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sexiest job in the 21st century” (Miller 2013). Despite budget constraints
created in part by failed programs inspired by the dot-com bubble of the
late 1990s and the inancial bubble that greeted the new century, dozens
of new programs have emerged at every level of higher education. Even
the usually subdued New York Times has caught the fever. Declaring data
scientists “the magicians of the Big Data era,” the newspaper describes their
many talents: “They crunch the data, use mathematical models to analyze
it and create narratives or visualizations to explain it, then suggest how
to use the information to make decisions” (ibid.). It is uncertain whether
they can also bring home the bacon and fry it up in a pan, but the Times
is satisied to transmit, with no critical relection, a promotional report
by McKinsey that forecasts the millions of jobs that the demand for data
scientists will create. It is remarkable that after the disastrous economic
catastrophes brought about by near-rapturous faith in the IT of the late
1990s, and in the big-data algorithms that helped bring the West to the
brink of a new Great Depression in 2008, educators continue to chase
after the next new fad. This time will be different. Myths matter. 4
A current exemplar of myth-building around big data is a 2013 book
by a pair of knowledgeable analysts whose breathless prose begins with
its title: Big Data: A Revolution That Will Transform How We Live,
Work, and Think . One of the characteristics of a good myth is its ability
to inoculate its story with what appears to be sober good sense in order
to achieve a degree of legitimacy before plowing ahead with the tall tale.
For the authors of Big Data this means putting some distance between
them and Chris Anderson: “Big data may not spell the 'end of theory,'
but it does fundamentally transform the way we make sense of the world”
(Mayer-Schönberger and Cukier 2013, 72). Here, we are encouraged to
question the implied hyperbole even as we adopt another, equally extraor-
dinary claim. For the authors, “the IT revolution is all around us” and it
is manifested not in the technology, but in information, which takes on
seemingly magical powers to change the way we know the world (ibid.,
77-78). This appears again when they turn to the method of choice in
big-data analysis, inding correlations: “With correlations, there is no
certainty, only probability. But if a correlation is strong, the likelihood of
a link is high.” They “demonstrate” this by asking us to observe the con-
nection between Amazon's book suggestions and those topics' appearance
on people's shelves (ibid., 53). Undeterred by the absence of anything
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