Solving Crimes, AI way!

Over the past few decades, most of the countries have allocated larger and larger shares of their budgets towards law enforcement. As per Forbesresearch, U.S. collectively spends $100 billion a year on policing and a further $80 billion on incarceration. In order to ensure effective utilisation of funds, and find innovative ways to crime management, governments in collaboration with private firms are increasingly looking to reduce and prevent crime and to more quickly respond to crimes in progress.

The idea behind many of these projects is that crimes are relatively predictable; it just requires being able to analyse a massive volume of data to find patterns that are useful to law enforcement. This kind of data analysis was technologically impossible a few decades ago and was part of science fiction as depicted by American sci-fi crime drama series "Person of Interest" in which computer programmer develops a supercomputer for the federal government which can predict and identify people planning terrorist acts.

However, with recent developments in machine learning, it is now practically possible to build AI-based products for crime resolution. For example,ShotSpotter uses smart city infrastructure to triangulate the location of a gunshot. It can alert authorities in effectively real-time with information about the type of gunfire and a location with accuracy up to 10 feet. This system has been in use in over 90 cities including New York, Chicago, Cape Town etc. On the other hand, Hikvision, a Chinese camera producer, collaborated with Intel to create cameras which can run facial recognition to search for potential criminals or missing people, and automatically detect suspicious anomalies like unattended bags in crowded venues. This has resulted in a 65% drop in crime rates in Sea Point, South Africa following the introduction of their cameras system.

While Predpol is using big data and machine learning to predict when and where crime will take place. In Washington, a 22% drop in residential burglaries has been reported after adopting this system. Similarly, Cloud Walk Technology is predicting if an individual will commit a crime before it happens to help the government use advanced AI to find and track individuals. The system will detect if there are any suspicious changes in their behaviour or unusual movements. For example, if an individual seems to be walking back and forth in a certain area over and over indicating they might be a pickpocket or casing the area for a future crime.

Though AI has shown its potential in crime detection, the ethical boundaries of AI are still unclear, compelling law enforcement authorities to tread carefully. Defining the scope and boundaries of AI, which includes personal data collection, will indeed prove to be a complex task. However, as AI represents a promise of a new paradigm in crime management, there is a strong case for pursuance across various branches of crime management.

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This article has been published in Bank of Baroda's FinTech Newsletter "FinTalk"

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