[denton-scratch]

> And that's because, despite all of its training data, it's not capable of actually reasoning. That may change in the future [...]

I don't think so. When you say "it's not capable of actually reasoning", that's because it's a LLM; and if it "changes in the future", that's because the new system must no longer be a pure LLM. The appearance of reasoning in LLMs is an illusion.

[LASR]

How is the illusion of reasoning different from say “actual reasoning?”

[southernplaces7]

Because it literally can't reason, and it also has no innate agency. Even the most dedicated creators of LLM-based AI technology have clearly and repeatedly stated that these are very sophisticated stochastic parrots with no sense of self. How much easier could it be to see that LLMs like GPT aren't actual thinking machines in the way we humans are?

Yes, many people reason based on pure pattern-matching and repeat opinions not because they've reasoned them but because they're what they've absorbed from other sources, but even the world's most unreasoned human being with at least functional cognition still uses an enormous amount of constant, daily, hourly self-directed decision-making for a vast variety of complex and simple, often completely spontaneous scenarios and tasks in ways that no machine we've yet built on Earth does or could.

Moreover, even when some humans say or "believe" things based on nothing more than what they've absorbed from others without really considering it in depth, they almost always do so in a particularly selective way that fits their cognitive, emotional and personal predispositions. This very selectiveness is a distinctly conscious trait of a self-aware being. Its something LLM's don't have as far as I've yet seen.

[RoyalHenOil]

In the same way that illusions of anything else differ from the real thing. A wax apple is different from a real apple, even if it's hard to tell them apart sometimes. You may require further investigation to differentiate them (e.g., cutting open the apple or asking the AI to solve tricky reasoning questions), but if you can find a difference, there is a difference.

[Hedepig]

I have a hunch I am misunderstanding your argument, but does that mean the only way to build a "true reasoning machine" would be to just create a human.

I guess what I'm really asking, what would you expect to observe to make it not illusory?

[denton-scratch]

To distinguish between "is an illusion" and "is not an illusion", you need evidence that isn't observational. The whole point of illusions is that observational evidence is unreliable.

A desert mirage in the distance is an illusion; to the observer, it's indistinguishable from an oasis. You can only tell that it's a mirage by investigating how the appearance was created (e.g. by dragging your thirsty ass through the sand, to the place where the oasis appeared to be).

[spookie]

If one has a reasonable understanding of 2 concepts that make up a larger system. And, such a system has little else in addition to those concepts, one is able to come up with that system by itself. Even though, it has never seen it, or their composition was never explained prior to that logical process.

The illusion happens when, clearly, the alleged reasoning behind how such a system comes to be is based on prior knowledge of the system as a whole. Meaning, its construction/source was within the training data.

[Hedepig]

That sounds like a good litmus test. Do you have a specific example you've tried?

My opinion is it isn't binary, rather it's a scale. Your example is a point on the scale higher than what it is now.

But perhaps that's too liberal a definition of "reasoning" , no idea.

We seem to move the goalposts on what constitutes human level intelligence as we discover the various capabilities exhibited in the animal kingdom. I wonder if it is/will be the same with AI

[kelseyfrog]

I'm really curious, are you able to demonstrate reasoning, not reasoning and the illusion of reasoning in a toy example? I'd like to see what each looks like.

[intended]

Have you met someone who is full of bullshit? They sound REALLY convincing, except if you know anything about the subject, their statements are just word salad?

[TeMPOraL]

Have you met someone who's good at bullshitting their way out of a tough spot? There may be a word salad involved, but preparing it takes some serious skill and brainpower, and perhaps a decent high-level understanding of a domain. At some point, the word salad stops being a chain of words, and becomes a product of strong reasoning - reasoning on the go, aimed at navigating a sticky situation, but reasoning nonetheless.

[denton-scratch]

The finest bullshitter I knew had serious skill and brainpower; and he BS'd about stuff he was expert in. It was really a sort of party trick - he could leave his peer experts speechless (more likely, rolling on the floor laughing).

His output was indeed word-salad, but he was eloquent. His bullshit wasn't fallacious reasoning; it didn't even have the appearance of reasoning at all. He was just stringing together words and concepts that sound plausible. It was funny, because his audience knew (and were supposed to know) that it was nonsense.

LLMs are the same, except they're supposed to pretend that it isn't nonsense.

[intended]

Which would be a good test - and by that test ChatGPT is not reasoning, since it cant get out of sticky situations.

Yeah, I think you've got a good example that improves the analogy.

[kelseyfrog]

Are you able to give some examples? I'd like to know what it looks like w r.t. LLMs.

[3seashells]

https://en.m.wikipedia.org/wiki/Philosophical_zombie

[Jensson]

Bullshit has an illusion of reasoning instead of actual reasoning. Basically you give arguments that sounds reasonable on the surface but there is no actual reasoning behind them.

[denton-scratch]

> Bullshit has an illusion of reasoning instead of actual reasoning.

Bullshit is a good case to consider, actually. What is the relationship between bullshit and reasoning? You could argue that bullshit is fallacious reasoning, "pseudo-reasoning" based on incorrect rules of inference.

But these models don't use any rules of inference; they produce output that resembles the result of reasoning, but without reasoning. They are trained on text samples that presumably usually are the result of human reasoning. If you trained them on bullshit, they'd produce output that resembled fallacious reasoning.

No, I don't think the touchstone for actual reasoning is a human mind. There are machines that do authentic reasoning (e.g. expert systems), but LLMs are not such machines.

[TeMPOraL]

> Bullshit is a good case to consider, actually. What is the relationship between bullshit and reasoning?

None in principle, at least if you take the common definition of bullshit as saying things for effect, without caring whether they're true or false.

Fallacious reasoning will make you wrong. No reasoning will make you spew nonsense. Truth and lies and bullshit, all require reasoning for the structure of what you're saying to make sense, otherwise it devolves to nonsense.

> But these models don't use any rules of inference

Neither do we. Rules of inference came from observation. Formal reasoning is a tool we can employ to do better, but it's not what we naturally do.

[dasil003]

> None in principle, at least if you take the common definition of bullshit as saying things for effect, without caring whether they're true or false.

Maybe splitting hairs, but I’d argue that the bullshitter is reasoning about what sounds good, and what sounds good needs at least some shared assumptions and resulting logical conclusion to hang its hat on. Maybe not always, but enough of the time that I would still consider reasoning to be a key component of effective bullshit.