The heavily lifting is done by whatever process figures out what word to put next in the monologue; not by the inner monologue itself.
It seems you use “monologue” in this sentence to refer to the sequence of words only, and then say that of course the monologue is not the cognition. With this I agree, but I don’t think that’s the correct interpretation of the combo “language of thought hypothesis” + “language of thought close to natural language”. Having a “language of thought” means that there is a linear stream of items, and that your abstract cognition works only by applying some algorithm to the stream buffer to append the next item. The tape is not the cognition, but the cognition can be seen as acting (almost) only on the tape. Then “language of thought close to natural language” means that the language of thought has a short encoding in natural language. You can picture this as the language of thought of a verbal thinker being a more abstract version of natural language, similarly to when you feel what to say next but lack the word.
cognition can be seen as acting (almost) only on the tape
… If not for the existence of non-verbal cognition, which works perfectly well even without a “tape”. Suggesting that the tape isn’t a crucial component, that the heavy lifting can be done by the abstract algorithm alone, and therefore that even in supposed verbal thinkers, that algorithm is likely what’s doing the actual heavy lifting.
In my view, there’s an actual stream of abstract cognition, and a “translator” function mapping from that stream to human language. When we’re doing verbal thinking, we’re constantly running the translator on our actual cognition, which has various benefits (e. g., it’s easier to translate our thoughts to other humans); but the items in the natural-language monologue are compressed versions of the items in the abstract monologue, and they’re strictly downstream of the abstract stream.
There’s a “stream” of abstract thought, or “abstract monologue”
The cognition algorithm operates on/produces the abstract stream
Natural language is a compressed stream of the abstract stream
Which seems to me the same thing I said above, unless maybe you are also implying either or both of these additional statements:
a) The abstract cognition algorithm can not be seen as operating mostly autoregressively on its “abstract monologue”;
b) The abstract monologue can not be translated to a longer, but boundedly longer, natural language stream (without claiming that this is what happens typically when someone verbalizes).
Which of (a), (b) do you endorse, eventually with amendments?
Which of (a), (b) do you endorse, eventually with amendments?
I don’t necessarily endorse either. But “boundedly longer” is what does a lot of work there. As I’d mentioned, cognition can also be translated into a finitely long sequence of NAND gates. The real question isn’t “is there a finitely-long translation?”, but how much longer that translation is.
And I’m not aware of any strong evidence suggesting that natural language is close enough to human cognition that the resultant stream would not be much longer. Long enough to be ruinously compute-intensive (effectively as ruinous as translating it into NAND-gate sequences).
Indeed, I’d say there’s plenty of evidence to the contrary, given how central miscommunication is to the human experience.
It seems you use “monologue” in this sentence to refer to the sequence of words only, and then say that of course the monologue is not the cognition. With this I agree, but I don’t think that’s the correct interpretation of the combo “language of thought hypothesis” + “language of thought close to natural language”. Having a “language of thought” means that there is a linear stream of items, and that your abstract cognition works only by applying some algorithm to the stream buffer to append the next item. The tape is not the cognition, but the cognition can be seen as acting (almost) only on the tape. Then “language of thought close to natural language” means that the language of thought has a short encoding in natural language. You can picture this as the language of thought of a verbal thinker being a more abstract version of natural language, similarly to when you feel what to say next but lack the word.
… If not for the existence of non-verbal cognition, which works perfectly well even without a “tape”. Suggesting that the tape isn’t a crucial component, that the heavy lifting can be done by the abstract algorithm alone, and therefore that even in supposed verbal thinkers, that algorithm is likely what’s doing the actual heavy lifting.
In my view, there’s an actual stream of abstract cognition, and a “translator” function mapping from that stream to human language. When we’re doing verbal thinking, we’re constantly running the translator on our actual cognition, which has various benefits (e. g., it’s easier to translate our thoughts to other humans); but the items in the natural-language monologue are compressed versions of the items in the abstract monologue, and they’re strictly downstream of the abstract stream.
So you think
There’s a “stream” of abstract thought, or “abstract monologue”
The cognition algorithm operates on/produces the abstract stream
Natural language is a compressed stream of the abstract stream
Which seems to me the same thing I said above, unless maybe you are also implying either or both of these additional statements:
a) The abstract cognition algorithm can not be seen as operating mostly autoregressively on its “abstract monologue”;
b) The abstract monologue can not be translated to a longer, but boundedly longer, natural language stream (without claiming that this is what happens typically when someone verbalizes).
Which of (a), (b) do you endorse, eventually with amendments?
I don’t necessarily endorse either. But “boundedly longer” is what does a lot of work there. As I’d mentioned, cognition can also be translated into a finitely long sequence of NAND gates. The real question isn’t “is there a finitely-long translation?”, but how much longer that translation is.
And I’m not aware of any strong evidence suggesting that natural language is close enough to human cognition that the resultant stream would not be much longer. Long enough to be ruinously compute-intensive (effectively as ruinous as translating it into NAND-gate sequences).
Indeed, I’d say there’s plenty of evidence to the contrary, given how central miscommunication is to the human experience.