What is machine learning?

To understand what machine learning is first , we need to understand the basic nature of machines like computers. Computers are essentially just devices that follow instructions.. However, machine learning brings in an interesting outlook, whereby a computer can learn from experience without the need for programming.

Machine learning takes computers to the next level where they can learn intuitively in the same way as humans. Machine learning has many applications, which include areas like virtual assistants, traffic predictive systems, surveillance systems, face recognition, spam and malware filtering, fraud detection, etc. One of the areas where machine learning is being used in policing.

Present challenges

Machine learning is being used by the police already, where they are integrating machine learning with AI (Artificial Intelligence) and using it in law and order. Let us look at the present police challenges that can be resolved through the use of machine learning:

• It is not enough that law enforcement agencies respond to incidents of crime but they need to work proactively to prevent crime. This is a challenge that police have where they need to try and predict where crime can occur and be prepared for this situation.
• Serial crimes can have a pattern and this pattern needs to be identified to crack the crime. For humans to track through thousands of crimes and identify a pattern is not so easy. This is where machine learning can be of use
• Certain locations are more prone to crime. Identifying such locations is a challenge. If police can identify such areas, it can help them predict possible places where crimes can occur andcan work to prevent such crimes. Police face charges of discriminating against minorities, whether ethnic or religious. The challenge before the police is to do their duty effectively without facing accusations of discrimination.
• Harmful online content is posted many a time. Certain types of music videos like drill videos are accused of being provocative and inciting violence. The challenge for the police is to handle threatening online content without infringing on the rights of people.

How the police can use machine learning effectively to achieve results?

The police can use machine learning effectively to resolve all challenges that are before them. The use of machine learning solutions can help in predictive policing, where they can prevent crimes and thus improve public safety. The following are some ways by which the police can use machine learning to achieve better results:

1) Pattern recognition

One of the most powerful applications of machine learning in policing is in the field of pattern recognition. Crimes can be related and may either be carried out by the same person(s) or may use the same modus operandi. The police can benefit if they are able to spot patterns in crimes. The data that the police get from crimes is essentially unstructured data. This data needs to be organized and sifted through to find patterns.

Machine learning can help do this easily. Machine learning tools can compare various crimes easily and generate a similarity score. These scores can then be used by the software to try and determine if there are common patterns. This is already being implemented by the New York Police Department. The tool has been used to crack cases effectively.

2) Predictive analytics

Another area related to machine learning that can help police is predictive analytics. This is a powerful application of machine learning that the police can use to achieve effective results. A tool that has predictive analytics features uses machine learning to help police in improving public safety. These tools focus on crime trends and are thus beneficial. When such trends are spotted, the police can proactively take action.

For example, when the system identifies a trend in a crime being committed in a particular area, the police can then allocate resources to that area so that they can proactively manage the situation and prevent a crime from occurring.

Another significant advantage of using predictive analytics is the benefit it offers for law enforcement officers. A police officer can be more efficient while using a predictive analytics tool. It will help the officer to have information about an area and crime trends in that area. The officers will be aware of each area and will also have sufficient information about crimes that have occurred.

3) Cybersecurity

Cybersecurity is an important area in today’s world. With the extensive use of internet everywhere, cybercriminals are targeting computer systems across the world. Cybersecurity is very important to not just to solve cases but to proactively prevent them. Cybersecurity can be enhanced through the use of machine learning. Tools that use machine learning can improve cybersecurity and proactively prevent crimes.

4) Enhanced public safety

Ensuring public safety is an important function of the police. This can be enhanced through the use of machine learning. Some tools that are being used in this regard are:

• Gunfire detection sensors can be used and they can detect instances of gunshots and triangulate the location. This can be done effectively through machine learning. Police can reach the trouble spot quickly even before anyone can call or raise a complaint.
• Use of machine learning in surveillance systems can help to recognize faces and this can help in solving and preventing crimes.
• A machine learning-based system can even predict if a person will commit a crime based on past data and trends. All these developments will aid the police in their work.

Machine learning solutions

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