I might interpreting over-hyped in a different way than you are then. By over-hyped I don't really mean that something is bad. Machine Learning is awesome and has solved a lot of problems that were previously, dare i say, unsolvable.
What I mean with over-hyped is that it, in many ways, have started to be used as a buzzword. It is a thing that startups instantly put in their sales pitch even though they might use it in the smallest and least significant part of their actual service. Even worse is when ML is crammed in to a project that doesn't really warrant for it. Working for an agency I have even had clients saying "We want to solve this using machine learning" when there are solutions that would have done the work better.
This of course does not mean that machine learning is bad or has failed. It just means that it is hyped and sometimes misunderstood by a lot of people working in the industry.
What I am saying is not
"over-hyped = Bad"
"over-hyped = People sometimes use it only because there is hype around it".
Oh I totally agree with the first impretation though. I think Machine Learning is absolutely terrible. Even if we solve the issues around climate change, AI research will inevitable bring the end of humanity and needs to be stopped.
Do you mean because of strong AI and the rise of the machines, or privacy concerns, or something else? I probably agree with all of your concerns at least somewhat, but even if we avoid the research heading in those directions, ML is still fundamentally important. ML is a very field that covers everything from data compression algorithms to cyber security to, as I mentioned, interpretation of scientific datasets. We would honestly never have progressed past the tech of the 70s without ML
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