It turned out that some things were just too hard to really understand. The weird thing is when you realize that actually we never understood how to do these t

It turned out that some things were just too hard to really understand. The weird thing is when you realize that actually we never understood how to do these things. People doing them are as competent as they need to be AND good storytellers/presenters about how they "know" what they're doing. Trying to tell a computer how to unambiguously do these tasks only revealed that nobody actually knows how to do them. This is also why a lot of business logic software is a lot more crappy than it seems like it ought to be. For sure some of it is written by people who don't know how to design a good software product. But there's also a lot of it that can't be made well because the people asking for it to be made don't understand (on like a logical or specification level) what their job actually is. If machine learning is a half-arsing industry, then it's only there because every industry that machine learning is attempting to augment is also an industry that is half-arsing. EDIT: And I think it's worth mentioning that I very well may owe my life to one of these "half-arsers" that I'm talking about. He found and removed a precancerous mole. The tests came back showing pre-basal cells (iirc). I asked a lot of questions about how he was able to identify the mole as problematic (and he saw it right off the bat even though my general practitioner and myself ignored it) and he really wasn't able to give a satisfying answer that didn't also identify other moles he said were (and have been) safe. He just knew it was bad and he was right.