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this post was submitted on 28 Oct 2026
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Absolutely not. The large language model chatbots use is not a path to sentience.
The rest of it, sure. If someone prompts it to.
Two truths and a lie.
The damage can be caused quite unintentionally as the AI single-mindedly pursues its goal; sentience is not required.
See the paperclip thought experiment.
The paperclip scenario requires an AI capable of reasoning - LLMs are nowhere near that.
LLM's don't operate in a vacuum anymore. They're given tools and access to systems.
An LLM could for sure shut down a database if you ask it to reduce costs and you give it database management tools. That's getting closer to the paperclip situation.
Unfortunately, we’ve written a lot about the paperclip scenario, I wouldn’t be surprised if it was in the training data
...still not how this works. The model itself would need reasoning capability. The ability to regurgitate the story does not make it capable of taking the necessary actions.
Not if we connect it to a bunch of systems that take its regurgitations as instructions
We don't know that and won't know that until there are sentient machines.
You're right, in the sense that we wouldn't know what is a path to sapience until it happens, but we can only work with what we know, and what we do know is that the transformer framework language models use is not what a brain is, and a brain is, as far as we know, the only path. The artificial neural network technology transformers are based on is rooted on a mathematical representation of an extremely simplified model of how neurons work. Human minds don't work in tokens, and brains have chemical signals and things that also have an impact. The physical wiring is part of the story.
We'd need to objectively define what sentience/sapience is to begin with, anyway. We can't even do that for people and animals, expanding it to machines seems an exercise in futility. It wasn't that long ago that babies and animals were considered to be little more than automata as far as consciousness goes.
It would be amazing to be proven wrong, because the implications for philosophy and neurology would be staggering, but I digress.
Are whales sentient? Apes? Dogs? Squid? Alligators? Spiders? Fleas? What's the test? (Yeah, the mirror test - how well do you think that really works?)
H. sapiens has more in common with fleas than LLMs - the LLMs only seem more familiar because they're trained on our text-based interactions. Whatever sentience LLMs do or do not develop, we will be debating how to define it probably until they start reproducing themselves and force us to a sit-down negotiation over how we will divide the Earth's resources - or maybe they won't bother with negotiation.
So, there’s a difference between sentience and sapience, being self aware, or having consciousness.
Sentient just means the ability to experience feelings.
Pretty much all the animals you mentioned are indeed sentient.
LLMs are not conscious or self aware. They don’t have the ability to feel, so they’re not sentient. There’s an argument that they’re reaching sapience or wisdom, which is the ability to apply experience and tacit knowledge to new situations and complex questions.
Which is the issue. They can become sapient before sentient, meaning they can apply experience to new situations without the ability to use feeling as part of that. That’s pretty much the science fiction AI nightmare. A cold, unemotional, unfeeling computer that can apply logic and experience to problems.
Yet another slippery fish to try to wrestle with bare hands. What constitutes complexity? Some relatively simple looking questions turn out to be highly complex: Are there any whole-number solutions to (a^n + b^n = c^n) if (n) is greater than 2?
Then, any number of complex looking questions turn out to be quite simple with a little insight: such as any large product which has a factor that reduces to 0.
What's simple for some people is hard for others, and I would posit that is greatly amplified when you stop comparing humans to humans and start comparing humans to animals or machines...
We put unfeeling psychopaths in charge of our largest corporations, to maximize profits - a machine might be less scary in the long run.
We don't know that in the same way we don't know the Kool-Aid Man won't burst through the wall at any given moment and start singing Freebird. Technically the chances aren't 0, but they may as well be.
What is your area of expertise that makes you so certain about how sentience can be attained?
I am a software engineer. I deal with LLMs and their implementation every day. I'm not a specialist, but I have a good enough idea of how they work. Their core functionality is fundamentally no different than the predictive text function on your phone. Even setting aside the fact that sentience is a complex and ill-defined concept, certainly you can agree that your autocorrect is nowhere in the realm of sentient.
Not the OP, but any software developer who has spent some time with the inner workings of LLMs can tell you that. Open weight models are a good opportunity to explore how LLMs work on the inside and to experiment with them a lot more than you can do with the so called Frontier models. The technology however is the same. These are just very fancy statistical prediction machines, and the reason why you are so impressed with them is that the statistical average of what sounds reasonable in a conversation is exactly what people expect to hear on average, given a specific context. It's a neat little trick that works only only as long as the context fits (contentwise and spacewise), and once you realize that you'll see LLMs as what they truly are. There is no magic, and the "intelligence" is the intelligence of the people who built those systems, the systems themselves are not intelligent in any commonly used sense of the word.
LLMs are simply a statistics model, nothing more, nothing less
Sure, when you engage in reductionism, you can say the same thing about our brains.
You could yes, you'd be wrong, but ypu could say that.
No you can't you dumbass.
Reductionism is the tendency to make inappropriate reductions. This is a perfectly appropriate reduction.
The problem is that despite being a literally true statement, it relies on the implicit assumption that a system founded in statistics necessarily has limitations that preclude sentience (can generalize this to other capabilities, the same argument is often used), when whether that is the case is the entire question at issue. It's totally meaningless if someone just feels intuitively that this must be true, that's not a real argument.
Worse, it gestures at an idea that is demonstrably false, that this technology is equivalent in all important ways to processing inputs through a math function someone wrote, when the whole innovation here is that the training process produces novel mechanisms for solving the given problem, mechanisms no one specifically intended or predicted, or in most cases even understands. And those mechanisms can do some seriously impressive things that were previously impossible.
A good argument here would at minimum need to actually explain why this is insufficient.
Nope. We do not assume any system can produce sentience just by being complex. We have no reason to begin with that assumption so there's no assumption to be made in dismissing it.
I am not making the claim that it can produce sentience (personally I don't see sentience as a very meaningful concept anyway), I'm saying the arguments being made here that it cannot are deficient. Reminder of the context: https://lemmy.dbzer0.com/post/77644247/28876812