Have you heard of “predictive policing”? The idea that big data can help law enforcement agencies to stop crime before it happens is a recent point of discussion in both criminology thought groups and the technological world. So when we use the term “predictive policing,” we refer to these discussions and ventures. We have experimented a little bit in it, and many are wondering if it should become the new norm.
There is no doubt though that big data is already being experimented with by law enforcement, even though there are several potential bugs to work out. There is some controversy around it, whether the means of surveillance justify the ends of halting potential crime. As the discussion continues, however, predictive policing doesn’t seem to be a law enforcement method to die out anytime soon.
Predictive Policing in Action
Predictive policing means using big data — obtained from businesses that predict consumer and market trends — to forecast criminal activity before it happens. Additionally, it means monitoring social media activity.
There have been examples of officers more heavily patrolling crime ridden areas before they predict a surge in criminal activity, based off of the information given to them through big data analysis. At times they’ll inform potential re-offenders and the rest of the community that they are under watch, and the crime rate will fall or the predicted rise will not happen. After all, many people who leave prison find themselves back there, unfortunately.
Portland State University documents such situations of alerting previous criminal offenders after big data has alerted officers of potential crime increases. In the same piece, it is documented that the Kansas City Police Department used an initiative titled the Kansas City No Violence Alliance (KC NoVA) in reaching out to those that predictive policing made suspect. They were able to contact these potential re-offenders and help them to find better housing and jobs. In doing so, it is hypothesized that they have successfully reduced homicides by 20 percent.
Communities like this one in Kansas City have benefited from predictive policing, and the ends to their means have without a doubt proved to be significant. Reportedly, the Kansas City Police Department identified around 60 criminal enterprises, and some of the whistle blowers were potential re-offenders. Not only was crime reduced, but some of the predicted suspects ended up benefiting the community rather than re-offending.
Faulty Design
The biggest arguments against predictive policing revolve around information privacy, police profiling, and flawed police algorithms. There is dispute about whether or not it’s ethical for third parties to give such information to law enforcement agencies, but critiques of predictive policing go beyond that.
As Alice Speranza puts it, “the data shared and gathered through commercial websites is often anonymized and then de-anonymized by commercial aggregators (who have less legal limitations and interest in ascertaining the identity of a specific individual).” So there is a fear that third party data from businesses could potentially lead to the arrest of an innocent person.
Speranza further comments on the monitoring of social media. If police algorithms search for patterns based on certain words or topics of conversation used in Facebook posts, for instance, there is the possibility that such things are coincidences and the wrong person could be arrested under false suspicion. As well, “that raises the spectre of Orwellian thought crime” she writes.
The Future of Predictive Policing
Predictive policing is on the rise and doesn’t seem to be going anywhere. While the tension around predictive policing’s ethical validity remains, results seem to be positive enough in preventing crime for it to become a more commonly used method of policing.
One has to wonder however, due to programs like Black Lives Matter and devices such as police dash cams, if the social stigma around law enforcement accountability will slow down the rise of predictive policing. Only time may tell.
About the Author
Avery Phillips is a freelance human based out of the beautiful Treasure Valley. She loves all things in nature, especially humans. Leave a comment down below or tweet her @a_taylorian with any questions or comments.
Sign up for the free insideAI News newsletter.
