> I have never been to Nicaragua, so....limited relevance Ok, that's probably some sort of error. > you'd think they could do slightly better It depends on h

> I have never been to Nicaragua, so....limited relevance Ok, that's probably some sort of error. > you'd think they could do slightly better It depends on how they made their model. With machine learning, it's easy to build something that does improve the whatever high-level metric they were tying to optimize (like "revenue") , but gives essentially random results for many individuals. This is especially true for any anything that wasn't fully covered in the training data/; a handwritten digit recognizer may work wonderfully on average, while giving random results random output when presented with anything that wasn't covered by the MNIST dataabsse. Sometimes this can be especially fragile[1]! [1] https://medium.com/@ageitgey/machine-learning-is-fun-part-8-how-to-intentionally-trick-neural-networks-b55da32b7196 https://medium.com/@ageitgey/machine-learning-is-fun-part-8-...