Peter Norvig, Google’s research director, offered an update to George Box’s maxim: “All models are wrong, and increasingly you can succeed without them.”
This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.
I assume all Scattertrons are on-board with thinking this is an incredibly naive position. At the moment I’m particularly impressed with Pat Sullivan’s “Spurious Genetic Associations” piece, which demonstrates precisely why numbers don’t speak for themselves. More data means… more plausible causal pathways. Moreover, the number of plausible causal pathways increases exponentially (or something like that) with the increase in the amount of data.
Here’s my concern, though: the google mania (demonstrated by Conley’s piece, which we’ve been bashing, as well as elsewhere in pop culture) does seem like a potent anti-intellectual trend: why think when you can count high? I found this to be the case, too, in the popular book The Wisdom of Crowds, for which Google is an important example. What that book finds exciting about Google is its apparent asystematicity; but this “works” only for particular, web-ish definitions of “works.” So… in the popular mind, how do we make this case?