This topic clearly touches a nerve with the HN community, but I strongly agree with you.
To be honest, I've been someone disappointed with the way AI/DL research has proceeded in the last several years and none of this really surprises me.
From the beginning, this whole enterprise has been detached from basic computational and statistical theory. At some level this is fine — you don't need to understand everything you create — but when you denigrate that underlying theory you end up in a situation where you don't understand what you're doing. So you end up with a lot of attention paid to things like "explainability" and "interpretability" and less so to "information-theoretic foundations of DL models", even though the latter probably leads to the former.
If you have a community that considers itself above basic mathematical, statistical, and computational theory, is it really a surprise that you end up with rhetoric about it being beyond our understanding? In most endeavors I've been involved with, there would be a process of trying to understand the fundamentals before moving on to something else, and then using that to bootstrap into something more powerful.
I probably come across as overly cynical but a lot of this seems sort of like a self-fulfilling prophecy: a community constituting individuals who have convinced themselves that if it is beyond their understanding, it must be beyond anyone's understanding.
There are certainly risks to AI that should be discussed, but it seems these discussions and inquiries should be more open, probably involving other people outside the core community of Big Tech and associated academic researchers. Maybe it's not that AI is more capable than everyone, just that others are maybe more capable of solving certain problems — mathematicians, statisticians, and yes, philosophers and psychologists — than those who have been involved with it so far.