32.2038, Books: Linguistics for the Age of AI: McShane, Nirenburg

[The LINGUIST List]

LINGUIST List: Vol-32-2038. Fri Jun 11 2021. ISSN: 1069 - 4875.

Subject: 32.2038, Books: Linguistics for the Age of AI: McShane, Nirenburg

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Date: Fri, 11 Jun 2021 17:21:16
From: Kailey Tse-Harlow [kailey at mit.edu]
Subject: Linguistics for the Age of AI: McShane, Nirenburg

 


Title: Linguistics for the Age of AI 
Publication Year: 2021 
Publisher: MIT Press
	   http://mitpress.mit.edu/
	

Book URL: https://mitpress.mit.edu/books/linguistics-age-ai 


Author: Marjorie McShane
Author: Sergei Nirenburg

Hardback: ISBN:  9780262045582 Pages: 448 Price: U.S. $ 75


Abstract:

One of the original goals of artificial intelligence research was to endow
intelligent agents with human-level natural language capabilities. Recent AI
research, however, has focused on applying statistical and machine learning
approaches to big data rather than attempting to model what people do and how
they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the
original goal of recreating human-level intelligence in a machine. They
present a human-inspired, linguistically sophisticated model of language
understanding for intelligent agent systems that emphasizes meaning—the deep,
context-sensitive meaning that a person derives from spoken or written
language.

With Linguistics for the Age of AI, McShane and Nirenburg offer a roadmap for
creating language-endowed intelligent agents (LEIAs) that can understand,
explain, and learn. They describe the language-understanding capabilities of
LEIAs from the perspectives of cognitive modeling and system building,
emphasizing “actionability”—which involves achieving interpretations that are
sufficiently deep, precise, and confident to support reasoning about action.
After detailing their microtheories for topics such as semantic analysis,
basic coreference, and situational reasoning, McShane and Nirenburg turn to
agent applications developed using those microtheories and evaluations of a
LEIA's language understanding capabilities.

McShane and Nirenburg argue that the only way to achieve human-level language
understanding by machines is to place linguistics front and center, using
statistics and big data as contributing resources. They lay out a long-term
research program that addresses linguistics and real-world reasoning together,
within a comprehensive cognitive architecture.
 



Linguistic Field(s): Cognitive Science
                     Computational Linguistics


Written In: English  (eng)

See this book announcement on our website: 
http://linguistlist.org/pubs/books/get-book.cfm?BookID=154493




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