If you asked me to describe the rising philosophy of the day, I’d say it is data-ism. We now have the ability to gather huge amounts of data. This ability seems to carry with it certain cultural assumptions — that everything that can be measured should be measured; that data is a transparent and reliable lens that allows us to filter out emotionalism and ideology; that data will help us do remarkable things — like foretell the future.
First, the revolution isn’t really in data, it’s in analysis. Most of the innovation in the last 15 years or so has come from the analysis side. Think PageRank: crawlers already existed, but it was the clever analysis of the raw data that made it valuable.
Second, I’m pleasantly amused by Brooks’s wariness of cultural assumptions. Even the most quantitative of scholars has those areas where quantification unsettles the nerves (ask quantitative academics about teaching evaluations if you want a sense of this). And, in general, quantitative scholars advance arguments in support of data on qualitative grounds. Gelman’s blog is rife with examples of (what he calls) “qualitative” or “sociological” evidence of some point about research. This is hardly a criticism since to evaluate the effectiveness of data-driven approaches with a data-driven approach would either be tautological or (at best) unpersuasive to data skeptics.
Of course, as Brooks outlines in his column, the best arguments for quantitative approaches are found in studies themselves.