As I have written on more occasions than I care to recall the term “machine learning” is rife with problems. The term itself is composed of words that when combined in that order result in a logical contradiction and is therefore nonsense. Another way it can be said is that machine learning is logically impossible. To put it as simply as I think it can be, machines can not learn. This is not some anti-tech tirade or unhinged rant though I have been known to publish some of those. Rather it is just an observation of the facts of the matter if you look up the words ‘machine’ and ‘learning’ in any dictionary, accept them as correct (as you must if you believe in the sanctity of language and hope to use it to convey meaning) and then combine them. The definition of that combined term is a logical contradiction unless you suppose that in combining the words to create the term you have also altered the meaning of one or both of them. Of course you are free to do this just as I am free to call bullshit on you for doing so.
I have been cogitating for a long time on a possible term that one could substitute for machine learning that would avoid all those problems, convey the meaning I think most people want to convey when they use the term, and is technically accurate and more precise. The best I have come up with so far is
neuroarchitecture inspired computing (NiC).
I realize It does not exactly roll off the tongue but it does have the advantage of forming a rather neat three letter, memorable acronym.
It is still less precise than I would like. Neuroarchitecture for example does not convey the fact that most people use the term machine learning to suggest learning like a human does with a human brain. Neuro could refer to any brain or neurosystem from any animal. Also, it is too strong in the sense that it implies that our understanding of how the brain works is settled science, when this is far from the case. This is another one of my beefs with machine learning. It suggests that we know enough about how learning works in ourselves that we now have built machines that can replicate that process. This is most definitely not the case. How the brain/a person learns is still hotly debated and far from settled. There are many theories but none are without controversy or critics. This is exactly why the inclusion of the word “inspired” is so important in the term NiC. Its use conveys a hint of uncertainty which I think is totally appropriate given how little we know about how brains/people actually learn. Overall I would rate it as acceptable but not great. Guess I need to keep thinking.