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This talk will examine the current big data programs utilized by governments and police departments around the world and discuss how they factor into individualized suspicion of persons. Can big data sets with the proper algorithm effectively predict who will commit a crime? What are the appropriate margins of error (if any at all)? I will discuss the use of algorithms on big data sets to predict both where crime will occur and who might commit it.
Additionally, I will discuss the types of data that exists in these databases and compare several different ways in which computer algorithms are used on big data sets to predict something about a particular individual. Should predictive policing algorithms more closely resemble those used to predict disease from DNA samples or those used in the clearance process? Should they be used at all?