In speeches praising intelligence-driven prosecution, Vance often cites the case of a 270-pound scam artist named Naim Jabbar, who for more than a decade made a living in the Times Square area bumping into pedestrians and then demanding money, saying they had broken his glasses. Convicted 19 times on the misdemeanor charge of “fraudulent accosting,” Jabbar never served more than five months in jail until he was flagged by the C.S.U. His next arrest, in July 2010, triggered an alert. Instead of being offered a plea bargain, he was indicted and subsequently convicted on a felony robbery charge, and sentenced to three and a half to seven years in prison. With time served before his conviction, he was soon paroled and then arrested again, in July 2014, for another broken-eyeglasses incident and charged with robbery and grand larceny. (NYTIMES, 2014)This is the simple genius of data driven decision making - learning to do more with less. If there are 10 bad guys, but 1 of them is a really bad guy - go after him first. After enough time, the repeat offenders are gone, locked up - and your resources are freed up a bit to deal with the real issues. Word spreads that it's more likely for repeat offenders to face real jail time and that acts as a disincentive to bad behavior. As Karen Friendman Agnifilo states in the article, "There’s a reason murders in Manhattan went from 70 in 2010 to 29 so far this year. We figured out who are the people driving crime in Manhattan, and for four years we focused on taking them out.
Big Data 1, Bad Guys 0!
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