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Reforming the data-driven justice system

February 19, 2015

This article from the New York Times really interests me. It’s entitled Unlikely Cause Unites the Left and the Right: Justice Reformand although it doesn’t specifically mention “data driven” approaches in justice reform, it describes “emerging proposals to reduce prison populations, overhaul sentencing, reduce recidivism and take on similar initiatives.”

I think this sentence, especially the reference to reducing recidivism, is code for the evidence-based sentencing that my friend Luis Daniel recently posted about. I recently finished a draft chapter in my book about such “big data” models, and after much research I can assure you that this stuff runs the gamut between putting poor people away for longer because they’re poor and actually focusing resources where they’re needed.

The idea that there’s a coalition that’s taking this on that includes both Koch Industries and the ACLU is fascinating and bizarre and – if I may exhibit a rare moment of optimism – hopeful. In particular I’m desperately hoping they have involved people who understand enough about modeling not to assume that the results of models are “objective”.

There are, in fact, lots of ways to set up data-gathering and usage in the justice system to actively fight against unfairness and unreasonably long incarcerations, rather than to simply codify such practices. I hope some of that conversation happens soon.

Categories: data science, modeling
  1. February 19, 2015 at 9:42 am

    Reblogged this on Destroyer of Exoplanets and commented:
    Optimism is a crutch for those who can’t handle the crushing weight of reality. And by that I mean, I really hope some good comes of this.

    Like

  2. darioperalta
    February 20, 2015 at 3:08 am

    If the models built and the data used to build them are open to the public then this may help highlight unfairness precisely because it could encode it.

    Like

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