

Misfortune teller: predicting criminal recidivism - skmurphy
http://www.theatlantic.com/magazine/archive/2012/01/misfortune-teller/8846/

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skmurphy
"Drawing from criminal databases dating to the 1960s, Berk initially modeled
the Philadelphia algorithm on more than 100,000 old cases, relying on three
dozen predictors, including the perpetrator’s age, gender, neighborhood, and
number of prior crimes. To develop an algorithm that forecasts a particular
outcome—someone committing murder, for example—Berk applied a subset of the
data to train the computer on which qualities are associated with that
outcome.

[...]

Philadelphia’s parole officers were surprised to learn, for example, that the
crime for which an offender was sentenced—whether it was murder or simple drug
possession—does not predict whether he or she will commit a violent crime in
the future. Far more predictive is the age at which he (yes, gender matters)
committed his first crime, and the amount of time between other offenses and
the latest one—the earlier the first crime and the more recent the last, the
greater the chance for another offense."

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DarkShikari
Correlation might be useful, but how about causation?

The most likely "cause" of criminal recidivism is sending millions of people
to prison for minor crimes, where they spend months learning from other
criminals, and then are released, upon which they find it impossible to find a
job (because they're marked as a felon) and are forced to return to crime.

