Professional Tetris players and people who classify pictures of cats and dogs.
Machine learning is not a mature or robust field. Real world applications are brittle and extremely narrow in scope. The past few years has seen a burst funding and hype, as a result of deep learning advancements, but that will gradually wane as all the low hanging fruit is picked. Many applications that are promising (like self-drive cars and medical classification) will face major regulatory hurdles. It will take a much more radical (and, frankly, unexpected) breakthrough before most humans have to worry.
Machine learning is not a mature or robust field. Real world applications are brittle and extremely narrow in scope. The past few years has seen a burst funding and hype, as a result of deep learning advancements, but that will gradually wane as all the low hanging fruit is picked. Many applications that are promising (like self-drive cars and medical classification) will face major regulatory hurdles. It will take a much more radical (and, frankly, unexpected) breakthrough before most humans have to worry.
I love to hear an alternate viewpoint.