Big Data Analytics – Crime prevention
How low
can crime rates go? When is low enough? The answer is never. Although the crime
rates in the big U.S. cities have been declining the last 20 years, but the law
enforcement agencies are never satisfied no matter how low they go. Big
cities such as Baltimore and Philadelphia have used predictive analysis tools
for law enforcement. These predictive analysis tools promises to “reduce the
homicide rate by predicting which prison parolees are likely to commit murder
and therefore receive more stringent supervision,” according to Wired.
This idea is to heavily rely on the Big Data predictive tools and capabilities
rather than on a parole officer’s instincts and regulations to determine which parolees
are most likely to commit homicide.
When a
parolee is released on probation and they are supervised by an officer, the
officer has to determine how much supervision the parolee needs. The creator of
this algorithm for predictive analytics, Richard Berk, had an interview
with ABC News in 2010. Mr. Berk is a professor at the University of
Pennsylvania. He has also expounded his latest version of software to identify
the individuals most likely to commit crimes other than murder. As the software
is being used more and predictions are being made, the accuracy of these
predictions will be monitored. If they prove to be successful, the analytics
software could move into other areas including influencing sentencing
recommendations and bail amounts.
Many
believe that it is impossible to predict a rare event like a murder. Mr. Berk
stated “It’s like trying to find the needle in the haystack.” However with new
advances in Big Data Analytics, they can now sift through that haystack more
quickly and more accurately than ever. Berk’s software tool examines
approximately 24 variables, from criminal record to geographic location. They
type of crime, and more importantly, how old was the individual when they committed
the crime, which were two of the most important predictive variables. “People
assume that if someone murdered then they will murder in the future,” said
Berk. But what really matters is what that person did as a young individual. If
they committed armed robbery at age 14 that’s a good predictor. If they
committed the same crime at age 30, that doesn’t predict very much.”
Many
people have made reference to Mr. Berk’s software tool with the Tom Cruise
movie “Minority Report.” Mr. Shawn Bushway, a professor of criminal justice at
the State University of New York at Albany says that Mr. Berk’s scientific
answer leaves policymakers with difficult questions to answer. By labeling one
group of inmates and parolee’s as high risk, they will be monitored more often
and hopefully decrease murders, which the potential victims should be happy
about. But on the flip side, for inmate rights advocates, that are tantamount
to harassment, “punishing people who, most likely, will not commit a crime in
the future,” said Bushway. “It comes down to a question of whether you would
rather make these errors or those errors,” said Bushway.
Other
cities have begun to use software to create predictive models by analyzing
crime and arrest data including Memphis with their IBM
Blue CRUSH (Criminal Reduction Utilizing Statistical History). According to
IBM, the CRUSH software reduced serious crime by more than 30 percent,
including a 15 percent reduction in violent crimes, over a four year period.
The Memphis Police were able to diagnosis crime “hot spots”, so they could
allocate more resources and deploy more personnel and increase the public’s
safety in these areas.
It is
important to keep the integrity of the justice system. However if we are already
spending time, money and resources to keep up with released parolees, we need
to shift some focus and attention on possible repeat offenders and offer them
extra guidance and assistance to hopefully negate a future violent crime. How
much is one life saved worth?
Other interesting articles include:
I didn't look at the recent blog posts before I just posted something about this same topic myself. It seems like we had the same idea! This is definitely an interesting topic. There seems to be a thin line between using predictive analysis for preventing crimes and using the analysis to punish "innocent" people. I think that some of the methods are definitely accurate if used correctly, such as the basic idea of identifying areas with high crime rates to locate future criminals, but it is hard to say when the predictions are taken too far.
ReplyDeleteJason and Brianna,
ReplyDeletePlease check: http://www.nij.gov/. You may find additional info there.
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