A couple weeks ago I was at the New York Philharmonic. The conductor, critically-acclaimed Alan Gilbert, and the piano soloist, Emanuel Ax, “broke the fourth wall” and explained Schoenberg’s Piano Concerto to the audience before playing it. They described Schoenberg’s 12-tone technique for composing music as: the composer selects a range of 12 notes and must use each note at least once before being allowed to repeat. Gilbert described the 12-tone technique as as an “organizational rule” (“Algorithm!” I thought).

Then Gilbert went on to say (and I wrote this down) “The 12-tone technique has been mis-applied by lesser composers…Great composers are in control of technique.” (“Lesser data scientists!” I thought.)

I took this all as an analogy for using machine learning algorithms. Don’t be incompetent! In the hands of lesser data scientists, the results will be unpleasant-“unpleasant” in the context of Data Science means anywhere from “meaningless” to “disastrous”. The heart of the problem of course is: no one thinks they’re incompetent.