| This perspective makes sense pragmatically, but in philosophical terms it’s a little absurd. Going back to Turing, the argument was for true, human creativity. The claim was that there is no theoretical reason a machine cannot write a compelling sonnet. After spending the better part of a century on that problem, we have made essentially zero progress. We still believe that there is no theoretical reason a machine cannot write a compelling sonnet. We still have zero models for how that could actually work. If you are a non-technical person who has been reading popular reporting about ML, you might well have been given the impression that something like GPT2 reflects progress on the sonnet problem. Some very technical people seem to believe this too? Which seems like an issue, because there’s just no evidence for it. Maybe a larger/deeper/more recurrent ML approach will magically solve the problem in the next twenty years. And maybe the first machine built in the 20th century that could work out symbolic logic faster than all of the human computers in the world would have magically solved it. There was no systematic model for the problem, so there was no reason to conclude one way or another, just as there isn’t any today. ML is a powerful metaprogramming technique, probably the most productive one developed yet. And that matters. It’s just still not at all what we’ve been proposing to the public for a hundred years. To the best of our understanding, it’s not even meaningfully closer. And that matters too, even if Siri still works fine. |