Comment by root_axis
2 days ago
> They are designed to predict human behavior in text
At best you can say they are designed to predict sequences of text that resemble human writing, but it's definitely wrong to say that they are designed to "predict human behavior" in any way.
> Unless consciousness serves no purpose for us to function, it will be helpful for the AI to emulate it
Let's assume it does. It does not follow logically that because it serves a function in humans that it serves a function in language models.
Given we don't understand consciousness, nor the internal workings of these models, the fact that their externally-observable behavior displays qualities we've only previously observed in other conscious beings is a reason to be real careful. What is it that you'd expect to see, which you currently don't see, in a world where some model was in fact conscious during inference?
> Given we don't understand consciousness, nor the internal workings of these models, the fact that their externally-observable behavior displays qualities we've only previously observed in other conscious beings is a reason to be real careful
It doesn't follow logically that because we don't understand two things we should then conclude that there is a connection between them.
> What is it that you'd expect to see, which you currently don't see, in a world where some model was in fact conscious during inference?
There's no observable behavior that would make me think they're conscious because again, there's simply no reason they need to be.
We have reason to assume consciousness exists because it serves some purpose in our evolutionary history, like pain, fear, hunger, love and every other biological function that simply don't exist in computers. The idea doesn't really make any sense when you think about it.
If GPT-5 is conscious, why not GPT-1? Why not all the other extremely informationally complex systems in computers and nature? If you're of the belief that many non-living conscious systems probably exist all around us then I'm fine with the conclusion that LLMs might also be conscious, but short of that there's just no reason to think they are.
> It doesn't follow logically that because we don't understand two things we should then conclude that there is a connection between them.
I didn't say that there's a connection between the two of them because we don't understand them. The fact that we don't understand them means it's difficult to confidently rule out this possibility.
The reason we might privilege the hypothesis (https://www.lesswrong.com/w/privileging-the-hypothesis) at all is because we might expect that the human behavior of talking about consciousness is causally downstream of humans having consciousness.
> We have reason to assume consciousness exists because it serves some purpose in our evolutionary history, like pain, fear, hunger, love and every other biological function that simply don't exist in computers. The idea doesn't really make any sense when you think about it.
I don't really think we _have_ to assume this. Sure, it seems reasonable to give some weight to the hypothesis that if it wasn't adaptive, we wouldn't have it. (But not an overwhelming amount of weight.) This doesn't say anything about the underlying mechanism that causes it, and what other circumstances might cause it to exist elsewhere.
> If GPT-5 is conscious, why not GPT-1?
Because GPT-1 (and all of those other things) don't display behaviors that, in humans, we believe are causally downstream of having consciousness? That was the entire point of my comment.
And, to be clear, I don't actually put that high a probability that current models have most (or "enough") of the relevant qualities that people are talking about when they talk about consciousness - maybe 5-10%? But the idea that there's literally no reason to think this is something that might be possible, now or in the future, is quite strange, and I think would require believing some pretty weird things (like dualism, etc).
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I mean if you have human without consciousness (if that is even possible) behaving in a statistically different distribution in text vs with. The machine will eventually be in distribution of the former from the latter because the text it's trained on is of the former category. So it serves a "function" in the LLM to minimize loss to approximate the former distribution.
Also I find it somewhat emotional distinction to write "predict sequences of text that resemble human writing" instead of "predict human writing". They are designed to predict (at least in pretraining) human writing for the most part. They may fail at the task, and what they produce is a text which resemble human writing. But their task is not to resemble human writing. Their task is to "predict human writing". Probably a meaningless distinction, but I find it somewhat detracts from logically arguments to have emotional responses against similarities of machines and humans.
> I mean if you have human without consciousness (if that is even possible) behaving in a statistically different distribution in text vs with. The machine will eventually be in distribution of the former from the latter because the text it's trained on is of the former category. So it serves a "function" in the LLM to minimize loss to approximate the former distribution.
Sorry, I'm not following exactly what you're getting at here, do you mind rephrasing it?
> Also I find it somewhat emotional distinction to write "predict sequences of text that resemble human writing" instead of "predict human writing"
I don't know what you mean by emotional distinction. Either way, my point is that LLMs aren't models of humans, they're models of text, and that's obvious when the statistical power of the model necessarily fails at some point between model size and the length of the sequence it produces. For GPT-1 that sequence is only a few words, for GPT-5 it's a few dozen pages, but fundamentally we're talking about systems that have almost zero resemblance to actual human minds.
I basically agree with you. In the first point I mean that if it is possible to tell whether a being is conscious or not from the text it produces, then eventually the machine will, by imitating the distribution, emulate the characteristics of the text of conscious beings. So if consciousness (assuming it's reflected in behavior at all) is essential to completing some text task it must be eventually present in your machine when it's similar enough to a human.
Basically if consciousness is useful for any text task, i think machine learning will create it. I guess I assume some efficiency of evolution for this argument.
Wrt length generalization. I think at the order of say 1M tokens it kind of stops mattering for the purpose of this question. Like one could ask about its consciousness during the coherence period.
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