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.

Finding the right model to predict crime in Santa Cruz

Science fiction stories are usually the setting when people talk about predicting crimes. But it appears that the police department in Santa Cruz is working with an academic in order to forecast where crimes will take place:

Santa Cruz police could be the first department in Northern California that will deploy officers based on forecasting.

Santa Clara University assistant math professor Dr. George Mohler said the same algorithms used to predict aftershocks from earthquakes work to predict crime.”We started with theories from sociological and criminological fields of research that says offenders are more likely to return to a place where they’ve been successful in the past,” Mohler said.

To test his theory, Mohler plugged in several years worth of old burglary data from Los Angeles. When a burglary is reported, Mohler’s model tells police where and when a so-called “after crime” is likely to occur.

The Santa Cruz Police Department has turned over 10 years of crime data to Mohler to run in the model.

I wonder if we will be able to read about the outcome of this trial, regardless of whether the outcome is good or bad. If the outcome is bad, perhaps the police department or the academic would not want to publicize the results.

On one hand, this simply seems to be a problem of getting enough data to make accurate enough predictions. On the other hand, there will always be some error in the predictions. For example, how could a model predict something like what happened in Arizona this past weekend? Of course, one could include some random noise into the model – but these random guesses could easily be wrong.

And knowing the location of where crime would happen doesn’t necessarily mean that the crime could be prevented.