‘metadata’ is a word used as an excuse to do what they want, it has no actual evaluated substance, the same as science (they label it science in order to be able to make it look any way they want)
Letters, The Economist Magazine May 24th 2014. pg 14
What is Big Data for?
SIR – I agree with Lexington (May 3rd) that excluding bias from data analyses is very difficult, as observed in 1974 by Richard Feynman. Even expert data scientists are hard pressed to understand data. However, the column made a common, though erroneous, link between correlations and causation by referring to “those vowing to ‘explain’ the world empirically” and to “high-minded empiricism”. There is no empiricism in Big Data.
Much harm is being done by people asserting causality as a consequence of data analysis. The results of data analytics are mere hypotheses that require empirical verification in the real world. Big Data’s pursuits of “what” should be symbiotically linked to empiricism’s pursuit of “why”, which would increase the real strength of data analytics and accelerate scientific discovery collaboratively with empiricism. Lexington, and voters, should always ask for verifying evidence that data analysis results are true in the real world.
Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology