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I agree with the sentiment (nothing new methodically) but have a thought: these methods were in the field of computer science and operations research (maybe). T
by wjnc 9y ago
I agree with the sentiment (nothing new methodically) but have a thought: these methods were in the field of computer science and operations research (maybe). The popularity of ML and data science is taking place in the same 20 yrs that every non-beta science is becoming more quantified. It takes a novel generation of researchers to combine the old with the new. ML's popularity, and ease of entry (in a broad sense, with tools and information easily available) is only helping the spreading.
- jl6 9y agoWhat is non-beta science?
- b34r 9y agoMy guess was “established” science, like something taught in schools.
- wjnc 9y agoSorry, that might be too local: Beta = natural science, alpha = humanities, gamma = social science. So my point is even humanities and social sciences are becoming more empirical (at least in subfields, and the retort that a lot of statistics got founded in humanities is well taken) and they are using the tools that are popular and widely known.