Data mining, formerly called Knowledge Discovery in Databases (KDD), is the activity of creating non-trivial knowledge suitable for action from databases of vast size and dimensionality. From the mid-1960s to the late 1990s, data mining moved from a disparaged, dubious sort of statistical work—“fishing” or “dredging”—to become what its practitioners proclaim to be an utterly transformative technology.
According to KDD advocates, traditional scientific approaches to data simply could not keep up with the volume of data and multidimensionality possible thanks to computers. Using traditional and digital humanities methods, I look at how stories of technologically determined emergence were crucial to the legitimization of data mining in authorizing the loosening and partial abandonment of the disciplinary and epistemological values of its predecessor disciplines, statistics and machine learning.
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