New Jersey’s experiment to reduce the number of people in jail awaiting trial • Hacker News Board

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#21

Post by adekok » Mon, Nov 27, 2017, 1:46 PM UTC

skybrian wrote: post #20

adekok wrote: post #19

Earlier quoted context omitted.

All of which are strongly correlated with factors open to bias. http://www.cnn.com/2017/03/07/politics/blacks-wrongful-convi... https://www.law.umich.edu/newsandinfo/features/Pages/starr_g... While people complain about the racial bias in the courtroom, the sex bias is substantially larger. Heck, the Supreme Court of Canada recently gave a woman a complete pass for trying to have her husband killed. Because after she…

That may be so, but none of these links are about bias in setting bail.

The comment I responded to discussed how bail was set based on prior events. My comment showed how those prior events were substantially biased.

Therefore, by a simple and clear chain of logic, setting bail based on prior events is also biased.

An alternate answer would be: do you really think that there is bias everywhere ELSE in the system, but not in bail?

Of course not.

And, if you look, you find papers like this:

https://link.springer.com/article/10.1007/BF02885913

We found that judges take gender, but not race, into account in determining the amount of bail for certain types of cases; more specifically, Black females faced lower bail than Black males in less serious cases. In contrast, we found that both race and gender affected the likelihood of pretrial release. White defendants were more likely than black defendants to be released pending trial and females were more likely than males to be released prior to trial. In fact, white females, white males, and black females all were more likely than black males to be released.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#22

Post by jnty » Mon, Nov 27, 2017, 1:51 PM UTC

AnthonyMouse wrote: post #9

asadjb wrote: post #6

It's better to move towards a more open and transparent system that's data driven. However if the system used here will be transparent isn't clear, only that it can be. The builders of these systems can choose not to share the algorithms behind it. A podcast I listened to a day or two ago [1]; You Are Not So Smart, discussed something related to this that I feel is important to point out here as well. It's about how…

> When our ML solutions are built on historical data, it learns those biases as well. It's actually worse than that, because the algorithm is giving you the correct result. For example, suppose that black men are more likely to fail to appear in part because they have worse, less flexible jobs because of racist hiring practices. That isn't fair, but it's still true that they're more likely to fail to appear. Are we s…

This is a dangerous misunderstanding.

The issue comes when features correlated with race are used to make inferences. This can occur in complex ways but a simple example, used elsewhere on this thread, is zip code. It might be that people from a mainly black area are more likely to exhibit whatever negative behaviour the model is looking for than a mainly white area, perhaps for the reasons you mention. What then happens is two otherwise identical people in the model are treated differently based on race.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#23

Post by avs733 » Mon, Nov 27, 2017, 1:54 PM UTC

Some of the most interesting and thorough public work on just how problematic these algorithms are was done by ProPublica[0]. They have a series of articles specifically focused on how machine learning/algorithms can either enable or create racist outcomes[1] that are all worth reading.

[0] https://www.propublica.org/article/machine-bias-risk-assessm... [1] https://www.propublica.org/article/breaking-the-black-box-ho...

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#24

Post by mholmes680 » Mon, Nov 27, 2017, 2:07 PM UTC

Some anecdotal outcomes [0], [1], [2] of the system below. In general, people were outraged for a few months and local news seemed to mention it in most drug-bust stories, but that seems to have died off. My law enforcement friends were beside themselves at first, but I think both sides are adjusting to the system.

I think in general I agree with it. Without context of witnessing the [alleged] crime and without the algorithm in front of me, sometimes I wonder if certain situations have exposed some holes in the algorithm. In addition to the three cited below, I remember reading about a guy in Ocean County being released after they found him with $1M of drugs... maybe his supplier took care of that problem for the community...

[0] - Burglary: http://pix11.com/2017/02/16/accused-serial-burglar-arrested-...

[1] - 1st deg murder: http://www.gloucestercitynews.net/clearysnotebook/2017/07/li...

[2] - possession and resisting arrest, but look at the 2016/2017 rap sheet: http://www.usbailreform.com/camden-nj-ex-con-shoots-cop-poin...

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#25

Post by azernik » Mon, Nov 27, 2017, 2:08 PM UTC

maxerickson wrote: post #18

opportune wrote: post #8

Earlier quoted context omitted.

