Source: The New York Times By QUENTIN HARDY
The word “data” connotes fixed numbers inside hard grids of information, and as a result, it is easily mistaken for fact. But including bad product introductions and wars, we have many examples of bad data causing big mistakes.
Big Data raises bigger issues. The term suggests assembling many facts to create greater, previously unseen truths. It suggests the certainty of math.
That promise of certainty has been a hallmark of the technology industry for decades. With Big Data, however, there are even more hazards, some human and some inherent in the technology.
Kate Crawford, a researcher at Microsoft Research, calls the problem “Big Data fundamentalism — the idea with larger data sets, we get closer to objective truth.” Speaking at a conference in Berkeley, Calif., on Thursday, she identified what she calls “six myths of Big Data.”
Myth 1: Big Data is New
In 1997, there was a paper that discussed the difficulty of visualizing Big Data, and in 1999, a paper that discussed the problems of gaining insight from the numbers in Big Data. That indicates that two prominent issues today in Big Data, display and insight, had been around for awhile.
“But now it’s reaching us in new ways,” because of the scale and prevalence of Big Data, Ms. Crawford said. That also means it is a widespread social phenomenon, like mobile phones were in the 1990s, that “generates a lot of comment, and then disappears into the background, as something that’s just part of life.”
Myth 2: Big Data Is Objective Read the rest of this entry »