
AI is sending people to jail and getting it wrong - TheAuditor
https://technologyreview.com/s/612775/algorithms-criminal-justice-ai
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bko
> So if you feed it historical crime data, it will pick out the patterns
> associated with crime. But those patterns are statistical
> correlations—nowhere near the same as causations. If an algorithm found, for
> example, that low income was correlated with high recidivism, it would leave
> you none the wiser about whether low income actually caused crime. But this
> is precisely what risk assessment tools do: they turn correlative insights
> into causal scoring mechanisms.

My main problem with this sort or argument is that it compares an algorithm to
some ideal. As though a judge has some infallible insight from carefully
studying empirical results for recidivism.

In regards to correlation vs causation, they're important when trying to
prescribe solutions. For instance, suppose that higher rates of recidivism are
caused by growing up in an abusive household. And having a violent parent also
causes a lower income. Correlation vs causation is important when trying to
remedy the problem. Giving the family money will not solve the underlying
problem, just a side effect. Solving the side effect may still be worth it
though. But if you're determining rates of recidivism, it would be better to
look at the underlying cause (did you grow up in a violent household) rather
than a side effect (poverty), but they would both lead to the same final
recidivism score. And you can still reject both under the premise that the
past that's out of your control should not be considered.

But even if you are set on only using the cause, statistical methods are more
likely to find these results. And you can easily control what input is
provided. You can tell a judge to ignore certain characteristics, but her
actual reasoning process is likely opaque.

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pmontra
The site is down now, cached copy at

[https://webcache.googleusercontent.com/search?q=cache:EqbA9Y...](https://webcache.googleusercontent.com/search?q=cache:EqbA9YswYUwJ:https://www.technologyreview.com/s/612775/algorithms-
criminal-justice-ai/)

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carl-erwin
wrong link missing www in url.

[https://www.technologyreview.com/s/612775/algorithms-
crimina...](https://www.technologyreview.com/s/612775/algorithms-criminal-
justice-ai/)

~~~
pmontra
Wow, somebody still doesn't handle both the www and the bare domain name URLs.
I didn't think about it. Thanks.

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0db532a0
Articles I read about the failings of AI can generally be summarised as
follows: Someone made a shitty statistical analysis and found out that the
result was shitty when the shitty model was run on a perfectly adequate
computer with shitty data. In other acronyms: SISO and also GIGO.

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dczx
The first concern is the vanishing/exploding gradient issue within neural
network based models and the inherent bias.

But greater is the propensity for abuse, the algorithm that determines the
risk model isn't publicly accessible.

Once we get to a point where an AI controls sentencing, it could be
manipulated. The idea that an AI get's to determine which humans go to jail is
the last thing we should ever utilize AI for.

A more important issue would be to focus on prison reform, let's reduce the
causation of crime. Unfortunately private prisons are expanding right now and
there's no reason to assume the prison lobby wouldn't love to influence an
algorithm designed to send more people to jail.

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kstenerud
The problem is far more fundamental. America operates under the premise that
crime is a moral failing, and that reducing crime is mostly a matter of strong
enough deterrents.

The underlying assumption that logically follows this thinking is that
criminals are by choice beyond redemption (essentially enemies of society),
and so your best course of action is separating them from the rest of the
population. What happens after that is not your concern: out of sight, out of
mind.

This mindset is readily apparent in the almost complete lack of societal
reintegration services, and the casual use of isolation, despite the ample
evidence of how much damage this does.

