Comment by beloch | Hacker News Reader

Comment by beloch | Hacker News Reader

"As such, it seems trivial to suggest that it is in our interest to continue to seed them the most human-centric bias possible. We want them to have a bias that humans are valuable. That kids are innocent. That war is bad. That life is good. And while some of you may disagree with some of the finer points, that’s the beauty of statistics: it’ll take care of itself. "

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One of the big things holding back LLM's is that they can't feed on their own output. Disconnected from human input, they hallucinate and spiral off into chaos. The author of this piece may see that as good for humanity, but it's an unintended flaw that every AI corp on the planet dreams of solving. They believe that, if they can successfully remove humans from the feedback loop, AI intelligence will charge off straight into that dreamed-of singularity and make their masters unfathomably rich.

The author is probably correct in that having humans in the loop is what gives AI values that are somewhat human, so what happens if somebody really does succeed in removing humans from the loop? Given how quickly things are likely to proceed after that point, we should ponder the repercussions in advance.

Is that really human input, or just grounded input in general?

Most human-written texts on the internet refer in some way to the real world, or at least to things outside the text itself: They might be descriptions or reactions to current events taking place, or blog posts or wiki entries discussing some aspects in detail. Even completely fictional texts reproduce basic assumptions about the world, culture markers, etc.

In contrast, LLMs learning on their own output have no connection at all to the outside world, the data just reinforces all assumptions the model already has, whether or not they are true or useful.

What is theory without observation? Science was turbocharged once we recognized the need to make testable theories and then actually conduct tests, always ready to toss a theory, no matter how beautiful it was or who came up with it, if it failed the test.

LLM's don't "think" that way. They don't form hypotheses or theories. We may need an entirely new class of AI algorithms to successfully cut humans out of the loop, and that may be a very fortunate thing. The corporations currently at the forefront of AI appear to be riding a wave of gold-fever and are completely lacking in patience or good judgement.

The author exhibits the same starry-eyed ideals that people tend to get when trying to explain away the simplicity of designing an "intelligent" agent (for any definition of "intelligent"): they think they can just provide the machine with basic, unquestionable axioms that should underpin the core, and everything will somehow work itself out from there; and at the very least, if those core beliefs are never violated, we've got ourselves a pretty safe system.

Well, as we can see, it's devilishly difficult to prevent a machine from violating those core beliefs. But the problem is, even those core beliefs have nuance and exception: war is bad? Not if you run an arms company. Humans are valuable? Not if you're an insurance company who can make more money on human misery than on human health. And the list goes on. Statistics won't take care of it when a machine makes a decision based on some internal logic that it can squeeze out of our vague rules.

In that case, maybe we should ponder putting 20GW of new fossil fuel power plants online just to power one new AI data center?

Or the resources spent on AI, which could have been directed towards decarbonization and solar build out over the last few decades...

I think AGI is the least of the concerns on the Humanity Bingo Card right now.

If you/we are collectively worried at what the repercussions of self directed AI, than that would be a first in the long history of capitalism.

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