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

Unfortunately, no detail on the actual algorithm in question. Is it executed manually or is it using a statistical model optimized for some tradeoff of metrics?

The most encouraging thing about this approach is the change to a data-driven systematic approach from the previous “whatever the judge thinks by looking at you” approach. It really doesn’t matter if the algorithm is completely correct, as once you make the conceptual change to using such a system, you can tune the parameters to fix any problems that arise.

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 we transfer our biases into the algorithms and ML solutions that we build. Given the move towards using algorithms for making decisions like this, it's something we should definitely consider.

If you have the time, definitely listen to this episode. It's an amazing podcast, but this one episode really hit me about how software can affect peoples lives – and not always for the better. How we as software engineers should be more aware of how the solutions we build will be used down-the-line.

tl;dr of the episode would be:

ML solutions, and algorithms designed by humans, are designed by looking at historic data. Historically, a number of races have not been treated fairly when it comes to the justice system, e.g. black people being treated harshly for the same crime as non-black people.

When our ML solutions are built on historical data, it learns those biases as well. Which means that the "racism" is also built into the algorithm as well. Of course the algorithm doesn't have any concept of racism, it's just another feature it uses to compute it's decision. But it is something we as designers of algorithms should keep in mind.

[1] https://youarenotsosmart.com/2017/11/20/yanss-115-how-we-tra...

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 loan, features such as ZIP code or race could encode discrimination into the model

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 waiting for their help to enforce the court's order, but before the police arrived I irritated one of the security guards and they all attacked me. I was charged with 'misdemeanor assault' and was released on my own recognizance after a night at the city jail.

Two months later I got the police report, and learned what I'd allegedly done. 9 months later I learned the "old man" security guard that freaked out on me was a retired police officer. He knew exactly what to say to the responding officer to cover his ass, and was well-practiced at testifying on the stand. It's easy to make shit up if you know what you're doing. His co-conspirator was kind of a doofus - he'd been a hospital security guard for 20+ years.

Two months after my trial, my girlfriend got arrested - her court-ordered mental health professionals didn't think her substance use was of any concern to them, and were heroically treating her presenting systems without any concern as to their cause. While I was arrested for assault (misdemeanor/victim), she was arrested for heroin possession (felony/victimless). Her bail was $5000. The various bail bondsmen I called weren't interested, or wanted more collateral than I had - apparently people arrested for drug charges have a tendency to not show up for their court dates. She spent 2 weeks in jail while her attorney negotiated with the justice system on her behalf.

(The system she was arrested into has since made some efforts to keep people out of the jails, or to reduce bails, but I don't know how these changes would've affected her experience...)

In a separate anecdote, my ex-wife recently picked a fight with her then-boyfriend (California). He responded to her provocation by escalating the fight into a very physical confrontation. Bystanders called the police, he got arrested... Bond was set for $50,000. He bailed himself out by charging $5,000 to his credit card with a bail bondsman. The charges were dropped a few days later. The bondsman apparently got to keep all $5,000 (edit: I think the term 'racket' applies).

I don't know that an algorithmic approach to justice will be much help at this stage, because the system is so corrupt. Any algorithm will have to start with "Is there an actual victim [0]? No: release without bond. Yes: [...]". I don't think the system will take well to considering that they've spent decades making work for themselves...

[0] I learned about 'strict liability' from a HN comment - thanks, whoever that was. https://en.wikipedia.org/wiki/Strict_liability