to me (though I agree with the conclusion that the ProPublica article is misleading). They claim to conclude:

"The predictor is probably not biased against any particular race - the race_factorAfrican-American:score_factorHigh term is not statistically significant. Or, as ProPublica puts it, it's "almost statistically significant"."

I don't think you can conclude that the predictor is probably not biased against any particular race -- you can only use significance to reject the null hypothesis, not prove the null hypothesis (especially since the significance is still somewhat high). Am I misunderstanding the claim in the article?

Re: Make Algorithms Accountable

#23

It's tremendously disheartening to see the mainstream media repeating ProPublica's lies. They ran a statistical analysis. Their R-script said that bias was statistically insignificant. So they repeated a bunch of anecdotes in the story and left that part of the analysis out. Reporting null results won't get you cited by the NYT, I guess. https://www.chrisstucchio.com/blog/2016/propublica_is_lying.... The power of the…

I might be misunderstanding the article you linked, but it seems very misleading to me (though I agree with the conclusion that the ProPublica article is misleading). They claim to conclude: "The predictor is probably not biased against any particular race - the race_factorAfrican-American:score_factorHigh term is not statistically significant. Or, as ProPublica puts it, it's "almost statistically significant"." I do…

I wrote the article. It's always tricky to me to figure out how to phrase a statement about a frequentist method (since frequentist methods formally say so little). I may have phrased this incorrectly.

So what I'm attempting to say is that they ran a statistical test, were unable to reject the null hypothesis, and then wrote an article phrased as if they did exactly that. But I think you are right that my phrasing is incorrectly, however.

Re: Make Algorithms Accountable

#24
post #2

I have a moral objection to the government using mechanized algorithms for e.g. sentencing, because the government is (or ought to be) accountable to the public, and must be able to justify all actions. Proprietary algorithms are particularly odious, because it is impossible to "justify" a decision even in the sense of tracing how the algorithm got to that point. On the other hand, private individuals ought not to be…

Your argument in the second paragraph seems to be that arbitrary discrimination, for instance racial discrimination, is economically irrational; discriminatory companies will be out-competed by non-discriminatory companies. But this ignores the historic reality of racial discrimination, which is that in some areas of the US, at some points in time, a significant number of white people were bigoted, and strongly (for…

You are missing a very important part of historic reality - pro-discrimination laws. Prior to the Civil Rights Act, we had a lot of local/state level economic regulation designed to prevent a race to the bottom (e.g. whites being forced to compete economically with colored folk) and to prevent greedy businessmen from acting against the public interest.

Re: Make Algorithms Accountable

#25

Earlier quoted context omitted.

I might be misunderstanding the article you linked, but it seems very misleading to me (though I agree with the conclusion that the ProPublica article is misleading). They claim to conclude: "The predictor is probably not biased against any particular race - the race_factorAfrican-American:score_factorHigh term is not statistically significant. Or, as ProPublica puts it, it's "almost statistically significant"." I do…

I wrote the article. It's always tricky to me to figure out how to phrase a statement about a frequentist method (since frequentist methods formally say so little). I may have phrased this incorrectly. So what I'm attempting to say is that they ran a statistical test, were unable to reject the null hypothesis, and then wrote an article phrased as if they did exactly that. But I think you are right that my phrasing is…

> It's always tricky to me to figure out how to phrase a statement about a frequentist method

That seems to me to be a fault whose location is not in your stars.

Re: Make Algorithms Accountable

#26

I would love—assuming Congress had their heads in the right place—to make a small council (council to prevent Luddite or crazy Presidents/Congresses from completely wreaking havoc) that would understand tech stuff like we do. People who just comment "Yea that's not how this works," or "hey techies think this is a good idea." Because I give a lot of governments good credit on tech stuff (and especially local governmen…

That's what lobbying is.

Except lobbyists answer to the people who pay them. Closest thing we have to the tech community paying lobbyists is the EFF.

If we had a professional organization, that would be a reasonable place to organize such a lobbying arm.

Re: Make Algorithms Accountable

#27

Earlier quoted context omitted.

Your argument in the second paragraph seems to be that arbitrary discrimination, for instance racial discrimination, is economically irrational; discriminatory companies will be out-competed by non-discriminatory companies. But this ignores the historic reality of racial discrimination, which is that in some areas of the US, at some points in time, a significant number of white people were bigoted, and strongly (for…

You are missing a very important part of historic reality - pro-discrimination laws. Prior to the Civil Rights Act, we had a lot of local/state level economic regulation designed to prevent a race to the bottom (e.g. whites being forced to compete economically with colored folk) and to prevent greedy businessmen from acting against the public interest.

