The Pre-Crime Premium: How Predictive Policing Algorithms Are Redrawing Our Neighborhood Maps
Beyond the Siren: What is Geospatial Risk Scoring? Imagine walking outside and relying on an app to tell you whether it might rain. Now, imagine that same kind of predictive tool, but instead of predicting weather, it forecasts crime rates in various neighborhoods. This is the crux of predictive policing , where historical crime data feeds into algorithms to produce what are known as geospatial risk scores or ‘hotspot’ maps. The analogy holds because, much like weather forecasts rely on patterns in meteorological data, predictive policing relies on patterns in crime-related data. However, these patterns can often be fraught with historical biases , which is where the issues begin to brew. While initially aimed at aiding law enforcement, these data are now increasingly used by various other sectors such as insurance companies, risk assessment firms, and financial institutions to assess and manage risks. Not surprisingly, the adoption of geospatial data extends far beyond its origin...