There’s new software that can predict who is likely to become a murderer.
Using probation department cases entered into the system between 2002 and 2004, Berk and his colleagues performed a two-year follow-up study—enough time, they theorized, for a person to reoffend if he was going to. They tracked each individual, with particular attention to the people who went on to kill. That created the model. What remains at this stage is to find a way to marry the software to the probation department’s information technology system.
When caseworkers begin applying the model next year they will input data about their individual cases – what Berk calls “dropping ‘Joe’ down the model”—to come up with scores that will allow the caseworkers to assign the most intense supervision to the riskiest cases.
Even a crime as serious as aggravated assault—pistol whipping, for example—”might not mean that much” if the first-time offender is 30, but it is an “alarming indicator” in a first-time offender who is 18, Berk said.
The model was built using adult probation data stripped of personal identifying information for confidentiality. Berk thinks it could be an even more powerful diagnostic tool if he could have access to similarly anonymous juvenile records.
The central public policy question in all of this is a resource allocation problem. With not enough resources to go around, overloaded case workers have to cull their cases to find the ones in most urgent need of attention—the so-called true positives, as epidemiologists say.
But before that can begin in earnest, the public has to decide how many false positives it can afford in order to head off future killers, and how many false negatives (seemingly nonviolent people who nevertheless go on to kill) it is willing to risk to narrow the false positive pool.
Pretty scary stuff, as it gets into the realm of thoughtcrime.