
How Deeply Human Is Language?
Chomsky, the Brain, and the AI Fantasy
Yosef Grodzinsky(Author)
MIT Press
Published on 21. April 2026
Book
Paperback/Softback
192 pages
978-0-262-05200-9 (ISBN)
Description
A leading neurolinguist explains linguistic theory and large language models—the top contenders for understanding human language—and evaluates them in the context of the brain.
Contemporary linguistics, founded and inspired by Noam Chomsky, seeks to understand the hallmark of our humanity—language. Linguists develop powerful tools to discover how knowledge of language is acquired and how the brain puts it to use. AI experts, using vastly different methods, create remarkable neural networks—large language models (LLMs) such as ChatGPT—said to learn and use language like us.
Chomsky called LLMs “a false promise.” AI leader Geoffrey Hinton has declared that “neural nets are much better at processing language than anything ever produced by the Chomsky School of Linguistics.”
Who is right, and how can we tell? Do we learn everything from scratch, or could some knowledge be innate? Is our brain one big network, or is it built out of modules, language being one of them?
In How Deeply Human Is Language?, Yosef Grodzinsky explains both approaches and confronts them with the reality as it emerges from the engineering, linguistic, and neurological record. He walks readers through vastly different methods, tools, and findings from all these fields. Aiming to find a common path forward, he describes the conflict, but also locates points of potential contact, and sketches a joint research program that may unite these communities in a common effort to understand knowledge and learning in the brain.
Contemporary linguistics, founded and inspired by Noam Chomsky, seeks to understand the hallmark of our humanity—language. Linguists develop powerful tools to discover how knowledge of language is acquired and how the brain puts it to use. AI experts, using vastly different methods, create remarkable neural networks—large language models (LLMs) such as ChatGPT—said to learn and use language like us.
Chomsky called LLMs “a false promise.” AI leader Geoffrey Hinton has declared that “neural nets are much better at processing language than anything ever produced by the Chomsky School of Linguistics.”
Who is right, and how can we tell? Do we learn everything from scratch, or could some knowledge be innate? Is our brain one big network, or is it built out of modules, language being one of them?
In How Deeply Human Is Language?, Yosef Grodzinsky explains both approaches and confronts them with the reality as it emerges from the engineering, linguistic, and neurological record. He walks readers through vastly different methods, tools, and findings from all these fields. Aiming to find a common path forward, he describes the conflict, but also locates points of potential contact, and sketches a joint research program that may unite these communities in a common effort to understand knowledge and learning in the brain.
More details
Language
English
Place of publication
Cambridge (Massachusetts)
United States
Publishing group
MIT Press Ltd
Illustrations
29 BLACK AND WHITE ILLUS.
Dimensions
Height: 210 mm
Width: 152 mm
Weight
369 gr
ISBN-13
978-0-262-05200-9 (9780262052009)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
04/2026
MIT Press
€29.49
Available for download
Person
Yosef Grodzinsky
Content
Table of Contents
Acknowledgments
Prologue: Is bigger better?
Part 1 Where We are: The Language Sciences
Chapter 1. Grammars, old and new
Chapter 2: Hints from current day linguistic theory
Part 2 Where we are: The technology
Chapter 3. From Perceptrons to Deep Learning
Chapter 4 Dreams about Talking Machines: Large Language Models
Part 3: Getting under the hood
Chapter 5. A duel: Science vs. Technology
Chapter 6. Poking linguistic holes in LLMs (ChatGPT included)
Part 4 The Brain’s Language Code
Chapter 7. A mosaic of neurolinguistic modules
Chapter 8. Modeling the linguistic brain with LLMs Coda: are LLMs models for the brain’s language mechanisms?
Epilogue: shall we work together?
Acknowledgments
Prologue: Is bigger better?
Part 1 Where We are: The Language Sciences
Chapter 1. Grammars, old and new
Chapter 2: Hints from current day linguistic theory
Part 2 Where we are: The technology
Chapter 3. From Perceptrons to Deep Learning
Chapter 4 Dreams about Talking Machines: Large Language Models
Part 3: Getting under the hood
Chapter 5. A duel: Science vs. Technology
Chapter 6. Poking linguistic holes in LLMs (ChatGPT included)
Part 4 The Brain’s Language Code
Chapter 7. A mosaic of neurolinguistic modules
Chapter 8. Modeling the linguistic brain with LLMs Coda: are LLMs models for the brain’s language mechanisms?
Epilogue: shall we work together?