Software predicts, and in so doing can problematically determine, high crime areas
Since its introduction by the Los Angeles Police Department two years ago, predictive police technology, which relies on data analysis software to predict where crimes will likely take place, has been lauded for lowering crime rates.
Since 2010, a number of police departments nationwide have introduced analytics units — Seattle joined the number last week. As the West Seattle Herald noted, “The software, developed by UCLA and the LAPD in Los Angeles based on models that predict earthquakes, will attempt to forecast where crimes might occur based on data analysis of logged crimes since 2008, according to the Mayor’s office. Police will use that data to determine where they patrol, searching for burglars and thieves in our neighborhoods.”
It’s worth noting that predictive policing far predates this predictive policing technology. Indeed, often based on highly problematic metrics, which as much create as they do respond to high crime areas, police target certain areas and neighborhoods expecting and seeking certain criminal activity. A spokesperson from SPD went as far as to say that using the predictive software would help eliminate institutional bias about crimes, who commits them and where:
“We anticipate that this software will help us in our work to eliminate institutional bias in the Seattle Police Department,” SPD Assistant Chief Mike Sanford said in a statement. “With Predictive Policing, we’re sending officers right to where we know the crime is, helping to take any unconscious bias out of the equation.”
However, Sanford’s point falls apart somewhat, given that the data the software works from is based on previously logged crimes and where they took place — data very much shaped by preexisting institutional bias and patterns of where police seek out arrests. And furthermore, recorded success of the predictive policing software must be understood as somewhat self-fulfilling. The American Criminal Law Review explains:
It must be noted that predictive policing itself may affect the statistics that shape the predictions. At one end of the spectrum, a successful predictive policing policy can create a self-perpetuating high crime area. For example, if police administrators direct police officers to a particular location, the increased police presence may mean more arrests. If there are more arrests, that fact will justify a continued designation as a high crime area, which will necessitate an even greater police presence and again more arrests. At the other end of the spectrum, a heavy police presence may deter crime (without greater arrests), which will mean that crime rates will be reduced causing the area to lose its “high crime area” designation even though it was the designation (and the extra police presence) that caused the decrease in crime.
The American Criminal Law Review has also noted that predictive policing software could pose a threat to Fourth Amendment protections against unreasonable searches and seizures. “Under current law, the character of a neighborhood as a ‘high crime area’ can be a factor for ‘reasonable suspicion’ to stop a suspect,” noted the ACLR, adding that there is therefore concern that “Predictive policing will create an implicit high crime area exception to the Fourth Amendment in those targeted areas. Individuals in those areas will have a lesser expectation of privacy than those in other non-high crime area neighborhoods.”
Natasha Lennard is an assistant news editor at Salon, covering non-electoral politics, general news and rabble-rousing. Follow her on Twitter @natashalennard, email firstname.lastname@example.org. More Natasha Lennard.
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