Christopher Slobogin (Vanderbilt U Law) has posted “Predictive Policing in the United States” (forthcoming in The Algorithmic Transformation of the Criminal Justice system (Castro-Toledo ed.) on SSRN. Here is the abstract:
This chapter, published in the book The Algorithmic Transformation of the Criminal Justice system (Castro-Toledo ed., Thomson Reuters, 2022) describes police use of algorithms to identify “hot spots” and “hot people,” and then discusses how this practice should be regulated. Predictive policing algorithms should have to demonstrate a “hit rate” that justifies both the intrusion necessary to acquire the information necessary to implement the algorithm and the action (e.g., surveillance, stop or arrest) that police seek to carry out based on the algorithm’s results. Further, for legality reasons, even a sufficient hit rate should not authorize action unless police have also observed risky conduct by the person the algorithm targets. Finally, the chapter discusses ways of dealing with the possible impact of racialized policing on the data fed into these algorithms.
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