Big data to help the police to improve security

Bigdata (i2tutorials.com)

The BBC’s documentary, The Age of Big Data, describes how the Los Angeles Police Department uses massive crime archives and other relevant data, combined with sophisticated mathematical algorithms to be accurate before drug dealers trade. Predict where and when they will be connected. This looks like a fictional science fiction, but it happens.

Sarah Brayne of the University of Texas at Austin, through a two-and-a-half-year observation and interview with the Los Angeles Police Commission, found that big data analysis technology has profoundly changed the means and practices of police monitoring, not only magnifying the existing surveillance capabilities of the police department. And lead to a fundamental transformation of monitoring activities.

Specifically, she believes that big data has driven innovation in police surveillance in five areas.

(1) Past assessments of crime risk often rely on police experience, while big data tends to quantify risk assessments and make accurate estimates in the form of risk values.
(2) The police use big data to predict the future, rather than passively responding or explaining past events.
(3) The ubiquitous automatic warning system helps the police systematically monitor an unprecedented number of people.
(4) In the past, the law enforcement database was mainly for people with criminal records, but now it includes many people who have not had direct contact with the police in the past, which makes the monitoring network more and more large.
(5) Data scattered in different places and fields in the past can be integrated through big data technology to form related data and promote the monitoring of everyone.

Big data remodeling police monitoring:

Social monitoring is not new, but the monitoring of modern society is far from the breadth and depth of the past.

In terms of breadth, the police used to monitor the main targets of parole and rescue, but now it has achieved wide coverage, even ordinary people can not escape monitoring. In terms of depth, relying on the convergence of data from various departments, the police department can now “deeply dig” all aspects of a person and make it a “transparent person”.

Big data means that the information we use to monitor society is massive and rich, high-frequency records can be processed quickly. Data is formatted and sourced differently, but electronically is easy to store and merge. These characteristics make it possible to profoundly change the way and method in which the police department monitors the society and maintains public safety, and makes the intelligence of police monitoring increasingly prominent.

Unlike the past, subjective judgments to determine the object of the investigation, big data technology allows the police to quantify each person’s criminal suspects. This allows the police to “discriminate” different groups of people based on the risk of crime, and can “get one right”. “High-risk areas” based on historical criminal records can make police patrols or checks more targeted and more evidence-based, and avoid prejudice and discrimination that the outside world would consider police enforcement (such as more investigations against blacks).

In the past, the police were passively responsive, relying on reporting, patrolling and quick response. But these practices are relatively inefficient, such as aimless patrols or sky-hunting searches. More and more criminologists believe that a more forward-looking and proactive approach should be adopted to find clues through data analysis, so that detours can be reduced and efficiency can be improved. At the same time, this can also reduce the dependence of monitoring on work experience. Even a fledgling police school graduate can follow a big data forecasting instruction, like a veteran policeman to patrol.

Relying on big data technology, the police’s monitoring method is gradually shifting from “interrogation” to “warning”. The police department links all connected people, phone numbers, license plate numbers, addresses, accidents, etc., and if there is any change, it will trigger a chain reaction, promptly and even promptly alert. This is like “crawling fishing”. Once the net is too large, just wait for the fish to touch the net.