Big Data Is Great, but Don't Forget Intuition - NYTimes.com - 2 views
www.nytimes.com/...but-dont-forget-intuition.html
social science data prediction computer forecasting intuition
shared by Javier E on 30 Dec 12
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THE problem is that a math model, like a metaphor, is a simplification. This type of modeling came out of the sciences, where the behavior of particles in a fluid, for example, is predictable according to the laws of physics.
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In so many Big Data applications, a math model attaches a crisp number to human behavior, interests and preferences. The peril of that approach, as in finance, was the subject of a recent book by Emanuel Derman, a former quant at Goldman Sachs and now a professor at Columbia University. Its title is “Models. Behaving. Badly.”
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A report last year by the McKinsey Global Institute, the research arm of the consulting firm, projected that the United States needed 140,000 to 190,000 more workers with “deep analytical” expertise and 1.5 million more data-literate managers, whether retrained or hired.
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A major part of managing Big Data projects, he says, is asking the right questions: How do you define the problem? What data do you need? Where does it come from? What are the assumptions behind the model that the data is fed into? How is the model different from reality?
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Society might be well served if the model makers pondered the ethical dimensions of their work as well as studying the math, according to Rachel Schutt, a senior statistician at Google Research. “Models do not just predict, but they can make things happen,” says Ms. Schutt, who taught a data science course this year at Columbia. “That’s not discussed generally in our field.”
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the increasing use of software that microscopically tracks and monitors online behavior has raised privacy worries. Will Big Data usher in a digital surveillance state, mainly serving corporate interests?
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my bigger concern is that the algorithms that are shaping my digital world are too simple-minded, rather than too smart. That was a theme of a book by Eli Pariser, titled “The Filter Bubble: What the Internet Is Hiding From You.”