Photo by Paula Mariel Salischiker In “Full Employment“, my July 2020 column, I wrote, “I am an AI skeptic. I am baffled by anyone who isn’t. I don’t see any path from continuous improvements to the (admittedly impressive) ‘machine learning’ field that leads to a general AI any more than I can see a path from continuous improvements in horse-breeding that leads to an internal combustion engine.” Today, I’d like to expand on that. Let’s talk about what machine learning is: it’s a statistical inference tool. That means that it analyzes training data to uncover correlations between different phenomena. Your phone observes that every time you type “hey,” you usually follow it with “darling” and it learns to autosuggest this the next time you type “hey.” It’s not sorcery, it’s “magic” – in the sense of being a parlor trick, something that seems baffling until you learn the underlying method, whereupon it becomes banal.