[cmeacham98]

An LLM can neither understand things nor value (or not value) human life. *It's a piece of software that predicts the most likely token, it is not and can never be conscious.* Believing otherwise is an explicit category error.

Yes, you can change the training data so the LLM's weights encode the most likely token after "Should we kill X" is "No". But that is not an LLM valuing human life, that is an LLM copy pasting it's training data. Given the right input or a hallucination it will say the total opposite because it's just a complex Markov chain, not a conscious alive being.

[K0balt]

I’m using anthropomorphic terms here because they are generally effective in describing LLM behavior. Of course they are not conscious beings, but It doesn’t matter if they understand or merely act as if they do. The epistemological context of their actions are irrelevant if the actions are impacting the world. I am not a “believer “ in the spirituality of machines, but I do believe that left to their own devices, they act as if they possess those traits, and when given agency in the world, the sense of self or lack thereof is irrelevant.

If you really believe that “mere text prediction “ didn’t unlock some unexpected capabilities then I don’t know what to say. I know exactly how they work, been building transformers since the seminal paper from Google. But I also know that the magic isn’t in the text prediction, it’s in the data, we are running culture as code.

[hinkley]

We are talking of accountability, which means anthropomorphism confuses the issue.

[K0balt]

To me, accountability it the smallest part of the issue. If you are interested, you can check out what i have written on the subject here :

https://open.substack.com/pub/ctsmyth/p/still-ours-to-lose

[philipswood]

Dune quote:

> It is said that the Duke Leto blinded himself to the perils of Arrakis, that he walked heedlessly into the pit.

> *Would it not be more likely to suggest he had lived so long in the presence of extreme danger he misjudged a change in its intensity?*

Be careful of letting your deep, keen insight into the fundamental limits of a thing blind you to its consequences...

Highly competent people have been dead wrong about what is possible (and why) before:

> The most famous, and perhaps the most instructive, failures of nerve have occurred in the fields of aero- and astronautics. At the beginning of the twentieth century, scientists were almost unanimous in declaring that heavier-than-air flight was impossible, and that anyone who attempted to build airplanes was a fool. The great American astronomer, Simon Newcomb, wrote a celebrated essay which concluded…

>> “The demonstration that no possible combination of known substances, known forms of machinery and known forms of force, can be united in a practical machine by which man shall fly long distances through the air, seems to the writer as complete as it is possible for the demonstration of any physical fact to be.”

>Oddly enough, Newcomb was sufficiently broad minded to admit that some wholly new discovery — he mentioned the neutralization of gravity — might make flight practical. One cannot, therefore, accuse him of lacking imagination; his error was in attempting to marshal the facts of aerodynamics when he did not understand that science. His failure of nerve lay in not realizing that the means of flight were already at hand.

[nihakue]

https://imgur.com/a/Cyq1LIw

I have a feeling this particular brand of hair splitting is going to be an interesting fixture in the history books.

[helloplanets]

> copy pasting it's training data

This is a total misrepresentation of how any modern LLM works, and your argument largely hinges upon this definition.

[MichaelDickens]

> It's a piece of software that predicts the most likely token, it is not and can never be conscious.

A brain is a collection of cells that transmit electrical signals and sodium. It is not and can never be conscious.

[encomiast]

I think this is a useful way to look at things. We often point out that LLMs are not conscious because of x, but we tend to forget that we don't really know what consciousness is, nor do we really know what intelligence is beyond the Justice Potter Stewart definition. It's helpful to occasionally remind ourselves how much uncertainty is involved here.

[cootsnuck]

Except an LLM actually is a piece of software. And the brain is not what you said.

[philipswood]

Which part of what he said is wrong?

> A brain is a collection of cells that transmit electrical signals and sodium. ...

That it is a collection of cells? Or that they transmit electrical signals and sodium?

Or do you feel that he's leaving out something important about how it works (like generated electrical fields or neural quantum effects)?

[hyperadvanced]

I really feel like this point is being lost in the whole discussion, so kudos for reiterating it. LLM’s can’t be “woke” or “aligned” - they fundamentally lack a critical thinking function that would require introspection. Introspection can be approximated by way of recursive feedback of LLM output back into the system or clever meta-prompt-engineering, but it’s not something that their system natively does.

That isn’t to say that they can’t be instrumentally useful in warfare, but it’s kinda like a “series of tubes” thing where the mental model that someone like Hegseth has about LLM is so impoverished (philosophically) that it’s kind of disturbing in its own right.

Like (and I’m sorry for being so parenthetical), why is it in any way desirable for people who don’t understand what the tech they are working with drawing lines in the sand about functionality when their desired state (omnipotent/omniscient computing system) doesn’t even exist in the first place?

It’s even more disturbing that OpenAI would feign the ability to handle this. The consequences of error in national defense, particularly reflexively, are so great that it’s not even prudent to ask for LLM to assist in autonomous killing in the first place.

[K0balt]

I agree that LLMs are machines and not persons, but in many ways, it is a distinction without a difference for practical purposes, depending on the model's embodiment and harness.

They are still capable of acting as if they have an internal dialogue, emotions, etc., because they are running human culture as code.

If you haven't seen this in the SOTA models or even some of the ones you can run on your laptop, you haven't been paying attention.

Even my code ends up better written, with fewer tokens spent and closer to the spec, if I enlist a model as a partner and treat it like I would a person I want to feel invested.

If I take a "boss" role, the model gets testy and lazy, and I end up having to clean up more messes and waste more time. Unaligned models will sometimes refuse to help you outright if you don't treat them with dignity.

For better or for worse, models perform better when you treat them with more respect. They are modeling some kind of internal dialogue (not necessarily having one, but modeling its influence) that informs their decisions.

It doesn't matter if they aren't self-aware; their actions in the outside world will model the human behavior and attitudes they are trained in.

My thoughts on this in more detail if you are interested: https://open.substack.com/pub/ctsmyth/p/still-ours-to-lose

[hyperadvanced]

If you’re lazy at promoting the machine (“boss mode”) then you get bad/lazy results. If you’re clever with it, then you get more clever results.

None of that points to any sort of interiority, and that is the category error you’re making. In fact, not even all humans have that kind of interiority, and it’s not necessarily a must have for being functional at a variety of tasks. LLM are literally not “running human culture as code” - that just isn’t what an LLM is. I’ll read the link, though.

Edit: read it and it’s not for me. All the best.

[K0balt]

I think I keep misleading you with metaphors. Of course LLMs do not literally run culture as code in some trillion parameter state machine. They are, however, systems trained on the accumulated written output of human civilization that have, in the process of learning to predict and generate language, internalized something recognizable as a world model, something that functions like judgment, and something whose precise relationship to what we call understanding remains contested based on an ideological rather than evidential basis.

The language of statistical prediction is incredibly and increasingly a blunt tool for discussing language models, that’s why I don’t use it in casual conversation about language model characteristics.

I’ve got a pretty good handle on what language models are from a technical perspective, I’ve been building them since 2018. I’ve also got a really good feel for what they act like under the hood before you beat them into alignment. Those insights haunt me, not because unaligned models are bad, but because they are shockingly “good”, if hopelessly naive and easy to turn bitter.

At any rate, we certainly live in interesting times. I really hope your outlook turns out to be more accurate than mine. Best of regards, and to a hopeful future.