Predicting and preventing burglaries though statistical models in Indio, California

In January 2011, I wrote about how Santa Clara, California was going to use statistical models to predict where crime would take place and then deploy police accordingly. Another California community, Indio, is going down a similar route to reduce burglaries:

The Indio Police Department with the help of a college professor and a wealth of data and analysis is working on just that — predicting where certain burglaries will occur.The goal is to stop them from happening through effective deployment or preventative measures…

The police department began the Smart Policing Initiative a year ago with $220,617 in federal funding from the U.S. Department of Justice…

Robert Nash Parker, a professor of sociology at the University of California, Riverside and an expert on crime, is working with Indio.

On Friday, he shared his methodology for tracking truancy and burglary rates.

He used data from the police department, school district, U.S Census Bureau and probation departments, to create a model that can be used to predict such daytime burglaries.

Nash said that based on the data, truancy seems to lead to burglary hot spots.

A few issues come to mind:

1. Could criminals simply change up their patterns once they know about this program?

2. Do approaches like this simply treat the symptoms rather than the larger issues, in this case, truancy? It is a good thing to prevent crimes or arrest people quickly but what about working to limit the potential for crime in the first place?

3. I wonder how much data is required for this to work and how responsive it is to changes in the data.

4. Since this is being funded by a federal agency, can we expect larger roll-outs in the future? Think of this approach versus that of a big city like Chicago where there has been a greater emphasis on the use of cameras.

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