In his article “What Data Can’t Do”, David Brooks discusses positive and negative aspects or “strengths and limitations” of data analysis and how one’s decision might depend on it. In the beginning author mentions the story of the chief executive of a large bank, who had to decide whether to relocate his business from crisis-driven Italy somewhere else, or stay, despite of unfavorable economic conditions. He decided to stay, notwithstanding that data suggested him to do otherwise. Staying for him meant to gain something more important than profits – to obtain people’s (both potential clients and present bank’s employees) recognition of his bank as a reliable one.
Data analysis is crucial part of making a decision, but pretty often it is not enough to come up with the answer to a certain problem. Sometimes relationships between people, business partners, for example, or family members are too complicated to rely on data to analyze given situation. Love, hatred, trust, fear and so on frequently are much more important factors for taking a decision. Analyzing the data is very powerful tool; it helps “compensate for our overconfidence in our own intuitions”, it can reduce risks of taking the wrong direction, but there are moments when data suggestions should be considered as a secondary option.
For example, data cannot accept into consideration social norms of society, while human’s brain, on contrary, cannot cope with big arrays of simple calculations. Well, people invented computers, so there is no need for brain monotonously calculate outcomes or collect data, on the other hand, data-collecting computers, whatever potent they might be, cannot execute certain decision without human interference. I agree with author that in some situations human’s brain, its analytical abilities and common sense are only things that people need to act right. Human decisions in contrast to computer based analysis of the data, capable of acting nonlinearly: even for biggest complicated problems brain could find simple and fast solution. This reminds me a novel by Phillip K. Dick “Do Androids Dream Of Electric Sheep” when empathy test is the only way to distinguish androids from humans. “Although androids can deal very well with the data analysis they don’t have empathic responses and thus are considered machines”
In “Big Data On Campus”, M.Parry describes a situation in several U.S. higher education institutions like: Arizona State University, Rio Salado Community College or Austin Peay State University, where degree-monitoring systems suggest students which courses to take or which major to follow relying on student’s activity on the Web. Whatever students do online leave traces which are like “digital breadcrumbs”. Computers analyze specific information, making e-advising software able to predict student’s grades, increase probability to get to the finish successfully with less efforts and so on. After all of the student’s activities are analyzed the verdict is made: Hey you, do you like chemistry and biology? Forget it, algorithm that predicted your possible future says that you have to consider wood carving instead! No wonder that for students who run off-track, the outcome could be regrettable. It could lead to dropping the major or taking more semesters to accomplish your degree. Despite of the convenience, these kinds of interventions into student’s life have yielded controversial results.
Another problem is that data is tend to get accumulated, or ”creates bigger haystacks” without any resolving. It is getting more and more complicated for people to deal with massive amounts of information. That is true that this way we can find more statistically significant correlations, but it doesn’t simplify original problem at all and make it more difficult for people, sometimes even stumping us.
There are more points in the article that show weak sides of data analysis. Many of them merge into idea that data collecting techniques don’t take into consideration what kind of data do they actually collect. Quantitative characteristics are more important than quality of the data. Nevertheless, the “big data” is a great and useful tool, and people who consider themselves professionals, have to figure out the proper way of using it in particular situation.
Works cited:
B. R. Sachs. “Consumerism and Information Privacy”. Virginia Law Review. March 1, 20011. SSRN: http://ssrn.com/abstract=1373123
M. Parry. “Big Data On Campus”. New York Times. July 22, 2012. http://www.nytimes.com/2012/07/22/education/edlife/colleges-awakening-to-the-opportunities-of-data-mining.html
