One really easy way to reduce the American penitentiary population would be to decriminalize drugs except for instancess in which someone has sold them to minors. Legalize the less-dangerous ones (marijuana) and sentence pushers to workfare and users to out-patient rehab and education for harder ones (heroin).

Even if that unlikely scenario were to play out, the prisons would still be too crowded and parole would remain a problem. If incarceration is meant to keep offenders from recommiting crimes and not merely as a punitive measure, how do we know which convicts to release and when? Parole has long been an inexact science, but perhaps Big Data can help. Perhaps. An excerpt from the Economist:

“Help may be at hand, in the form of ‘risk-assessment’ software, which crunches data to estimate the likelihood a prisoner will re-offend. Such software tends to increase the proportion of applicants who are granted parole while also reducing the proportion who re-offend. Two such programmes, LSI-R and LS/CMI, appear to reduce parolee recidivism by about 15%. Developed by Multi-Health Systems, a Canadian firm, they were used to assess 775,000 parole applications in America in 2012. Four-fifths of parole boards now use similar technology, says Joan Petersilia of Stanford University.

The data that matter include the prisoner’s age at first arrest, his education, the nature of his crime, his behaviour in prison, his friends’ criminal records, the results of psychometric tests and even the sobriety of his mother while he was in the womb. The software estimates the probability that an inmate will relapse by comparing his profile with many others. The American version of LS/CMI, for example, holds data on 135,000 (and counting) parolees.

It is better to be guided by software than one’s gut, says Olivia Craven, head of the Idaho Commission of Pardons and Parole. Donna Sytek of the New Hampshire Parole Board agrees. Unaided, parole board members rely too much on their personal experiences and make inconsistent decisions, she says.“