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

economist.com

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

#31
post #21

Earlier quoted context omitted.

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 impro…

> Okay, I think I see what you mean now. It's a bit hard to see

I must admit to not understanding how it's difficult to see the correlation. If bail is set on factors X, Y, and Z, AND those factors are shown to be biased, then by definition, bail is also biased.

> since you're so focused on gender bias.

That's just a weird statement to make. The research shows bias and I quoted the research... how does that make me "so focused" on gender bias?

> it's not adding new bias.

That is a good point, but continuing existing bias is a serious problem.

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

#32
post #17

This isn't an "algorithm" the way people here are thinking. It is a risk formula. The thing it does is standardize which risk factors have been shown to be important. The inputs are: Age at current arrest Current violent offense Current violent offense & 20 years old or younger Pending charge at the time of the offense Prior misdemeanor conviction Prior felony conviction Prior conviction (misdemeanor or felony) Prior…

Thanks for the clarification. I wish journalists wrote like this :)

Whether or not we want to call this an “algorithm,” it is a step en route to a probability based decision making machine. Not a bad example to frame discussions around.

The obvious plus-side is that if it works (sounds pretty plausible), this scoring system could help optimise jail time and its costs against the societal costs of re-offense. If it takes pressure of the justice system and reduces wait times, it could improve suspects’ civil and republican rights. The right to a timely trial, habeas corpus..

The downsides are a little foggier, and depend more on where this goes and what kinds of patterns emerge. In this simple scenario, there’s not a lot of data here and few obvious opportunities for bias or some other injustice. Doesn’t sound too bad.

..except age. If people your age reoffend more often, it doesn’t seem fair or just that you are effectively implicated for their wrongdoing. Does it?

As this system gets bigger it will want more data, for improved accuracy. Race, gender & political affiliation are obvious nonos. We can’t discriminate on those grounds. How about arrest location, home address, income in the previous year, marital status and level of education? Rent or own? Have a dog? File tax? This starts sounding like an insurance quote.

If we go down a more google/facebook/ML route, we can probably eliminate any data points that raise specific objections. With enough data, we can find proxies for anything. More specifically, our black boxes will find proxies for anything.

From a blind justice perspective, I think it’s all the same problem regardless. We are being implicated by affiliation, a statistical affiliation. That’s not blind.

I think there you have the core issue. It’s present in a pen-and-paper scoring system. It’ll be present in a Google CrimeRank algorithm.

We’ve gotten very used to talking about bias in nonspecific terms, with a lot of emphasis on chauvinist bias. But, we’re bias machines. That’s what judges are, to a large extent. Not all bias is irrational, bigoted or chauvinist. Do we really want to eliminate only rational bias, or is bias a problem for reasons other than that?

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

#33
post #10

I got arrested 26 months ago. I'd gone back to the hospital with a court order that said the hospital's behavior was not in compliance with the law, and that they had to let their patient (my friend) go. I made the mistake of going without a police escort. The ER staff didn't know that their employer actually had no legal authority to hold their patient in their psychiatric ward. I called the police and was patiently…

You lead an interesting life. Your comment reminded me how curious it is that some people tend to have regular (yearly-ish?) clashes with police and the criminal justice system, and others go their entire life without anything more than a "Good morning" with a cop.

Well. There are factors that increase your risk of dealing with cops: 1) being non white (or, not the same skin color/ethnical background as the majority population) 2) being in any way "non-conforming to mainstream" - e.g. wearing dreads, "gangsta clothing", looking like a punk or basically anything that makes you stand out.

Cops always go for those looking different than the mass when they're bored.

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

#34
post #22

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…

> The issue comes when features correlated with race are used to make inferences.

Practically all features are correlated with race. Income, culture, religion, education, proximity to gangs, parental involvement, etc. etc. And many factors cause other factors, which then also correlate.

The difference between zip code as a mechanism for Bayesian inference and redlining is that redlining is disproportionate. Redlining doesn't adjust probabilities in response to data, it just outright bans anyone in a neighborhood, which overcompensates. It makes inaccurate predictions to the detriment of the people in that neighborhood, because some of the people there have mitigating factors that overcome the negatives of living there, and it doesn't take that into account. An algorithm that considers all available data does.

You still have to address the things that cause trouble for the people in that neighborhood, but those are separate problems. You have to fix them, not pretend they don't exist.

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

#35

Earlier quoted context omitted.

You lead an interesting life. Your comment reminded me how curious it is that some people tend to have regular (yearly-ish?) clashes with police and the criminal justice system, and others go their entire life without anything more than a "Good morning" with a cop.

Well. There are factors that increase your risk of dealing with cops: 1) being non white (or, not the same skin color/ethnical background as the majority population) 2) being in any way "non-conforming to mainstream" - e.g. wearing dreads, "gangsta clothing", looking like a punk or basically anything that makes you stand out. Cops always go for those looking different than the mass when they're bored.

The longer your history the more the cops will treat you like a criminal during even the most trivial interactions. Due to the large amount of discretion they have the more scrutiny you get the more likely you are to wind up with a lengthier criminal history.

Old men who have an (irrelevant) DUI from the '70s on their history get asked if they've been drinking when they roll a 4-way stop on their way to church on Sunday morning.

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

#36
post #10

I got arrested 26 months ago. I'd gone back to the hospital with a court order that said the hospital's behavior was not in compliance with the law, and that they had to let their patient (my friend) go. I made the mistake of going without a police escort. The ER staff didn't know that their employer actually had no legal authority to hold their patient in their psychiatric ward. I called the police and was patiently…

You lead an interesting life. Your comment reminded me how curious it is that some people tend to have regular (yearly-ish?) clashes with police and the criminal justice system, and others go their entire life without anything more than a "Good morning" with a cop.

The police officer who arrested me was almost apologetic: it was 6 of them against me, and he had to do something.

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

#37
post #25

Earlier quoted context omitted.

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.

The technique I'm referring to is including race as a factor, and then instructing your model to disregard that factor. Not being race-blind, but being race-aware while attempting to be neutral to race.

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

#38
post #37

Earlier quoted context omitted.

It's not a technique, it's a natural outcome of statistical modeling. It doesn't get used because people are innumerate and reactionary.

The technique I'm referring to is including race as a factor, and then instructing your model to disregard that factor. Not being race-blind, but being race-aware while attempting to be neutral to race.

Yeah I think this is an interesting idea but I don't actually understand how the great-grandparent comment believes that this could be done. I don't think it works in a strict Bayesian sense. You would have to go out of your way to instruct your model to operate correctively

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

#39
post #21

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…

I cannot read the paper there - How is "judges take gender, but not race, into account in determining the amount of bail" determined? Purely from correlation between bail amounts and above factors?
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