With every call you make on your cell phone and every swipe of your debit and credit cards, a digital signature of when, what, and where you call or buy is incrementally built every second of every day in the servers of your credit card provider and wireless carrier. Monitoring the digital signatures of your consumer DNA-like code are models created with data mining technologies, looking for deviations from the norm, which, once spotted, instantly issue silent alerts to monitor your card or phone for potential theft. This is nothing new; it has been taking place for years. What is different is that since 9/11, this use of data mining will take an even more active role in the areas of criminal detection, security, and behavioral profiling.
Behavioral profiling is not racial profiling, which is not only illegal, but a crude and ineffective process. Racial profiling simply does not work; race is just too broad a category to be useful; it is one-dimensional. What is important, however, is suspicious behavior and the related digital information found in diverse databases, which data mining can be used to analyze and quantify. Behavioral profiling is the capability to recognize patterns of criminal activity, to predict when and where crimes are likely to take place, and to identify their perpetrators. Precrime is not science fiction; it is the objective of data mining techniques based on artificial intelligence (AI) technologies.
The same data mining technologies that have been used by marketers to provide personalization, which is the exact placement of the right offer to the right person at the right time, can be used for providing the right inquiry to the right perpetrators at the right time, before they commit crimes. Investigative data mining is the visualization, organization, sorting, clustering, segmenting, and predicting of criminal behavior, using such data attributes as age, previous arrests, modus operandi, type of building, household income, time of day, geo code, countries visited, housing type, auto make, length of residency, type of license, utility usage, IP address, type of bank account, number of children, place of birth, average usage of ATM card, number of credit cards, etc.; the data points can run into the hundreds. Precrime is the interactive process of predicting criminal behavior by mining this vast array of data, using several AI technologies:
Link analysis for creating graphical networks to view criminal associations and interactions
Intelligent agents for retrieving, monitoring, organizing, and acting on case-related information
Text mining for examining gigabytes of documents in search of concepts and key words
Neural networks for recognizing the patterns of criminal behavior and anticipating criminal activity
Machine-learning algorithms for extracting rules and graphical maps of criminal behavior and perpetrator profiles