Providing background information for those unfamiliar with the UG theory. Making the debate relevant to modern AI advancements. Encouraging multidisciplinary contributions (linguistics, NLP, cognitive science, etc.). Adding specific questions to guide responses.
Chomsky’s theory of Universal Grammar remains relevant in linguistics but is debated in the context of AI and deep learning. While Universal Grammar posits an innate structure for language, AI and deep learning models focus on learning language patterns from data, without relying on predefined grammatical structures. This difference has led to contrasting views on the applicability of Universal Grammar in AI research
We have attempted to unify Chomsky and Skinner in our new AI (artificial agent) design - an agent that will learn a language like an infant. Skinner's approach seemed to dominate for what was required for the AI application, with Chomsky's structuralist approach much less relevant. Preprint here: Preprint Artificial Agent Language Development based on the Xzistor M...
The question can be framed differently, such as, "Can AI models have a world model like humans do?"(Innate linguistic structure can be represented with latent representation). In short, it is possible to train models to have the World model in 5 to 10 years of time. But the actual catch is if the AI has a similar qualia or representation of the world to humans, then it's still mimicking data. An actual intelligent machine discovers its own universal grammar, and as it will have far more parameters in its language, that language will be decipherable from our understanding.
Is Grammar an Inherent Product of the Human Brain?
"Gotta love a good academic controversy! The video below looks into perhaps the most intense and raging arguments in the field of linguistics, beginning with Noam Chomsky’s theories from the 1950s and 1960s suggesting that humans share a Universal Grammar (UG) that stems from the structure and functions that have evolved in the human brain. This theory is still hotly debated, and takes on even more interesting parameters in the age of artificial intelligence and large language models (LLMs). As we become increasingly reliant upon these word-prediction machines, how does what we know about human language impact the way they are created and function?"
https://scholarlykitchen.sspnet.org/2025/06/06/is-grammar-an-inherent-product-of-the-human-brain/?informz=1&nbd=&nbd_source=informz
https://youtu.be/bbrh_t8WhBc
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