For an example in CS, we currently use machine-learning algorithms that work very well in practice. However, why they work so well is still unclear in many cases (although we are making progress).
I find it fascinating that describing an automated learning process is so much easier than manually teaching. Once trained, looking inside a model to gather information about how it comes up with an answer to a question is somewhat similar to doing exactly that with a real brain.