The Army now uses an algorithm to predict and 'intercept' violent offenders. Will your 'behavioral record' follow you in civilian life?

The [Army] researchers drew on 38 databases containing information on 446 variables for each soldier who served between 2004 and 2009. During that period, 5,771 soldiers committed murder, manslaughter, kidnapping, robbery or other violent felonies. (Domestic violence and sex crimes were not included in the study because research suggests that they follow risk patterns that are distinct from other types of offenses.)
Using a technique known as machine learning, researchers looked for patterns among the violent offenders and used what they found to create a risk model that took account of their demographic characteristics, health histories, career details and other factors predating their crimes.
For men, who accounted for the vast majority of both soldiers and offenders, 24 factors were found to be at play. Those most at risk were young, poor, ethnic minorities with low ranks, disciplinary trouble, a suicide attempt and a recent demotion, according to a report published Tuesday in the journal Psychological Medicine.
The highest-risk group — just 5% of the total population of male soldiers — accounted for 36% of the crimes perpetrated by men, the researchers found. Each year, on average, 15 of every 1,000 of those men committed a violent offense. That was more than seven times the overall rate for male soldiers.
The highest-risk female soldiers were responsible for 33% of crimes perpetrated by women, who overall were about half as likely as men to commit violent offenses.
http://www.latimes.com/science/sciencenow/la-sci-sn-predicting-violent-crime-by-army-soldiers-20151006-story.html