Generative linguistics contribution to artificial intelligence: Where this contribution lies?

TL;DR

This paper explores the significant influence of Generative linguistics, especially Chomsky's theories, on AI development, highlighting contributions from syntax, semantics, and language models, while acknowledging ongoing debates and divergences.

Contribution

It provides a comprehensive, unbiased analysis of how Generative linguistics has contributed to AI, emphasizing its role in syntax, semantics, and language modeling.

Findings

GL significantly influences AI, especially in syntax and semantics

Large Language Models derive from GL principles

Debates remain on the nature of language input in AI

Abstract

This article aims to characterize Generative linguistics (GL) contribution to artificial intelligence (AI), alluding to the debate among linguists and AI scientists on whether linguistics belongs to humanities or science. In this article, I will try not to be biased as a linguist, studying the phenomenon from an independent scientific perspective. The article walks the researcher/reader through the scientific theorems and rationales involved in AI which belong from GL, specifically the Chomsky School. It, thus, provides good evidence from syntax, semantics, language faculty, Universal Grammar, computational system of human language, language acquisition, human brain, programming languages (e.g. Python), Large Language Models, and unbiased AI scientists that this contribution is huge, and that this contribution cannot be denied. It concludes that however the huge GL contribution to AI, there are still points of divergence including the nature and type of language input.