Minority report: Pre-crime technology has arrived

Remember the movie Minority Report, where advanced analytics and supercomputing was able to predict where the next crime would take place and a special police unit was able to arrest murderers before they committed their crime? Well, that technology is not just for Hollywood anymore.

Pre-crime technologies are already here

The following pre-crime technologies already exist (with more to come):

  • Future Attribute Screening Technology (FAST)
  • LexisNexis® Accurint® Virtual Crime Center
  • Artificial Neural Network (ANN)


With the Future Attribute Screening Technology (FAST) system, the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) seeks to improve DHS’s ability to quickly and objectively screen individuals for malintent, defined as the mental state of an individual intending to cause harm to our citizens or infrastructure.

One of the most prominent programs out there, this pre-crime system is already so advanced that developers claim that it has about an 80% success rate. Its purpose is to detect malicious intent by screening people for both psychological and physiological indicators via a mobile screening lab. This brings up ethical questions, such as what are the consequences of being deemed guilty based upon statistical algorithms and predictive analytical assessments?

FAST is designed to track and monitor, among other inputs, body movements, voice pitch changes, alterations in the rhythm and intonation of speech, eye movements, body heat changes, blink rate, pupil variation, and breathing patterns. Occupation and age are also considered.

The FAST system is intentionally designed to only examine physiological and behavioral cues so that no privacy or civil rights are violated.

LexisNexis® Accurint® Virtual Crime Center

Government Security News recently announced that LexisNexis® Risk Solutions has a new policing technology that gives law enforcement greater visibility into crime in both their jurisdictions and nationwide by linking billions of public records with agency-provided data. The new LexisNexis® Accurint® Virtual Crime Center provides a comprehensive view of peoples’ identities so that law enforcement can better target investigations, identify patterns, predict upcoming events and deploy resources more efficiently.

LexisNexis Accurint Virtual Crime Center links different data types on people, places, vehicles, phones and other information into one visual dashboard. It is a next-generation policing platform for COMPSTAT, analytics, crime analysis and investigations. It brings together for the first time disconnected data from many different sources to reveal insights and linkages that otherwise might never have been seen.

For example, the Accurint Virtual Crime Center helps find the “who” in an investigation by linking agency data with public identity data from over 10,000 sources. With a single search, agencies can scour their own Records Management System as well as external data to discover non-obvious connections between people and generate investigative leads.

Artificial Neural Network (ANN)

Researchers at Tomsk University in Russia have created a computer program that can be used to predict different aspects of criminal behavior using Artificial Neural Network (ANN) technology and have suggested that the technique could be adapted as an effective tool in selecting suitable employment candidates as well.

The team was able to divide survey respondents into classifications based on the ANN program’s analysis of dominant personality characteristics, which were correlated to the type of crime they had been jailed for in 80% of cases.

The main goal of the study was to see if prisoners could be classified based on the survey results using a specially-developed ANN program, which would separate respondents based on dominant characteristics; and to see if those dominant characteristics were related to the type of crime for which the subject had been convicted.

The study found that in 80% of cases, the scientists could accurately predict what crime a prisoner had been convicted of, based on the dual ANN program analysis of the personality survey results.

The survey attempted to cover a large set of personality characteristics, while the Artificial Neural Network divided responses into two separate, scaled two-factor classifications. The first measured respondents on a scale of domination to subordination and the second, friendliness to hostility.

“We are interested in the problem of predicting behavior, which is primarily determined by the individual’s temperament and character,” said Project lead ­­­­Michael Golovchiner, Associate Professor in the department of Applied Mathematics at Tomsk University. He further stated, “The question of whether there is a set of characteristics that distinguish criminals convicted of various crimes is a task well-suited to ANN because this is an issue of classification. The training and testing revealed two characteristic factors: ‘domination-submission,’ and ‘friendliness-hostility,’ and the error rate of classification was about 20 percent, indicating a relatively high level of accuracy.”

Global impact

Pre-crime security is a hot topic globally as well as in the U.S. For example, the Chinese government is leveraging predictive policing capabilities that have been used by US law enforcement, and has funded research into machine learning and other artificial intelligence technologies to identify human faces in surveillance videos. The Chinese government has also used this technology to create a “Situation-Aware Public Security Evaluation (SAPE) platform” that predicts security events based on surveillance data, which includes anything from actual terrorist attacks to large gatherings of people.

The Chinese government has plenty of data to feed into such systems. Over the past several years China has invested heavily in building its surveillance infrastructure, turning the country into the biggest market for security technology.

It also plans to use that data in an effort to perform behavioral prediction at an individual level—tasking the state-owned defense contractor China Electronics Technology Group to develop software that can sift through the online activities, financial transactions, work data, and other behavioral data of citizens to predict which will perform “terrorist” acts. The system could watch for unexpected transfers of money, calls overseas by individuals with no relatives outside the country, and other trigger events that might indicate they were plotting an illegal action.

China Electronics Technology Group Chief Engineer Wu Manqing said at a news conference, “We don’t call it a big data platform, but a united information environment. It’s very crucial to examine the cause after an act of terror, but what is more important is to predict the upcoming activities.”

Undoubtedly, more cities, governments, and businesses will be increasingly adopting such technology. How they choose to use this technology is what we should be most concerned about. For perhaps in the future, we might be using technology to not only read our minds but to control our minds as well. And, that is a scary thought.

Someone better call Tom Cruise!

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