But that's the thing: they didn't. Instead, they called them "neural networks". It wasn't random.
It feels like part of the field now wants to pretend it was never about how to make a machine think. "No, we're only doing abstract maths, only going on self-contained explorations of CS theory." Yeah, right. That feels like a reaction to the new wave of AI hype in business. Now that the rubes are talking about thinking machines again, better distance themselves from them, lest we be confused for those loonies.
Thing is, the field was always driven in big part by trying to catch up with nature. It took inspiration from neuroscience, much like neuroscience borrowed some language from CS, both for legitimate reasons. A brain is a computer. It's precisely where the CS and neuroscience have an overlap - they're studying the same thing, just from opposite directions. It's just silly to play the "oh my field is better and your field doesn't know shit" game.
> Decision trees are called 'trees' for, more or less, the same reason.
Decision trees are called after the data structure, which is a way to express a mathematical object, which is older than CS and got that name from... who knows, but my money is on "genealogical tree", which itself is called a "tree" because people back then liked to tie everything to trees (symbol of growth) and flowers and cute animals (symbols of making babies).
The field inherited "trees" from the past. "Networks", too. But "neural" - that was a modern analogy the field itself is responsible for.
