LINGUIST List 32.2038

Fri Jun 11 2021

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

Editor for this issue: Billy Dickson <billydlinguistlist.org>



Date: 11-Jun-2021
From: Kailey Tse-Harlow <kaileymit.edu>
Subject: Linguistics for the Age of AI: McShane, Nirenburg
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Title: Linguistics for the Age of AI
Published: 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:
https://linguistlist.org/pubs/books/get-book.cfm?BookID=154493



Page Updated: 11-Jun-2021