How Artificial Intelligence can control criminal activities?

AI and Crime prevention

AI and Crime prevention

How Artificial Intelligence can control criminal activities?

Overview

Artificial Intelligence is being used to both prevent and control crimes in many countries. In fact, AI’s involvement in crime management dates to the early 2000s. AI is used in such areas as bomb detection and deactivation, surveillance, prediction, social media scanning and interviewing suspects. However, for all the hype and hoopla around AI, there is scope for growth of its role in crime management. Currently, a few issues are proving hindersome.  AI is not uniformly engaged across countries in crime management. There is fierce debate on the ethical boundaries of AI that is compelling law enforcement authorities to tread carefully. Defining the scope and boundaries of AI which includes personal data collection is a complex task. Problems notwithstanding, AI represents a promise of a new paradigm in crime management and that is a strong case for pursuance.








What is the crime prevention model?

It is about analyzing large volumes of various types of data from many different sources and deriving insights. Based on the insights, predictions can be made on various criminal activities. For example, the social media provides a veritable data gold mine for analysis though, for privacy issues, it is a contentious issue. It is a known fact that part of the radicalization activities of youth is done by various radical groups through social media. Ai can reveal crucial insights by analyzing such data and provide leads to law enforcement agencies. There are also other data sources such as the ecommerce websites. Amazon and eBay can provide valuable data on the browsing and purchasing habits of suspects. The model is not new, though. Back in 2002, John Poindexter, the Retired Admiral of the US Army had developed a program named Total Awareness Program which prescribed collecting data from online and offline sources. But following vehement opposition because of privacy intrusion issues, funding support to the program was stopped within a year.

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Real-life applications

In this section, we will read about a few case studies on the role of AI in crime management, the model and the results.

Bomb detection and deactivation

The results of deploying robots in detecting bombs have been encouraging which led the military procuring military robots worth $55.2 million. Over time, robots have become more sophisticated and can distinguish between a real bomb threat and a hoax by examining a device. According to experts, robots should soon be able to deactivate bombs.

Surveillance, prevention and control

In India, AI-powered drones are used to control crowds by spraying pepper and paintballs or making announcements. Drones are fitted with cameras and microphones. Drones, it is believed, can soon identify people with criminal records with facial recognition software and predict crimes with its machine learning software. In 2016, the Dallas Police deployed a robot to shoot down a criminal.

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Social media surveillance

Social media provides the platform for executing different crimes such as drugs promotion and selling, illegal prostitution and youth radicalization for terrorist activities. For example, criminals use hashtags to promote different causes to intended audiences. Law enforcement agencies in the US have succeeded to an extent in tracking such crimes with the help of AI. Instagram, for example, is used to promote drug trafficking. In 2016, New York law enforcement used AI to track down drug peddlers. AI searched for millions of direct and indirect hashtags meant to promote drugs and passed on the information to police. Similarly, to tackle radicalization of youth, law enforcement agencies are using AI to monitor conversations in social platforms.

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Interviewing suspects

An AI-powered chatbot in a university in Enschede, a city in the eastern Netherlands is being trained to interview suspects and extract information. Expectations from the bot are to examine the suspect, ask questions and detect from the answering patterns and psychological cues whether the suspect is being truthful. The name of the bot is Brad. It is still in the basic stage, but the development represents a new aspect in crime management.

Advantages and disadvantages

The main advantages and disadvantages are described below.

Advantages

Security needs and considerations are dynamic and complex, and you need a system that adapts fast and efficiently. Human resources are capable but have constraints. In this view, AI systems have the advantages of scaling up and doing their jobs efficiently. For example, monitoring possible criminal activities on social media, from a manual perspective, is a gargantuan task. Human approaches can be erroneous and slow. AI systems can perform this task by scaling up and performing the tasks faster.

Disadvantages

Firstly, for all the hype around, AI’s involvement in crime management is still in the nascent stage. So, cut the hype and accept that its efficiency in crime prevention or control on a larger scale is still unproven.

Second, crime prediction and prevention will require data collection much of which could be personal data. This makes the government and law enforcement agencies vulnerable to extreme criticism from citizens and other groups. This will be interpreted as intrusion on citizens’ freedom. Data collection and snooping have been extremely contentious issues in the past, especially in countries with democratic setups.

Third, developing AI systems that learn from unstructured data can be an extremely challenging task. Since the nature of criminal activities have been becoming more sophisticated, it might not always be helpful to provide structured data. It is going to take time for such systems to adapt.








Conclusion

Currently, there are many challenges confronting the involvement of AI systems in crime management. However, it is worth the effort to engage AI in crime prevention and control. The nature of crime and terrorist activities is evolving to become more sophisticated every day and purely human involvement is no longer enough to tackle such problems. In this context, it may be important to note that AI will not replace human beings but will complement each other. AI systems can be fast, accurate and relentless and it is these qualities that law enforcement agencies will want to exploit. At this moment, it really seems a good bet.

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