Probably stems from the foundational misnomer of “artificial intelligence” (which glamorizes the algorithm) compared with, say “data-driven algorithms” which em

Probably stems from the foundational misnomer of “artificial intelligence” (which glamorizes the algorithm) compared with, say “data-driven algorithms” which emphasizes both aspects suitably. AI might have been a passable term in the era of rule-based expert systems, but both “AI” and “ML” are particularly misleading terms (when applied to modern data-heavy methods), leading to consequences like that pointed out in the article. Further, glossing over the importance of data to emphasize the algorithms is not accidental, given the subject’s roots in CS, and the rhetoric used to promote the field. The sub fields where it plays out differently are those which have a healthy respect for the prices of data gathering.