Linguistics for the Age of AI

• Published in: The MIT Press eBooks
• Main Authors: McShane, Marjorie, Nirenburg, Sergei
• Format: eBook Book
• Language: English
• Published: Cambridge, Massachusetts MIT Press 2021; The MIT Press
• Edition: 1
• Series: The MIT Press
• Subjects: actionability; anaphoric event coreference; Artificial Intelligence; broad referring expressions; cognitive modelling; cognitive robotics; Cognitive Sciences; Cognitive studies; cognitive systems; component-level evaluation; Computaitonal linguistics; Computational linguistics; computational pragmatics; computational semantics; Computer Science; Computing and Information Technology; Computing and Processing; constructions; definite descriptions; ellipsis; error recovery; explanation; Extracting and representing meaning; fractured syntax; fragments; holistic evaluation; incongruities; incorporating; incrementality; indirect speech acts; Integrated NLU applications; intelligent agents; Interdisciplinary studies; knowledge bases; Language and Linguistics; language-endowed intelligent agent systems; language-endowed intelligent agents; Lexicography; linguistic and extralinguistic scope; Linguistics; Linguistics & Language; Machine learning; managing complexity; Maryland Virtual Patient; microtheories; Model and system evaluation; Modification; natural language processing; natural language processing (computer science); natural language understanding; NLP; non-literal language; OntoAgent cognitive architecture; personal pronouns; Pre-semantic analysis; proposition-level semantic enhancements; Reference, Information and Interdisciplinary subjects; Residual ambiguities; systems and models; theories; Theory and methodology; treating underspecified elements; underspecification; understanding; unknown words; Model and system evaluation; explanation; managing complexity; artificial intelligence; indirect speech acts; intelligent agents; knowledge bases; error recovery; understanding; fractured syntax; fragments; cognitive systems; language-endowed intelligent agent systems; computational semantics; cognitive robotics; Pre-semantic analysis; AI; anaphoric event coreference; personal pronouns; unknown words; microtheories; Extracting and representing meaning; constructions; cognitive modelling; incrementality; Modification; proposition-level semantic enhancements; actionability; language-endowed intelligent agents; holistic evaluation; computational linguistics; underspecification; definite descriptions; linguistic and extralinguistic scope; natural language understanding; Maryland Virtual Patient; broad referring expressions; NLP; Theory and methodology; incongruities; Residual ambiguities; OntoAgent cognitive architecture; incorporating; computational pragmatics; natural language processing; treating underspecified elements; non-literal language; Integrated NLU applications; ellipsis; theories; systems and models; component-level evaluation
• ISBN: 0262363135; 9780262363136; 9780262045582; 0262045583
• DOI: 10.7551/mitpress/13618.001.0001

A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. 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.