>Just because cognitive scientists don't know everything about how intelligence works (or on what it is) doesn't mean that they know nothing.
Author's claim is pretty strong: that human intelligence and what is called GenAI have no common ground at all. This is untrue at least intuitively for the entire field of ML. "Intuitively" because it cannot be proven or disproven until you know exactly what is human intelligence, or whatever the author means by thinking or reasoning.
>Arguably AI researchers ought to have a fairly well defined stance of what "intelligence" means and can't use a trick like "nobody knows what intelligence is" to escape criticism.
If you don't formalize your definition, the discussion can be easily escaped by either side by simply moving along the abstraction tree. The tiresome stochastic parrot/token predictor argument is about trees while the human intelligence is discussed in terms of a forest. And if you do formalize it, it's possible to discover that human intelligence is not what it seems either. I'm not even starting on the difference between individual intelligence, collective intelligence, and biological evolution, it's not easy to define where one ends and another begins.
AI researchers mainly focus on usefulness (see the definition above). The proof is in the pudding. Philosophical discussions are fine to have, but pretty meaningless at best and designed to support a narrative at worst.
>Author's claim is pretty strong: that human intelligence and what is called GenAI have no common ground at all.
I feel that you're being unfair to the author here; the quote you responded to in your GP post alluded to "reason or think", and their argument is that LLMs don't. This is more specific than the sweeping statement you attribute to them.
> AI researchers mainly focus on usefulness (see the definition above).
And usefulness is something the article doesn't touch on, I think? The point of the article is that some users attribute capabilities to LLMs that can be explained with the same mechanisms as the capabilities they attribute to psychics (which are well understood to be nonexistent).
> Philosophical discussions are fine to have, but pretty meaningless at best and designed to support a narrative at worst.
Why this is relevant to AI research is (in my interpretation) that it is known to be hard for humans collectively to evaluate how intelligent an entity really is. We are easily fooled into seeing "intelligence" where it is not. This is something that cognitive scientists have spent a lot of time thinking about, and may perhaps be able to comment on.
For what it's worth I've seen cognitive scientists use AI to do cools stuff. I remember seeing someone who was using AI to show that it is possible to build inference without language (I am speaking from memory here, it was a while ago and I lost the reference sadly so I hope I'm not deforming it too much). She was certainly not claiming that her experiments showed how intelligence worked, but only that they pointed to the fact that language does not have to be a prerequisite for building inferences. Interesting stuff though without the sensationalism that sometimes accompanies the advocacy of LLMs.
Author's claim is pretty strong: that human intelligence and what is called GenAI have no common ground at all. This is untrue at least intuitively for the entire field of ML. "Intuitively" because it cannot be proven or disproven until you know exactly what is human intelligence, or whatever the author means by thinking or reasoning.
>Arguably AI researchers ought to have a fairly well defined stance of what "intelligence" means and can't use a trick like "nobody knows what intelligence is" to escape criticism.
If you don't formalize your definition, the discussion can be easily escaped by either side by simply moving along the abstraction tree. The tiresome stochastic parrot/token predictor argument is about trees while the human intelligence is discussed in terms of a forest. And if you do formalize it, it's possible to discover that human intelligence is not what it seems either. I'm not even starting on the difference between individual intelligence, collective intelligence, and biological evolution, it's not easy to define where one ends and another begins.
AI researchers mainly focus on usefulness (see the definition above). The proof is in the pudding. Philosophical discussions are fine to have, but pretty meaningless at best and designed to support a narrative at worst.