Wednesday, March 20, 2013

Could Big Data Analytics be Used to Prevent Crimes?


We have discussed a long list of the many benefits that big data analytics can bring to society. The benefits include improving healthcare, the economy, and even helping track down criminals. How far, though, is too far? Where do we stop relying on algorithms and equations and start relying, once again, on our intuition?

The movie, Minority Report, is a great example of how big data analytics could lead to predictions that penalize people. The movie is based on the idea of law enforcement using “visions” of the future to imprison future criminals. In the United States, this idea has already started taking place. The parole boards of more than half of the states use predictions based on data analysis to factor into the decision of whether or not to release an inmate from prison. Some areas use “predictive policing”, which is the term for using big data analytics to lead law enforcement to areas where a crime is likely to happen.

It is believed that this is not the end of big data analytics in law enforcement, rather, it is just a stepping-stone to preventing crimes by predictions. The US Department of Homeland Security is even heading a project called FAST (Future Attribute Screening Technology) that monitors individuals’ vital signs, body language, and other physiological patterns to try to identify terrorists.

While using big data to stop bad things from happening is attractive, there is a thin line before reaching the concept of punishing people for things they have not done. It has been said, and rightfully so, “To accuse a person of some possible future behavior is to undermine the very foundation of justice: that one must have done something before we an hold him accountable for it.” I am sure that at one time or another we have all had a bad or mean thought, but that does not mean that we should be punished for something that just ran across our mind! In another respect, we must think about the idea of “innocent until proven guilty”. That is one of the most fundamental concepts of fairness.

We need to remember that being able to make our own choices and being able to react in real time (on our own, without an algorithm) is something that we cannot lose as humans. We cannot forget that, while big data can be a wonderful tool, we need to live in a trusting world that appreciates freedom.



**I am not including this video because I am trying to be political. It is just interesting to see the relationship between Minority Report and how it could apply to real world situations. 


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2 comments:

  1. Awesome post Bri. Yea, I completely agree with what you've said. When we start to extrapolate to what this could become, the future seems a bit scary especially when we're dependent on probability (no matter how precise).

    One of the things that struck me the most is how one can validate any of this. I read an article over the summer about how law enforcement entities in dangerous metropolitan cities were using predictive analytics to identify where commonalities existed for certain crimes. What was interesting was how they quantified their findings. As police officers, one of their best weapons is simply their presence. If a police cruiser is around, chances are a crime is less likely to be committed. So, after specific locations were identified the presence of the police force in these locations was increased. Law enforcement saw a dramatic decrease in specific crimes such as breaking and entering as well as theft, which intuitively makes sense. However, like Brianna pointed out, to what extent is this valid? How can we validate that this is a good model? If we say that the decrease in these crimes is a sign that it works, are we stretching the truth?

    I'd say that there are absolutely no ethical grounds to charge or even momentarily incarcerate or impede on someone's rights based solely on a predictive model. The extent that I think these tools should be used is in cases where non-intrusive (such as increased police presence) means are conducted.

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  2. Few weeks ago, I saw a very interesting topic which is related to crime rate. Last year, IBM sent hundreds of thousands of their high level managers and experts to many cities around the world to help them implement big data. What is the topic? How to decrease crime rate. Taipei, the capital of Taiwan, was also honored to be one of the elected cities. There are so many monitoring devices such as red light camera and movement recorders set up on the road. However, Taiwanese police officers do not have big data training or expertise to deal with massive data day by day. They didn't use these devices well. IBM experts help them to build a complete database, and teach these officers to use it. By analyzing the dramatic huge data, now Taipei police officers can easily trace where the incidents happened and where the incidents may happen in the future. Big data does use to prevent crimes, and it is doing well.

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