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