Imagine your every move, on and offline being watched and recorded at all times, leaving a digital trace. Every click, like, favorite, retweet, we do online, and everything we do offline, like a credit card purchase we make, all are contributing factors to leaving a digital trace or digital shadow and collected into a large data set. This is what people like to refer to as “Big Data”; being able to dig up data from multiple sources, analyzing the data collected and sometimes make decisions based off that data. Big data has been around for quite some time now, which originally started off when businesses collected data on their clients to see what makes them agitated. But one day, someone discovered that this big data system can be used in law enforcement investigations in many different ways.
Michal Kosinski, a student attending Cambridge University for his PhD in Psychometrics, met and teamed up with fellow student David Stilwell, who had just created and launched his own Facebook application called the MyPersonality App. From this app, users fill out a psychological questionnaire, and based off of their answers to this questionnaire, users were given a “personality profile”. Kosinski took the participants answers from their questionnaires and compared it to their online information left behind such as: the posted they liked, shared posts, or their specified information on Facebook such as: where they live, gender, age, and marital status. While this information on its own may not be a reliable source of information, when thousands of posts or “individual data sources” are reinforced and recorded into a system, it is easier to make pretty accurate predictions.
After years of revision, Kosinski and his team were able to put the finishing touches on their app in 2012, where they were able to make even more specific predictions than ever. They announced that after their revisions, they were able to tell just based off of 68 “likes” on Facebook, a persons skin color, ones sexual orientation, religious affiliation, and their political status. All of this predicted information is surprisingly anywhere from 80-100% accurate. Interestingly enough, this personal data that has been collected can actually be used the other way around, to search for other personal profiles.
Social media as a whole has changed how law enforcement not only solves and prevents crime. “There’s a growing number of police departments who are making social media part of intelligence processing,” says Mike King, a former police officer who works in the law enforcement division of the Geographic Information Systems (GIS) developer. King continues to say that there is “a weird psychology involved with people who are deeply embedded in social media.” Although mainly relying on social media to crack a case can be difficult because it is dependent on so many different factors, one of them being if someones location is turned on, but on the other hand, in some cases where social media was heavily used, they found perpetrators actually broadcasting and announcing the crimes they have just committed.
The idea of using big data in law enforcement cases is something that has been around for two decades now, and continues to get more powerful everyday. Today, most law enforcement agencies have adopted this method, and are using whatever available data to prevent crime and in some cases, even catch criminals and put them behind bars. In fact a number of cities in the United States are beginning to use what they refer to it as “predictive data” aka big data on a lot of their cases to further investigations, across a number of different platforms such as the cloud, all different kinds of social media, emails, and even our personal cellphones.
In Durham, North Carolina where the crime rate is pretty high with about 13, 357 violent (recorded) crimes per year, their police department was able to cut their crime rate in half by using “predictive data” to analyze relationships. The relationships that are analyzed are the ones between places, people, and other personal data, which ultimately makes the police department run more efficiently.
In Los Angeles, the LAPD are using big data systems to collect data from old cases such as: rap-sheets, case management tools, DMV records, license plates, and so forth. “For years we’ve had stovepipe systems that have a lot of information but don’t talk to each other and don’t compare that information,” says LAPD Chief Charlie Beck. Since the LAPD has implemented the use of big data into their investigations, they have also seen a drop in their crime rate as well.
The Chicago police department is also a big supporter of using predictive data to solve cases. In fact, they have implemented a state-of-the-art big data system. Their system has what they call a “heat-list” , which is basically a list of about 400 people who are most likely going to be involved in crime. When someone is added to the CPDs heat-list, they are notified immediately, along with the legal consequences that could come along with the crimes they may or may not commit as a part of the police departments Violence Reduction Strategy (VRS) which was established in July 2013. The CPD big data system also uses graphic and predictive algorithms. The reason being is that majority of the crimes being committed such as: gang violence, drugs, and gun violence all travel through or occur in their neighborhoods and local cities.
Lastly, the police department in Ft. Lauderdale was chosen to have a First of a Kind research development program with IBM. The purpose of this project is to analyze crime-related data sources using a combination of advanced technologies. During this project, IBM analyzed all kinds of data from 911 calls to criminal records. While analyzing this range of data, they are mainly focused on looking for patterns in location, time, unlike the MyPersonality app, which determines who will be likely to commit a crime rather than where and how its being committed. According to the company International Business Machine (IBM), the research program will allow for a “deeper level of knowledge regarding possible contributing factors of crimes and foresee the demand for service at a more granular level of time and location…”, which ultimately leads to enabling the city to “to move operations from reactive to proactive, leading to a safer city.”
Now, is this a good or bad thing? Well I guess it depends if you like being watched or surveilled 24/7 and put into a data base. Personally, I don’t feel comfortable knowing every move I make on and offline is being recorded and stored into a bigger data system. Although, this is just the beginning for predictive data in law enforcement agencies and technology will keep advancing, police swear they are not interested in violating our privacy. “We’re going to continue to test boundaries and I believe that’s what makes the Untied States such a great country,” says King.
There is still a long way to go when it comes to implementing predictive or big data into law enforcement agencies. Anybody can form a bias opinion off of information that has been collected based off of a persons personal information without actually meeting them or knowing anything else about them at all. On the other hand, I also have seen people post pictures and announce the crimes they have just committed on social media as well. If people are bold enough post their involvement in illegal actives, than the use of big data in that way is completely fine.
Is using big data the best decision? In todays day and age and where we stand with racism as a country, I am not sure its the best decision. Police officers already have a bias opinion in their head about kids and young adults of this generation, so will giving the cops more information that people didn’t know was being recorded and used against them, actually help fight crime? I am a realist, and realistically, id like to see how this plays out, because all you hear today about social media and cops, is that cops are intentionally killing people of color just based off of their personal feelings towards them. To me, this seems like adding fuel to the fire in some cases, but could also be beneficial if used in the correct manner.