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Consider that, not long ago, most AI experts knew for a fact that neural networks were a failed avenue. Consider that, in 2013, most of the top names in computer vision were saying that the nascent success of DL might be just a fluke. And remember the debates about local minima?
In general, I'm also not a fan of the idea of an "expert". It makes it sound like there's some threshold of knowledge beyond which you know it all, you've made it (perhaps the threshold is when you reach full professorship). I don't think that's how it works.
If someone tells you they're a top expert, a pioneer, the main thing they're an expert at is playing status games. The same people will probably also try to demean those they feel are in competition with them, because that's how status games work.
As for me, I'm just someone who's been trying to learn as much as possible (not just about AI). That's how I'd define myself: someone who gets excited about stuff and learns about it. If there's an "expert threshold", I hope I never reach it.
"Science is the belief in the ignorance of experts."
This is helpful certainly but I think it helps to have some measure of specific expertise in an area, rather than nothing. It doesn't help to use labels such as "expert" as you've said, because of the changing nature of tech these days
“Everyone is an expert” and “no one is an expert” are both unhelpful. There is a useful definition in there. All of this has far more to do with the (im)maturity of the field than definitions of words.
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