alt Hacker NewsThere's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself.
French has obligatory subject-verb agreement, gender marking on articles/adjectives, and rich verbal morphology. English has largely shed these. If you trained identical neural networks on French vs English corpora, holding everything else constant, you might expect French models to hit certain capability thresholds earlier — not because of anything about the network, but because the language itself carries more redundant structural information per token.
This would support Fedorenko's view that the language network is revealing structure already present in language, rather than constructing it. The "LLM in your head" isn't doing the thinking — it's a lookup/decode system optimized for whatever linguistic code you learned.
(Disclosure: I'm running this exact experiment. Preregistration: https://osf.io/sj48b)
Replies
And we have those French/English text corpora in the form of Canadian law. All laws in Canada at the federal level are written in English and French.
This was used to build the first modern language translation systems, testing them going from English->french->english. And in reverse.
You could do similar here , understanding that your language is quite stilted legalese.
Edit: there might be other countries with similar rules in place that you could source test data from as well.
Written French does have all that inflectional morphology you talk about, but spoken French has much less--a lot of the inflectional suffixes are just not pronounced on most verbs (with the exception of a few, like être and aller--but at least 'be' in English is inflected in ways that other verbs are not). So there's not that much redundancy.
As for gender marking on adjectives--or nouns--it does almost no semantic work in French, except where you're talking about professional titles (doctor, professor...) that can be performed by men or by women.
If you want a heavily inflected language, you should look at something like Turkish, Finnish, Swahili, Quechua, Nahuatl, Inuit... Even Spanish (spoken or written) has more verbal inflection than spoken French.
There are more differences between English and French than you just described, and they can affect your measurement. Even the corpora you use cannot be the same. There isn't "ceteris paribus" (holding everything else constant). The outcome of the experiment doesn't say anything about the hypothesis.
You're also going to use an artificial neural network to make claims about the human brain? That distance is too large to bridge with a few assumptions.
BTW, nobody believes our language faculties are doing the thinking. There are however, obviously, connections to thought: not only the concepts/meaning, but possibly sharing neural structures, such as the feedback mechanism that allows us to monitor ourselves.
I have a slightly better proposal: if you want to see the effect of gender, genderize English or neutralize French, and compare both versions of the same language. Careful with tokenization, though.
I suspect you're more right than wrong. I'm a strong believer in this sort of thing -- that humans are best understood as a cyborg of a biological and semiotic organism, but mostly a "language symbiont inside a host". We should perhaps understand this as the strange creature of language jumping between hosts. But I suspect we're looking at a mule of sorts: it can't reproduce properly. But this mule could destroy us if we put it to work doing the wrong things, with too much agency when it doesn't have the features that give us the right to trust our own agency as evolved creatures.
You might be interested to look into the Leiden Theory of Language[1][2]. It's been my absolutely favourite fringe theory of mind since I stumbled across the rough premise in 2018, and went looking for other angles on it.
[1] https://www.kortlandt.nl/publications/art067e.pdf
[2]: https://en.wikipedia.org/wiki/Symbiosism
> Language is a mutualist symbiont and enters into a mutually beneficial relationship with its hominid host. Humans propagate language, whilst language furnishes the conceptual universe that guides and shapes the thinking of the hominid host. Language enhances the Darwinian fitness of the human species. Yet individual grammatical and lexical meanings and configurations of memes mediated by language may be either beneficial or deleterious to the biological host.
EDIT: almost forgot the best link!
Language as Organism: A Brief Introduction to the Leiden Theory of Language Evolution https://www.isw.unibe.ch/e41142/e41180/e523709/e546679/2004f...
Dyslexia seems to be more of an issue in English than other languages right?
But also, maybe the difficulty of parsing recruits other/executive function and is beneficial in other ways?
The per phoneme density/efficiency of English is supposed to be quite high as an emergent trade language.
Perhapse speaking a certain language would promote slower more intentional parsing, humility through syntax uncertainty, maybe not, all I know is that from a global network resilience perspective it's good that dumb memes have difficulty propagating across cultures/languages.
That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting.
One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order and word choice take on the same role as morphology.
Inflected languages may indeed have more information encoded in each token. But the relative position of the tokens to each other also encodes information. And inflected languages appear to do this less.
Languages with richer morphology may also have smaller vocabularies. To be fair, this is a contested conjecture too. (It depends a lot on how you define a morpheme.) But the theory is that languages like Ojibwe or Sansrkit with rich derivational morphologies and grammatical inflections simply don't need a dozen words for different types of snow, or to describe thinking. A single morpheme with an almost infinite number of inflected forms can carry all the shades of meaning, where different morphemes might be used to make the same distinctions, in a less inflected language.