Should We Use Big Data To Punish Crimes Before They're Committed

Should We Use Big Data To Punish Crimes Before They're Committed


Should We Use Big Data To Punish Crimes Before They're Committed

John Anderton is the chief of a special police unit in Washington, D.C. This particular morning, he bursts into a suburban house moments before Howard Marks, in a state of frenzied rage, is about to plunge a pair of scissors into the torso of his wife, whom he found in bed with another man. For Anderton, it is just another day preventing capital crimes. “By mandate of the District of Columbia Precrime Division,” he recites, “I’m placing you under arrest for the future murder of Sarah Marks, that was to take place today....”
Other cops start restraining Marks, who screams, “I did not do anything!” The opening scene of the film Minority Report depicts a society in which predictions seem so accurate that the police arrest individuals for crimes before they are committed. People are imprisoned not for what they did, but for what they are foreseen to do, even though they never actually commit the crime. The movie attributes this prescient and preemptive law enforcement to the visions of three clairvoyants, not to data analysis. But the unsettling future Minority Report portrays is one that unchecked big-data analysis threatens to bring about, in which judgments of culpability are based on individualized predictions of future behavior.
Of course, big data is on track to bring countless benefits to society. It will be a cornerstone for improving everything from healthcare to education. We will count on it to address global challenges, be it climate change or poverty. And that is to say nothing about how business can tap big data, and the gains for our economies. The benefits are just as outsized as the datasets. Yet we need to be conscious of the dark side of big data too. Read the full article here: http://www.popsci.com/science/article/2013-03/should-we-use-big-data-to-punish-crimes-before-theyre-committed?single-page-view=true

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