With calling, shopping, and even dating all done on computers, it’s not too surprising that cops are relying more and more on digital data to help them catch criminals.
In what is called predictive policing, cops can use data to assist them in identifying people more likely to commit crimes.
While the concept definitely has it’s merits as it could drastically increase the efficiency of the police force by narrowing down the number of people they would have to keep a close eye on, it runs the risk of over-arresting certain people for more menial crimes based on who they spend time with and where they live.
Using data to assist officers is not a new concept, but the scale of what predictive policing would include if adopted nationwide would be another matter entirely.
“What is new about modern predictive policing is the promise that, using so-called big data,” asserted Aderson B. Francois of The New York Times. “Law enforcement can use sophisticated objective statistical and geospatial models to forecast crime levels, thereby making decisions about, when, where, and how to intervene.”
Essentially, predictive policing would create the equivalent of a weather map, only the forecast will not be a 70 percent chance of rain Friday night, but perhaps a 30 percent chance of robbery on Colorado Boulevard.
Like the weather report, it really is hit or miss.
Predictive policing is still in its testing phases and has stellar results in some areas and confusing results in other places.
“In 2011, for example, in Trafford, Manchester, police noted a 26.6% fall [due to predictive policing] in burglaries, compared to a 9.8% fall across Greater Manchester in the same period,” wrote Mark Easton of BBC. “It [predictive policing in Kent] ran a successful four-month trial starting in December 2012, but after rolling out predictive policing across the county in April 2013, recorded an increase in crime for the following year.”
While predictive policing did find success in Britain, there are also kinks to work out as well.
The failure of predictive policing in Kent was largely attributed to an inefficient allocation of resources and inaccurate crime data.
No system will be impeccably accurate with humans at the helm feeding information. The main issue with predictive policing is the information that goes into the system.
“At first glance, such systems seem benignly empirical. But such an understanding wrongly assumes the neutrality of information,” wrote Natasha Lennard of Vice News. “The picture of crime to come is based on pre-existing police data, which we know to be biased and flawed.”
The data used will reflect on how the police operate. If the police focus more on one crime-ridden area, then the data will thus be skewed and will tell the police to scour that area.
As such, the system, while useful, is still flawed because it relies on the most unreliable source: humans.
Thus, predictive policing probably should not be relied upon too heavily since it will tend to be as flawed as the person reading it.
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