What could that even look like? In the extreme case this is like asking, "Why do I have to write programs, can't the computer just do what I tell it?". Writing

What could that even look like? In the extreme case this is like asking, "Why do I have to write programs, can't the computer just do what I tell it?". Writing the program is telling it what you want. In supervised machine learning, annotating the data is, instead. If you tell me, "Go to ebay and get me a list of the prices of washing machines", that sounds simple, but then I'm faced with some washer/dryer combo or some hand-crank contraption. These are things you didn't think of. I can either ask you, or take a guess and hand you something that needs to be cleaned up later. If I'm instead training a model, I need to encounter these tricky examples in order to ask you for a policy on them. If I'm collecting an unbiased sample of the training data, this could take a very long time. If there's some sampling strategy maybe it's faster, but there's still a minimum number of examples we need to think about, no matter what.