The negative comments here are disappointing. ML is a fantastic tool for science, where it can propose a model that works as a starting point for getting to a m

The negative comments here are disappointing. ML is a fantastic tool for science, where it can propose a model that works as a starting point for getting to a model that works AND that you can understand. This is quite common in physics, for example, where people are happy to build elaborate experiments just to poke at the universe in weird ways. An ML algorithm is a theorist's particle accelerator where they can treat it as something to be explored to gain insight. The reason people are pissed about this is that we're doing this breadth-first, because the incentives make it that way. People are right to be concerned if we never get back to deeper analyses, but I'm not at all concerned. At some point the low hanging fruit will be gone and every scientific community will be better off having these new results. As we get better at probing the black box, and we will because there's a lot of value behind doing so, we will start to shift back to the deeper questions.