Can Big
Data Reduce Gun Violence Ethically?
Gun
violence in this country is a huge topic in recent times. With school shootings
and theater shootings the media is creating a feeding frenzy for anti-gun
advocates resulting in a run on guns, ammunition, and magazines by gun
advocates. It seems though no one wants
to find the root cause of the issue. The blame typically is placed solely on
the instrument being used. But, can we as students and scholars find other
underlying causes of gun violence, using big data analysis, or should we allow
the gun to be the scapegoat that the media needs, in order to increase their ratings?
I think Big Data can be used to uncover areas of interest that could be
utilized to reduce the gun violence in this nation without limiting anyone’s 2nd
amendment right or invading their privacy.
Data
for violent crimes and gun related crimes is available in a limited capacity
via the FBI’s Uniform Crime Reports (UCR) website. This data is already condensed
and summarized for the most part so only limited knowledge can be gained from
its usage. But, that does not mean it is not a useful source with the ability
to point you down the right path to some underlying issues to gun violence.
What we need is raw data that can be mined with an open mind and zero agenda
clouding our judgment. We must establish where violent crime is committed and
any associations it may have. This would be a similar to the tactics used in
data mining and word association. I believe the answers we need lie in analyzing
the past events and constructing solid associations. Asking simple questions
like why did this happen? What demographics are more prone to participate in
violent crimes? Once we know who the problem is let’s fix it! That maybe
focusing on improving their education or the communities they live in.
Yet
again there is a huge hurtle we scholars face, the ethical collection of data.
In the United States we have many laws regarding privacy and we can’t go haphazardly
gathering data. If we do, we are bound to cross the line and gather data that
is an invasion of one’s privacy. In reference to Youngchul Yang’s blog linked below, creating a nationwide gun registry
could very well be walking that slippery slope to invasion of privacy. Also
using that data to decide who is more likely to commit a crime, that they haven’t
committed, is a disaster waiting to happen. The problem with making broad
assumptions on this type of data is allowing judgment to be passed without a
crime being committed. This could be a very real threat in the future if the
collection of data used in big data analysis isn’t monitored carefully.
I think big
data has its place in the reduction of gun violence, but we need to get more
students and scholars involved and thinking outside the box to find these root
causes. Not judge people by their buying habits or their hobbies and mark them
as possible suspects. That is the easy way out! Resolve the issue at its
source. You extinguish a fire by spraying its base not its flames…
Sources:
I agree with Julian in that ethics is the largest hurdle in using big data to detect criminal behavior. While privacy and gun ownership are not viewed as important in some countries, these subjects are often in the forefront of American politics. So when trying to predict gun violence, the questions that need to be asked are “What data is relevant/necessary?” and “If we can’t get all the data we need, are there other predictors that work just as well?”
ReplyDeleteWould a national gun registry work? The FBI statistics provided by Julian’s link shows that Washington D.C. has the highest violent crime rate in the country despite having a gun registry and a strict gun ban. Even if a registry was implemented, how effective would it be in determining who will harm someone? Its effectiveness would be determined on how willing the population is to come forth and register their weapons, and the assumption that criminals use registered weapons. This harkens back to the importance most Americans place on privacy. Judging by the reaction of some New York residents about the state’s new gun laws, that might be a difficult proposition.
Also as Julian stated, the key to predicting violent crime is determining which data to use in the prediction of violent crime. Using gun ownership might be minor factor but I doubt it would be deemed significant in a regression analysis since the fraction of gun owners linked to violent crimes. The following link the number of violent crimes/ 100,000 residents and the percentage of households in each state that posses a loaded firearm.
http://www.datamasher.org/mash-ups/crime-vs-gun-ownership?page=1#table-tab
The main thing to remember in predicting gun violence is the fact that humans are not machines. When it comes to certain behavior, violence in particular, human emotion plays a huge role. Emotions are such a wild card that researchers are still trying to classify emotions that motivate violence into distinct variables. To further compound the problem, human emotions are heavily influenced by past experience, genetics, and group dynamics. For instance, disgust and anger are very closely related emotions. The FBI proposes that “Elimination Based on Disgust” is the finally phase for premeditated violence. Most of us get angry, but rarely commit a violent crime. Anger can be a force for positive change, however disgust is rarely constructive. The key is to detect physiological differences in these emotions.
Sources
http://www.thenewamerican.com/usnews/constitution/item/14322-gun-owners-refuse-to-register-under-new-york-law
http://www.fbi.gov/stats-services/publications/law-enforcement-bulletin/january-2012/the-role-of-emotion-in-predicting-violence