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A non-anthropomorphized view of LLMs

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475 points zdw | 9 comments | | HN request time: 0.306s | source | bottom
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Al-Khwarizmi ◴[] No.44487564[source]
I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent.

The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing an UI events API and you were talking about zeros and ones, or voltages in transistors. Technically fine but totally useless to reach any conclusion about the high-level system.

We need a higher abstraction level to talk about higher level phenomena in LLMs as well, and the problem is that we have no idea what happens internally at those higher abstraction levels. So, considering that LLMs somehow imitate humans (at least in terms of output), anthropomorphization is the best abstraction we have, hence people naturally resort to it when discussing what LLMs can do.

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1. tempfile ◴[] No.44488604[source]
The "point" of not anthropomorphizing is to refrain from judgement until a more solid abstraction appears. The problem with explaining LLMs in terms of human behaviour is that, while we don't clearly understand what the LLM is doing, we understand human cognition even less! There is literally no predictive power in the abstraction "The LLM is thinking like I am thinking". It gives you no mechanism to evaluate what tasks the LLM "should" be able to do.

Seriously, try it. Why don't LLMs get frustrated with you if you ask them the same question repeatedly? A human would. Why are LLMs so happy to give contradictory answers, as long as you are very careful not to highlight the contradictory facts? Why do earlier models behave worse on reasoning tasks than later ones? These are features nobody, anywhere understands. So why make the (imo phenomenally large) leap to "well, it's clearly just a brain"?

It is like someone inventing the aeroplane and someone looks at it and says "oh, it's flying, I guess it's a bird". It's not a bird!

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2. CuriousSkeptic ◴[] No.44488702[source]
> Why don't LLMs get frustrated with you if you ask them the same question repeatedly?

To be fair, I have had a strong sense of Gemini in particular becoming a lot more frustrated with me than GPT or Claude.

Yesterday I had it ensuring me that it was doing a great job, it was just me not understanding the challenge but it would break it down step by step just to make it obvious to me (only to repeat the same errors, but still)

I’ve just interpreted it as me reacting to the lower amount of sycophancy for now

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3. danielbln ◴[] No.44489811[source]
In addition, when the boss man asks for the same thing repeatedly then the underling might get frustrated as hell, but they won't be telling that to the boss.
4. jibal ◴[] No.44490982[source]
Point out to an LLM that it has no mental states and thus isn't capable of being frustrated (or glad that your program works or hoping that it will, etc. ... I call them out whenever they ascribe emotions to themselves) and they will confirm that ... you can coax from them quite detailed explanations of why and how it's an illusion.

Of course they will quickly revert to self-anthropomorphizing language, even after promising that they won't ... because they are just pattern matchers producing the sort of responses that conforms to the training data, not cognitive agents capable of making or keeping promises. It's an illusion.

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5. squidbeak ◴[] No.44491762[source]
The vending machine study from a few months ago, where flash 2.0 lost its mind, contacted the FBI (as far as it knew) and refused to co-operate with the operator's demands, seemed a lot like frustration.
6. Applejinx ◴[] No.44495185{3}[source]
Of course this is deeply problematic because it's a cloud of HUMAN response. This is why 'they will' get frustrated or creepy if you mess with them, give repeating data or mind game them: literally all it has to draw on is a vast library of distilled human responses and that's all the LLM can produce. This is not an argument with jibal, it's a 'yes and'.

You can tell it 'you are a machine, respond only with computerlike accuracy' and that is you gaslighting the cloud of probabilities and insisting it should act with a personality you elicit. It'll do what it can, in that you are directing it. You're prompting it. But there is neither a person there, nor a superintelligent machine that can draw on computerlike accuracy, because the DATA doesn't have any such thing. Just because it runs on lots of computers does not make it a computer, any more than it's a human.

7. TeMPOraL ◴[] No.44495703[source]
> It is like someone inventing the aeroplane and someone looks at it and says "oh, it's flying, I guess it's a bird". It's not a bird!

We tried to mimic birds at first; it turns out birds were way too high-tech, and too optimized. We figured out how to fly when we ditched the biological distraction and focused on flight itself. But fast forward until today, we're reaching the level of technology that allows us to build machines that fly the same way birds do - and of such machines, it's fair to say, "it's a mechanical bird!".

Similarly, we cracked computing from grounds up. Babbage's difference engine was like da Vinci's drawings; ENIAC could be seen as Wright brothers' first flight.

With planes, we kept iterating - developing propellers, then jet engines, ramjets; we learned to move tons of cargo around the world, and travel at high multiples of the speed of sound. All that makes our flying machines way beyond anything nature ever produced, when compared along those narrow dimensions.

The same was true with computing: our machines and algorithms very quickly started to exceed what even smartest humans are capable of. Counting. Pathfinding. Remembering. Simulating and predicting. Reproducing data. And so on.

But much like birds were too high-tech for us to reproduce until now, so were general-purpose thinking machines. Now that we figured out a way to make a basic one, it's absolutely fair to say, "I guess it's like a digital mind".

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8. tempfile ◴[] No.44498305[source]
A machine that emulates a bird is indeed a mechanical bird. We can say what emulating a bird is because we know, at least for the purpose of flying, what a bird is and how it works. We (me, you, everyone else) have no idea how thinking works. We do not know what consciousness is and how it operates. We may never know. It is deranged gibberish to look at an LLM and say "well, it does some things I can do some of the time, so I suppose it's a digital mind!". You have to understand the thing before you can say you're emulating it.
9. ben_w ◴[] No.44501576{3}[source]
While they will agree with you that they don't, it's also the case that this is via training.

Consider that we have recordings of Brent Spiner covered in white paint and wearing yellow contact lenses claiming to have no emotions, not because he didn't, but because he was playing a role, which is also something we know LLMs can do.

So we don't know for sure if LLMs do or don't have qualia, irregardless of what they say, and won't until we have a more concrete idea of what the mechanism is behind that sense of the phrase "mental state" so we can test for their presence or absence.