Another problem in the same vein is that when ML algorithms make use of Bayesian inference they can bake in correlations ( e.g. between race and credit score) that we would normally purposefully avoid using as a factor, because while it enhances predictive power, it again codifies our existing biases, prejudices, and injustices. For example if you were deploying an ML model to determine whether someone deserved a loa…

Including race as a parameter should reduce the impact of those correlations on the output of the model (by allowing the model to measure and control for the bias that exists in the input data). Incautiously using race just because it reflects those existing biases would be a problem. This is what lots of humans do, overestimating the information provided by their own inferences of race. Like internet assholes who bl…

That's actually a very interesting idea for a technique. But not one I've ever heard of actually being used.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#26

Post by grafporno » Mon, Nov 27, 2017, 2:20 PM UTC

jnty wrote: post #22

AnthonyMouse wrote: post #9

Earlier quoted context omitted.

> When our ML solutions are built on historical data, it learns those biases as well. It's actually worse than that, because the algorithm is giving you the correct result. For example, suppose that black men are more likely to fail to appear in part because they have worse, less flexible jobs because of racist hiring practices. That isn't fair, but it's still true that they're more likely to fail to appear. Are we s…

This is a dangerous misunderstanding. The issue comes when features correlated with race are used to make inferences. This can occur in complex ways but a simple example, used elsewhere on this thread, is zip code. It might be that people from a mainly black area are more likely to exhibit whatever negative behaviour the model is looking for than a mainly white area, perhaps for the reasons you mention. What then hap…

Yes, the algorithm may be correct, but garbage in, garbage out still applies, bcause of biases.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#27

Post by skybrian » Mon, Nov 27, 2017, 2:42 PM UTC

adekok wrote: post #21

skybrian wrote: post #20

Earlier quoted context omitted.

That may be so, but none of these links are about bias in setting bail.

The comment I responded to discussed how bail was set based on prior events. My comment showed how those prior events were substantially biased. Therefore, by a simple and clear chain of logic, setting bail based on prior events is also biased. An alternate answer would be: do you really think that there is bias everywhere ELSE in the system, but not in bail? Of course not. And, if you look, you find papers like this…

Okay, I think I see what you mean now. It's a bit hard to see since you're so focused on gender bias.

I think you're right that these factors, while answering fairly objective questions, reinforce bias due to things like prior convictions. Once someone starts down this path, they get treated worse by the system based on history. Even though they did their time, they aren't starting fresh.

Still, I think it's an improvement (to a very flawed system) because it's not adding new bias. It also doesn't seem practical to reexamine previous convictions to see if they were fair when setting bail.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#28

Post by skybrian » Mon, Nov 27, 2017, 2:52 PM UTC

avs733 wrote: post #23

Some of the most interesting and thorough public work on just how problematic these algorithms are was done by ProPublica[0]. They have a series of articles specifically focused on how machine learning/algorithms can either enable or create racist outcomes[1] that are all worth reading. [0] https://www.propublica.org/article/machine-bias-risk-assessm... [1] https://www.propublica.org/article/breaking-the-black-box-ho…

These are interesting links, but off topic because there's no machine learning involved.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#29

Post by maxerickson » Mon, Nov 27, 2017, 2:53 PM UTC

azernik wrote: post #25

maxerickson wrote: post #18

Earlier quoted context omitted.

Including race as a parameter should reduce the impact of those correlations on the output of the model (by allowing the model to measure and control for the bias that exists in the input data). Incautiously using race just because it reflects those existing biases would be a problem. This is what lots of humans do, overestimating the information provided by their own inferences of race. Like internet assholes who bl…

That's actually a very interesting idea for a technique. But not one I've ever heard of actually being used.

It's not a technique, it's a natural outcome of statistical modeling.

It doesn't get used because people are innumerate and reactionary.

Re: New Jersey’s experiment to reduce the number of people in jail awaiting trial

#30

Post by GVIrish » Mon, Nov 27, 2017, 3:27 PM UTC

tomohawk wrote: post #12

Once they reduce the jail population, what's next? Likely, cuts in the number of jail cells. Seems like a good thing, but will this make it less likely for police to arrest people in the first place, potentially making the streets less safe? This article talks about the effect in the UK: http://www.telegraph.co.uk/news/2017/11/24/police-reluctant-...

If a series of stupid policy decisions are made that constricts jail cell supply so much that even dangerous suspects are not detained, then yeah.

But there is a lot of social benefit to not having people sit in jail awaiting trial if they don't need to. People on limited income can't afford to miss work or not be around to take care of their kids or other love ones. People who turn out to be innocent still end up experiencing difficult life consequences as a result of unnecessary jail time.

I think the public interest is served by reducing the number of people in jail in a more fair and transparent manner. It will take sensible policy-making to make sure that it doesn't result in unintended consequences (as some others have pointed out) down the road, but it's worth starting down the road in the first place.