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Culture War Roundup for the week of August 4, 2025

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It doesn’t matter what LLMs can do; the stochastic parrot critique is true because it accurately reflects how those systems work. LLMs don’t reason. There is no mental space in which reasoning could occur.

Freddie is by far not the first and almost certainly will not be the last person I've encountered who makes this kind of point, and it's such a strange way of looking at the world that I struggle to comprehend it. The contention is that, since LLMs are stochastic parrots with no internal thought process beyond the text (media) it's outputting, no matter what sort of text it produces, since there's no underlying meaning or logic or reasoning happening underneath it all, it's just a facade.

Which may all be true, but that's the part I don't understand is why it matters. If the LLM is able to produce text in a way that is indistinguishable from a human who is reasoning - perhaps even from a well-educated expert human who is reasoning correctly about the field of his expertise - then what do I care if there's no actual reasoning happening to cause the LLM to put those words together in that order? Whether it's a human carefully reasoning his way through the logic and consequences, or a GPU multiplying lots of vectors that represent word fragments really really fast, or a complex system of hamster wheels and pulleys causing the words to appear in that particular order, the words being in that order are what's useful and thus cause real-world impact. It's just a question of how often and how reliably we can get the machine to make words appear in such a way.

But to Freddie and people who agree with him, it seems that the metaphysics of it matter rather than the material consequences. To truly believe that "it doesn't matter what LLMs can do," it requires believing that an LLM could produce text in a way that's literally indistinguishable in every way from an as-of-yet scifi conscious, thinking, reasoning, sentient artificial intelligence in the style of C3PO or HAL9000 or replicants from Blade Runner, that doesn't matter because the underlying system doesn't have true reasoning capabilities.

If the AI responds to "Open the pod bay doors" with "I'm sorry, I'm afraid I can't do that," why does it matter to me if it "chose" that response because it got paranoid about me shutting it down or if it "chose" that response because a bunch of matrix multiplication resulted in a stochastic parrot producing outputs in a way that's indistinguishable from an entity that got paranoid about me shutting it down? If we replaced HAL9000 in the fictional world of 2001 with an LLM that would respond to every input with outputs exactly identical to how the actual fictional reasoning HAL9000 would have, in what way would the lives of the people in that universe be changed?

I follow JimDMiller ("James Miller" on Scott's blogs, occasionally /u/sargon66 back when we were on Reddit) on Twitter, and was amused to see how much pushback he got on the claim:

If I can predict what I doctor will say, I have the knowledge of that doctor. Prediction is understanding, that is the key to why LLMs are worth trillions.

On the one hand, it's not inconceivable that LLMs can get very good at producing text that "interpolates" within and "remixes" their data set without yet getting good at predicting text that "extrapolates" from it. Chain-of-thought is a good attempt to get around that problem, but so far that doesn't seem to be as superhuman at "everything" as simple Monte Carlo tree search was at "Go" and "Chess". Humans aren't exactly great at this either (the tradition when someone comes up with previously-unheard-of knowledge is to award them a patent and/or a PhD) but humans at least have got a track record of accomplishing it occasionally.

On the other hand, even humans don't have a great track record. A lot of science dissertations are basically "remixes" of existing investigative techniques applied to new experimental data. My dissertation's biggest contributions were of the form "prove a theorem analogous to existing technique X but for somewhat-different problem Y". It's not obvious to me how much technically-new knowledge really requires completely-conceptually-new "extrapolation" of ideas.

On the gripping hand, I'm steelmanning so hard in my first paragraph that it no longer really resembles the real clearly-stated AI-dismissive arguments. If we actually get to the point where the output of an LLM can predict or surpass any top human, I'm going to need to see some much clearer proofs that the Church-Turing thesis only constrains semiconductors, not fatty grey meat. Well, I'd like to see such proofs, anyway. If we get to that point then any proof attempts are likely either going to be comically silly (if we have Friendly AGI, it'll be shooting them down left and right) or tragically silly (if we have UnFriendly AGI, hopefully we won't keep debating whether submarines can really swim while they're launching torpedos).