I first heard it in an AI class as well. When I relate the story I usually give it as an anecdote of apocryphal origin. But I do love the story, because it br

I first heard it in an AI class as well. When I relate the story I usually give it as an anecdote of apocryphal origin. But I do love the story, because it brings into focus several issues: what do you actually want your classifier to learn? what does your training set actually teach? how do you know you've learned the right thing? Many times it seems like people go into these things hoping that the machine learning part will figure out things for them and relieve themselves of the problem of thinking hard about the problem. It doesn't. It only moves your problem over a bit and increases the difficulty. In fact this problem pops up even in pedagogy where the lessons people are taught actually train them to do the wrong thing (for example pilots responding to aircraft attitude upsets). The parable's lesson is a simplistic one, basically: "stop and think about what you're doing". But like other simple lessons about crying wolf or stitching in-time, it bears repeating.