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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.
Real experts don’t identify themselves as experts. We mistake excellence and expertise for perfection and infallibility. That is the root cause of many problems.
At some point, people go from being interested in "what is right" to "who is right"
That point is the moment of grant submission. A story: In 1986-7, I took John Hopfield's class. I then went to IJCNN (San Diego) and watched countless speakers start talk with "When I proved this, before Hopfield, I..." All grant seeking. I left ML/AI for 25 years after that.pic.twitter.com/gXnMbGsM3t
So... a good rule of thumb would be to listen to those that are demeaned by the "top experts" and don't bother to play their status game?
I disagree. I think it’s fine to identify as an expert. Then you are saying “take your best shot, there’s nothing I shouldn’t be able to answer”. It’s the ones who identify as an expert and then can’t defend a position with a simple testable numeric model to be wary of.
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