971–980 of 1001 posts
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What if somebody simulated all neurons of a bird and fed them appropriate stimuli? Would a bird neural replica be conscious? It would flap, that's for sure.
This has been tried with much simpler organisms, it did not behave like the real thing thus far. There was a paper about it, there now seems to be a project to push on the frontier https://openworm.org
It's a waste of time to think about whether an LLM has a subjective experience of reality, and this handily sets aside issues like AI rights. But the fact remains that these next-token-predictors exhibit objective, human-like behaviours, and for that reason the work of in-house philosopher Amanda Askell _is_ important. It's important that Claude is happy, empathic, demonstrates understanding and empathy for the human…
> It's important that Claude is happy, empathic, demonstrates understanding and empathy for the human condition I think you've fallen into the trap the essay describes. Of course Claude cannot be "happy" or "empathetic" for any meaningful definitions of those words, just like ELIZA couldn't be happy. It can output text that mimics words an empathetic or happy person might say (say, Julius Caesar if it could speak Eng…
Oh dear. Funny story.
So the other month, I made a quick and dirty Eliza implementation; bolted on the crappiest numeric sentiment classifier I could get away with (regex), and integrated the output of the classifier over time in a 'functional affect vector' (aka. emotion vector)
Anyone's intuition will tell you that this cannot POSSIBLY have 'Real Feelings (TM)'; and that's the whole point.
A) It was still capable of quite a bit of functional affect though; to wit I got it to trigger fireworks when happy, and rain when unhappy. This was the actual point of the exercise. Functional Affect Does The Thing, QED, yay me.
After that it gets annoying though.
B) Am I allowed to say it's happy or sad? Well... I mean emotion.happy=0.995 and emotion.sad=0.001. "It's really happy" is a prosaic description of a real numeric value representing a real functional state. What else am I supposed to call it? I swear I never meant to go there, and now I'm stuck with it.
C) So, we all know that it's a crappy demo, not the real thing. So I ducked into the psychology literature to try and find a protocol to disprove. For Science! And this is where the psychology literature really let me down.
So now I'm stuck with the crappiest thing that can plausibly still chat, and where I can't actually disprove it has emotions. Not properly, at least. And I'm not saying it's because it has emotions, because that would be really funny, but no.
I'm saying that -despite lots of people having fun debates at the local pub- it doesn't seem like anyone actually scientific has done anything about it in the last century or so. I might be searching in the wrong places. Some Help Here?
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Yeah. There are good arguments against LLM consciousness. This is not one of them. I'm hearing a lot of bad arguments against LLM consciousness lately. Bad argumentation heralds bad outcomes.
> Bad argumentation heralds bad outcomes. What bad outcomes do you foresee from badly arguing against LLM consciousness?
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> Its still bunch of instructions. So is your brain. That's the problem with this argument.
This sort of tech-centric distillation of visceral human experience into simple analogies is so grating. We can simultaneously acknowledge that consciousness is not well defined and not "testable" with certainty while also acknowledging that there is something different between the conscious experience we are all aware of as humans, and instructions executing on a chip. The only thing that has changed in the discours…
You say this based on what? Your brain is executing instructions on wetware. The entire universe is governed by physical laws.
At its base, the argument that computers can't be conscious is dualist. It assumes that there's some parallel realm of spirit that the brain is peculiarly able to tap into, but which computer programs that function in very similar ways to the brain don't tap into.
> the quality of the simulacrum that LLMs produce vs. pre-ML chatbots.
It seems to me that you're denigrating LLMs, or implying that they're only simulating thought, as opposed to actually thinking. But the difference between thinking and an extremely good simulacrum of thought is meaningless. They become the same thing. It's a bit like the Mitchell and Webb skit about faking the moon landings, in which the plotters quickly realize that the only way to convincingly fake landing on the moon is to fly a rocket to the moon and film the "fake" landings on the moon.
So it means we need a better harness for the agent, will it not get solved when we get to improve the simulation capability/environments?
