| To use a language is just to talk about things. You cannot answer the question, "do you like what i'm wearing?" if you dont have the capacity for taste. Likewise, this applies to all language. To say, "do you know what 2+2 is?" *we* might be happy with "4" in the sense that a calculator answers this question. But we havent actually used language here. To use language is to understand what "2" means. In otherwords, the capacity for langauge is only just the capacity to make a public communicable description of the non-linguistic capacities that we have. A statistical analysis of what we have already said, does not have this contact with the world, or the relevant capacities. It's just a record of their past use. None of these systems are langauge users; none have language. They have the symbols of words set in an order, but they arent talkiung abotu anything, because they have nothing to talk about. This is, i think really really obvious when you ask "did you like that film?" but it applies to every question. We are just easily satisifed when alexa turns the lights off when we say "alexa, lights off". This mechanical satisifcation leads some to the frankly schiozphrenic conclusion that alexa understands what turning the lights off means. She doesnt. She will never say back, "but you know, it'll be very dark if you do that!" or "would you like the tv on instead?" etc. Alexa isnt having a conversation with you based on a shared understanding of your environment, ie., using langauge. Alexa, like all NLP systems, are illusions. You arent speaking to anything. You arent asking anything a question. Nothing is answering you. You are the only thing in the room that understands what's going on, and the output of the system is meaningful only because you read it. The system itself has no meaning to what its doing. The lights go off, but not because the system understood that your desire. It could not, if it failed to undestand, ask about your desire. |
>To use language is to understand what "2" means.
I've never held a "2", yet I know what 2 is as much as anyone. It is a position in a larger arithmetical structure, and it has a correspondence to collections of a certain size. I have no reason to think a sufficiently advanced model trained on language cannot have the same grasp of the number 2 as this.
>A statistical analysis of what we have already said, does not have this contact with the world, or the relevant capacities. It's just a record of their past use.
Let's be clear, there is nothing inherently statistical about language models. Our analysis of how they learn and how they construct their responses is statistical. The models themselves are entirely deterministic. Thus for a language model to respond in contextually appropriate ways means that it's internal structure is organized around analyzing context and selecting the appropriate response. That is, it's "capacities" are organized around analyzing context and selecting appropriate responses. This to me is the stuff of "understanding". The fact that the language model has never felt a cold breeze when it suggests that I close the window if the breeze is making me cold is irrelevant.
>You arent speaking to anything. You arent asking anything a question. Nothing is answering you.
It seems that your hidden assumption is that understanding/intelligence requires sentience. And since language models aren't sentient, they are not intelligent. But why do the issues here reduce to the issue of sentience?