Runaway Feedback Loops in Predictive Policing

• DOI: 10.48550/arxiv.1706.09847
• Publication Date: 2017-01-01
• Authors: Danielle Ensign; Sorelle A. Friedler; Scott Neville; Carlos Scheidegger; Suresh Venkatasub...
• Keywords: FOS: Computer and information sciences; Computer Science - Computers and Society; Statistics - Machine Learning; Computers and Society (cs.CY); 0202 electrical engineering, electronic engineering, information engineering; Machine Learning (stat.ML); 02 engineering and technology; 16. Peace & justice

Predictive policing systems are increasingly used to determine how allocate police across a city in order best prevent crime. Discovered crime data (e.g., arrest counts) help update the model, and process is repeated. Such have been empirically shown be susceptible runaway feedback loops, where repeatedly sent back same neighborhoods regardless of true rate. In response, we develop mathematical model predictive that proves why this loop occurs, show exhibits such problems, demonstrate change inputs system (in black-box manner) so does not occur, allowing rate learned. Our results quantitative: can establish link our model) between degree which causes problems disparity rates areas. Moreover, also way \emph{reported} incidents (those reported by residents) \emph{discovered} (i.e. those directly observed officers dispatched as result algorithm) interact: brief, while attenuate feedback, they cannot entirely remove it without interventions suggest.