The Growing Use of Big Data and Analytics in Law Enforcement
Big data has always existed in the federal government, from tax information to population numbers. The term big data essentially means a high volume of data that can be processed for decision making purposes. However, its growing presence coupled with emerging technologies, have turned it into a hot commodity in recent times.
Analytics basically plays a role in evaluating the different variables in big data for that output, solution or prediction. Moreover, a key change in the evolution of analytics is the use of autonomous analytics. Previously, data analytics was used for human decision makers, to evaluate and make a final decision. However, through the use of machine learning and other advances, it is the technologies that can now take the next step and actually make the decision or recommended action on their own.
Given this, it is no surprise that the use of big data and analytics is of special use in the law enforcement community. In fact, increased investment in big data tools and services have been seen in recent contract spending, as reported in GovWin's report, Federal Big Data Market, 2020-2022.
One example comes from the Networking and Information Technology Research and Development (NITRD) Program, which is a sub-committee of the National Science and Technology Council comprised of multiple agencies performing R&D across emerging technology areas. For FY 2021, NITRD realigned its Interagency Working Groups into 11 Program Component Areas (PCAs), eight of which work with big data technologies, including high performance computing, advanced analytics, artificial intelligence (AI) and high-speed networking. The total FY 2021 budget request across NITRD’s eight PCAs dealing with big data technologies is $5.7B. This total is up $323M vs. FY 2020 and $461M vs. FY 2019.
The most controversial use of analytics in law enforcement is predictive policing – a term that defines the method in which law enforcement uses data, historical information and analytical models to identify and forecast crime prone areas and entities. For example, Assistant Director Scott Smith at a 2017 RSA conference panel stated that the FBI cybercrime unit is focusing the use of predictive policing in its mission, as reported by FedScoop. In essence, the FBI is attempting to forecast potentially harmful cyber activity through use of predictive analytics to pinpoint a breach or other illegal activity before it actually happens.
Moreover, private entities are boasting of data mining techniques to help law enforcement in targeting criminals such as online sex traffickers. These methods rely on machine learning mechanisms in mining online ads and currency payments in order to discern and identify those participating in the illegal criminal activity.
One example of big data and analytics use in law enforcement comes with the FBI’s release of the Crime Data Explorer. The portal, built in conjunction with 18F, provides reported crime data in a modernized fashion. Making FBI crime data public is not a new phenomenon, however, the Crime Data Explorer provides the trends and rates of crime across the U.S. by state and type of crime and allows users to upload the raw data for further analytical manipulation. Such information will likely be used by other law enforcement entities and the public alike.
In sum, the use of big data will not disappear from the law enforcement sector, rather, its use will vastly increase, particularly as emerging technologies such as artificial intelligence and machine learning are refined. The big data appeal of saving time and resources will continue as a “doing more with less” mindset resonates across all government faculties, including law enforcement.
Understand the Federal Big Data Market
Originally published on August 23, 2017
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