I often hear the assumption that LLMs can or will become conscious because consciousness is likely substrate independent . The idea being that our brain is just a computer made out of meat and it doesn't do anything that can't be precisely simulated by a silicon computer. But I wonder if some of the magic in the human brain is its analog nature. Chemical signaling and impulses of neurons interact with each other with…
But they don't move. They can't. In the end, a film is just a series of still images. The images are projected in such rapid succession that they fool us into seeing things in motion that are not actually in motion. And if we slowed the film down enough, from 20 frames a second, to say, a frame every 20 seconds, well... the illusion would stop. We'd see each discrete still image for exactly what it was.
This is the same way computers work. Every tick of the clock, we get a new static image in memory. But those images are all static, as still as the images on film. And no static matrix of information can be conscious, just like no still image can move.
This is radically different than the neurons in our brains, which are each living things, sensing things, with a continuous analog existence. Whatever we feel comes from their lives. We can measure the things they do with their lives, but we shouldn't mistake the measurement for the thing being measured. A ruler is a foot long, but it’s not ticklish.
It's a waste of time to think about whether an LLM has a subjective experience of reality, and this handily sets aside issues like AI rights. But the fact remains that these next-token-predictors exhibit objective, human-like behaviours, and for that reason the work of in-house philosopher Amanda Askell _is_ important. It's important that Claude is happy, empathic, demonstrates understanding and empathy for the human…
The fact that Claude produces tokens that, when composed, appear to convey those qualities seems to me to be little indication of whether or not a hypothetically conscious model "feels" those qualities. What does that even mean, without a proper scientific model of consciousness? IMO philosophers in this space are practicing pseudo-science that feels good but has no basis in a useful empiricism
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What? Where are you seeing such claims? I.e. that only humans can be conscious, that AI in general is not conscious by definition?? Seems to me you've put up an easy-to-dismiss strawman. Here's how I would summarize crux of the argument: LLMs (specifically) are, by construction, chameleons. More precisely, role-playing machines. When compelled to have a conversation as "themselves", all they do is take on the role of…
Err… right here in TFA? >> The first requirement is that the computer program has a body (either physical or virtual) and sense organs LLMs may be chameleons, but, to steal an excellent quote, if you can’t tell does it really matter. My personal take on this is that consciousness is a thing induced, not a thing evoked. If it generates a response on the observer as a conscious thing would it is, by my definition, cons…
And if you read my comment above carefully, I point out at least one way you could tell whether an agent has an I or just pretending to – by tracking their energy expenditure/reaction times. But they would give themselves in other ways as well. Pretending can only fool one short-term.
I'm not going to discuss the quote since @sp1nningaway already pointed out it doesn't say what you say it does.
> My intention is to highlight the fact that LLM conversations are cleverly disguised examples of sentence continuation Regardless of bigger issues, this kind of statement reveals a deep misunderstanding. Problem type does not limit problem complexity. Nor does problem type limit solution complexity or power. If a machine has to learn to understand humans to complete text, then that is what it has to do. And there is…
Raphaël Millière has a very useful term for this kind of vacuous dismissal, the redescription fallacy ( https://arxiv.org/pdf/2401.03910 , page 9): > Recent debates have been clouded by a misleading inference pattern, which we term the “Redescription Fallacy.” This fallacy arises when critics argue that a system cannot model a particular cognitive capacity, simply because its operations can be explained in less abstr…
Earlier quoted context omitted.
Raphaël Millière has a very useful term for this kind of vacuous dismissal, the redescription fallacy ( https://arxiv.org/pdf/2401.03910 , page 9): > Recent debates have been clouded by a misleading inference pattern, which we term the “Redescription Fallacy.” This fallacy arises when critics argue that a system cannot model a particular cognitive capacity, simply because its operations can be explained in less abstr…
> or (more pointedly) that brain activity could not possibly implement cognition because it can be described as a collection of neural firings. This sounds like a dismissal of the argument through a characterized straw man. That is, it seems that reducing the complexity of the brain to "collection of neural firings" is not being honest about everything involved to a much greater degree than saying neural networks are…
Humans appear to intelligenty communicate, however these are just cleverly disguised sound patterns produced by the brain that happen to increase the likelihood of food going into their mouths, and various similar reward attracting mechanisms that make survival outcomes more likely. So human intelligence could be reduced to something like "fancy food-attracting algorithms" using the same fallacy.
I'm kind of on the fence on the subject of whether LLMs could be compared to the complexity of the human brain, myself.