In the 2002 Tom Cruise movie “Minority Report,” crime in the year 2054 is eliminated by an elite PreCrime squad whose special powers enable them to see the future and predict crime.
It may be 42 years until 2054, but some police agencies have already begun to predict future crime by mining “Big Data.” Big Data is any data that can be accessed legally and potentially assist police in next-generation crime fighting, from phone records, financial transactions, and crime statistics to closed circuit videos, e-mails, and still images.
The idea is not that new. Law enforcement has always collected data. What’s new is the amount of data. Google CEO Eric Schmidt says five exabytes of data is generated every 48 hours. An exabyte is one million terabytes. There’s a lot of crime to fight. According to the FBI, in 2009 there were 1.3 million violent crimes, 9.3 million property crimes, and 6.3 million larceny/thefts. That’s one crime every 2 seconds.
What’s also new is how the data is mined.
“We’re inventing new ways to proactively capture data that may be useful in investigations, and to find smarter ways to cross-reference government data across multiple agencies and data mined in the private sector,” says Philip Becnel, managing partner of Dinolt Becnel & Wells Investigative Group (Washington, D.C.).
Law enforcement agencies in the Washington, D.C., area now collect data from dozens of stationary cameras that capture 1,800 license plate images a minute, information stored for later investigative use. The FBI recently announced it was making its facial recognition technology available to other law enforcement agencies.
“While the FBI has pledged not to mine photographs from social media to add to its current database of around 13 million mug shots, it can and does routinely search the Internet for matches to crime suspects,” Becnel says.
Social media is a mother lode of information. Researchers at the University of Wisconsin recently taught a computer how to detect bullying-related tweets among the 250 million publicly visible messages posted daily on Twitter. Now the machine is identifying more than 15,000 bullying-related tweets most days. This specific tweet traffic seems to ebb on weekends, presumably because school is in session only on weekdays.
The FBI is also developing a leap-ahead technology called Sentinel, a case management system that allows investigators to search for unique pieces of data, like crime details or phone numbers, across multiple investigations.
“Big Data has great potential to predict crime, crime hot spots, and criminal trends,” says John DeCarlo, a professor of criminal justice and forensic science at the University of New Haven. “When we look at technologies like criminal path mapping and predictive policing, we begin to see the same potential in using Big Data that retailers have observed.”
In 2011, the Santa Cruz, Calif., Police Department began using crime records from the city’s archives that contained decades of data on when, where, and what types of crime occurred in the past to predict when, where, and what future crimes may occur.
The Santa Cruz crime model originated with UCLA mathematician George Mohler, who noticed that, over time, crime maps tend to resemble maps of natural phenomenon, like earthquakes. Earthquakes tend to swarm. So do crimes. The trick is predicting when, where, and how many. Mohler adjusted the earthquake algorithms previously used to predict earthquake aftershocks to produce hot spot maps where future burglaries or car thefts might be likely to occur. When Santa Cruz police used Mohler’s maps to deploy patrols to predicted crime hot spots, there was a 27-percent drop in burglaries compared to the same area in the same month the year before.
In August, the New York Police Department, in partnership with Microsoft, launched a state-of-the-art crime prevention and counter-terrorism technology based on Big Data mining, called the Domain Awareness System.