The debate about the criminal justice system increasingly is driven by empirical studies. Phil Dixon wrote thoughtfully last week about a new analysis of 700,000 drug arrests conducted by UNC faculty members outside the School of Government. This article by a Georgia law professor is also attracting attention – it claims to be “the most substantial empirical analysis of misdemeanor case processing to date,” based on “multiple court-record datasets, covering several million cases across eight diverse jurisdictions.” Similarly, in the popular media, this Washington Post article analyzes a huge trove of data to determine the percentage of arrests in each county across the nation that are based on marijuana possession.
I could list many more examples, but the general point is one with which I suspect most readers will agree: that big data is revolutionizing the discussion of criminal justice. This transformation has been unfolding for decades. Drivers include the growth of law and economics and other law and social science approaches, which has fertilized the legal field with social science techniques, and the increasing availability of large datasets, which has made statistical analysis easier. This post offers a few thoughts about the costs and benefits of this new data-focused world. Continue reading