Social scientists at the University of Chicago developed an artificial intelligence-based algorithm that can forecast crime in urban areas up to a week in advance.
Unlike other problematic algorithmic predictions that look at crime as emerging from hotspots and spreading to other areas, their algorithm analyzes previous crime reports along with many other factors. It divides a city into 1,000 square feet tiles. It then uses the historical data on violent and property crimes to predict crime likelihood in Chicago with 90 percent accuracy.
The model was also used to predict crimes in eight cities in the U.S. and worked well in those scenarios as well. These cities include big names like Los Angeles, Atlanta, and Philadelphia.
Will this new development in crime forecasting prove beneficial in increasing police efficiency and preventing recurring crimes? Please share your thoughts in the comments section below.