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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

#11

Post by pdkl95 »

tcj_phx wrote: 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…

> He knew exactly what to say to the responding officer to cover his ass

Replacing human judgment with algorithms is a terrible idea for many reasons, but this might be the worst. Algorithms are deterministic, and thus they can be manipulated. "SEO" services exist in spite of Google's efforts to protect their ranking algorithm. Does anybody seriously believe their local government will be more successful than Google at preventing people (i.e. police, prosecutors, etc) from "optimizing" their input to the algorithm?

edit - justification for the claim that a bail algorithm would be easy to manipulate:

The recent single-pixel attack[1] against image classifiers. https://arxiv.org/abs/1710.08864

Google's failure to recognize obviously inapropriate videos in their "youtube kids" app ("elsagate") https://medium.com/@jamesbridle/something-is-wrong-on-the-in... (a good summary & discussion https://www.youtube.com/watch?v=LKp2gikIkD8 )

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

#12

Post by tomohawk »

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-...

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

#13

Post by CoongLiu »

opportune wrote: post #8
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…

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…

By definition, any model is basically bound to be discriminatory. Taking data, extracting common key features, and discarding the rest is essentially generalisation.

But the model is amoral. It's (morally) neither good nor bad for utilising certain features.

If it turned out that race was the most accurate attribute for a particular situation, it would be nonsensical ignore it.

The current trend of trying to paper over biases, while generally born of noble sentiment, probably only perpetuates the problem. Because it's usually done far down stream, and doesn't necessitate change at the source. Functionally, it's like a cover up by a large corporation

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

#14

Post by pjc50 »

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-...

That situation in the UK is simply due to under-funding.

The article points out that the current US situation uses economic status as a reason for keeping people in jail, more so than actual risk to the public. Resulting in huge over-use and (as pointed out) going to jail even briefly increases re-offending risk.

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

#15

Post by Simon_says »

tcj_phx wrote: 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.

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

#16

Post by ufo »

CoongLiu wrote: post #13
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…

By definition, any model is basically bound to be discriminatory. Taking data, extracting common key features, and discarding the rest is essentially generalisation. But the model is amoral. It's (morally) neither good nor bad for utilising certain features. If it turned out that race was the most accurate attribute for a particular situation, it would be nonsensical ignore it. The current trend of trying to paper ov…

> If it turned out that race was the most accurate attribute for a particular situation, it would be nonsensical ignore it.

Only if you are optimizing for prediction accuracy. If you want to optimize for something like "justice" or "citizen wellbeing" then you might want to come to a different conclusion

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

#17

Post by dzdt »

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 violent conviction 
  Prior failure to appear in the past two years 
  Prior failure to appear older than two years 
  Prior sentence to incarceration
Each input is given a simple 0-2 integer importance weighting. Scores are summed, then rescaled by a translation table.

Outputs are a 1-6 "fail to appear" risk score, a 1-6 "new criminal activity" risk score, and a yes/no "new violent criminal activity" risk flag.

What to do with the scores (and any other factors to consider) is still left up to the judge. The advantage is in translating "does this defendent have a record?" into a numerical risk score in an evidence-based way.

[1] http://www.arnoldfoundation.org/wp-content/uploads/PSA-Risk-...

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

#18

Post by maxerickson »

opportune wrote: post #8
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…

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 blather about how it is rational to be afraid of black men because of their higher rates of assault. Never mind that the absolute rate is still so low that there is ~0 predictive power from the race of a given individual.

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

#19

Post by adekok »

dzdt wrote: 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…

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 was charged with attempted murder, she conveniently remembered that she was the victim of domestic violence.

Despite her claims being provably false.

i.e. claimed incidents occurred when they lived hundreds of miles apart. There's no record of her ever calling the police, despite her claims of multiple police visits, etc.

https://www.youtube.com/watch?v=yq2WWsY8Rmc

As was noted in other comments here, such a "data driven" approach just continues existing prejudices.

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

#20

Post by skybrian »

adekok wrote: post #19
dzdt wrote: 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…

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.
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