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Comment by kalkin | Hacker News Reader

Relatedly, it'd be helpful if you could point to folks with good ML research credentials making a detailed case against x-risk. The prominent example of whom I'm aware is Yann LeCun, and what I've seen of his arguments take place more in the evopsych field (the stuff about an alleged innate human drive for dominance which AIs will lack) than the field in which he's actually qualified.

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TBH, I don't find LeCun particularly convincing. I think he's correct but not persuasive, if that makes sense.

Debunking AI x-risk is a weird thing to spend time on. There's really no up-side, and there aren't a bunch of rich people paying for Institutes and Foundations on Non-Breathtaking-Very-Boring-Safety-Research. Also, most of the arguments in favor of x-risk that lawmakers and laypeople find most convincing are unfalsifiable, so it's a bit like arguing against religion in that respect.

I don't think there are any public intellectuals in this space doing it well. I'm not sure what to make of that. For myself, I make the argument for focusing on concrete safety problems from within the agencies and companies that are allocating resources. I'm not gifted TED talker.

There's definitely an audience for debunking x-risk, but probably not one that attracts institutional funding. Being a tech critic in the mode of Timnit Gebru or Emily Bender will get you media attention, but I doubt it's lucrative. (And empirically the media ecosystem doesn't appear to incentivize being fair-minded enough to persuade a fence-sitter, either.)

(Not the OP) In this article Le Cun argues in very concrete technical terms about the impossibility of achieving AGI with modern techniques (yes, all of them):

Meta's AI guru LeCun: Most of today's AI approaches will never lead to true intelligence

https://www.zdnet.com/article/metas-ai-guru-lecun-most-of-to...

Edit: on second thought, he gets maybe a bit too technical at times, but I think it should be possible to follow most of the article without specialised knowledge.

I wouldn't describe most of what's in that interview as "very concrete technical" terms - at least when it comes to other people's research programs. More importantly, while it's perfectly reasonable for LeCun to believe in his own research program and not others, "this one lab's plan is the one true general-AI research program and most researchers are pursuing dead ends" doesn't seem like a very sturdy foundation on which to place "nothing to worry about here" - especially since LeCun doesn't give an argument here why his program would produce something safe.

You can ignore that, of course he'll push his research. But he never says that what he does will lead to AGI. He's proposing a way forward to overcome some specific limitations he discusses.

Otherwise, he makes some perhaps subtle points about learning hidden variable models that are relevant to modern discussions about necessarily learning world-models in order to best model text.

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