I don't doubt that such laws existed, though I know very little about them. I might surmise that the "public interest" upheld by these laws was based on a rather restrictive definition of "public".

But I don't quite understand your point. My point was that if your goal is to end racial discrimination, free-market forces left to themselves are not sufficient. Sometimes legislation is needed to level the playing field and make non-discriminatory businesses economically viable.

Does your post relate to that, and I am just missing something? Or are you heading in a different direction?

Re: Make Algorithms Accountable

#28

It's tremendously disheartening to see the mainstream media repeating ProPublica's lies. They ran a statistical analysis. Their R-script said that bias was statistically insignificant. So they repeated a bunch of anecdotes in the story and left that part of the analysis out. Reporting null results won't get you cited by the NYT, I guess. https://www.chrisstucchio.com/blog/2016/propublica_is_lying.... The power of the…

the scores are dependent. It's talking about a subset of the data compared to the entire set, rather than a similar subset or random set. The term unlabeled Random_Race is the same as Random_Race:score_factorHigh+score_factorMedium, as opposed to each one individually. So while neither high nor medium alone have statistical significance for African Americans, together they do, a statistical puzzle.

Or rather, if you had also copied line 44, less of a puzzle, since `score_factorWhatever` becomes significant in a race specific model. It isn't race alone nor the score alone. It is something else (age? another not modeled thing?)

They say so in this link, https://www.propublica.org/article/how-we-analyzed-the-compa... Where they explain a bit more in detail what the chart labels mean than what they are labeled in the R script.

Score == dependent variable. So why you ran your blog comments as Score == potential independent variable is a little strange.

As for why you want to critique the very last chart (which does appear in 36, and does as a big chart not to work at all)

Who cares?

Overall, every other time, if we look at a Pearsons fit (line 51)

All defendants Low High Survived 2681 1282 0.55 Recidivated 1216 2035 0.45 Total: 7214.00 False positive rate: 32.35 False negative rate: 37.40 Specificity: 0.68 Sensitivity: 0.63 Prevalence: 0.45 PPV: 0.61 NPV: 0.69 LR+: 1.94 LR-: 0.55

Why the hell would we use this for sentencing guidelines? It isn't very specific, nor sensitive. It has a fairly high false positive and false negative rate.

When you jail someone, you take away that person's rights and you are probably as much as not going to jail them again. This sentencing guideline basically disguises that, and does it in such a way where it isn't specific nor sensitive, and to boot, 1/3 of the time you'll be wrong in your decision. Furthermore, you'll already know in your gut which 1/3 it is going to be - probably someone young or black.

Propublica's writers are totally justified to write the article. They go further than many journalists and show you what they did, and there is no rule in the 4th estate that says they have to do that. If you don't like the fact that statistics as a subject, and policies dependent on statistics, for most people, have to be framed with a story, that's a different issue altogether. But why not come out and just say that.

Re: Make Algorithms Accountable

#29
I think there are elements to complicated tags in complicated algorithms that people need to see and understand. All the details - nah. I don't know all the details that go into the math of my credit report. I do know I have the right and responsibility to see what debts and savings that are reported.

I do think the author is right - issues that can affect someone's rights and responsibilities that are being embedded in an algorithms are part of the public trust and should be examined a bit more closely by the public. Do I or anyone else need to see all the details - no. Do I need to understand some basics and understand some of the tagging. Yes.

This is what helps uphold a free society.

Re: Make Algorithms Accountable

#30
post #7

Earlier quoted context omitted.

Yes, this was a viable solution back in the day because there was a 90% chance (made up number, but you get the idea) that denying someone from a redlined district was a good financial choice, and it was too expensive to do a detailed analysis to determine if an applicant was in the other 10%. With the automated credit checking and statistical analysis available these days, this isn't really an issue anymore. Banks c…

> Yes, this was a viable solution back in the day because there was a 90% chance (made up number, but you get the idea) that denying someone from a redlined district was a good financial choice, No That wasn't the reason why redlining existed. It existed because it was explicitly racist policy enabled directly from the National Housing Act of 1934[0] -- which was basically just codifying the existing racist attitudes…

Your first link indicates that, as I said, the purpose of redlining was to direct wise economic decisions. Some researched (linked from wikipedia) suggests that the data may have been biased against black neighborhoods due to bias of the appraisers. It does not suggest that the purpose was to specifically screw over black people.
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