New Algorithm Predicts Crime Before Happenings

It has been tested in US cities of Atlanta, Austin, Detroit, Los Angeles, Philadelphia, Portland, and San Francisco. According to the researchers, “We report an approach to predict crime in cities at the level of individual events, with predictive accuracy far greater than has been achieved in past.”

The crime rate is getting higher than before. The police are very concerned as there is no way they can predict the intentions of the criminals. But we have good news for the police. A new algorithm has been devised which will help to predict the crime even before happening. That seems quite interesting, as this will help to plan beforehand.

Researchers and Scientists from the University of Chicago have been working to develop a new algorithm. This can predict future crime with 90 % accuracy within a range of 1000 feet. The older versions relied on the traditional neighborhood or political boundaries, which are usually biased. Oh, beware criminals! You can be next. You need to plan better. The data is collected by monitoring violent and property crimes.

It has been tested in US cities of Atlanta, Austin, Detroit, Los Angeles, Philadelphia, Portland, and San Francisco. According to the researchers, “We report an approach to predict crime in cities at the level of individual events, with predictive accuracy far greater than has been achieved in past.”

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Rather than using it for accuracy, rather it should be used to devise urban policies and policing strategies to address crime. According to Chattopadhyay, “We created a digital twin of urban environments. If you feed it data from what happened in the past, it will tell you what’s going to happen in the future. It’s not magical; there are limitations, but we validated it and it works really well. Now you can use this as a simulation tool to see what happens if crime goes up in one area of the city, or if there is increased enforcement in another area. If you apply all these different variables, you can see how the systems evolve in response.”

The researchers also added, “We acknowledge the danger that powerful predictive tools place in the hands of over-zealous states in the name of civilian protection, but here we demonstrate their unprecedented ability to audit enforcement biases and hold states accountable in ways inconceivable in the past.”

The algorithm shouldn’t fall in the wrong hands, other its credibility and usage will be compromised.

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