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Linguistics for the Age of AI
Marjorie McShane and Sergei Nirenburg
2021
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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.
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Keywords
- actionability
- AI
- anaphoric event coreference
- artificial intelligence
- broad referring expressions
- Cognitive Modelling
- Cognitive Robotics
- Cognitive science
- cognitive systems
- component-level evaluation
- Computational linguistics
- computational pragmatics
- computational semantics
- Computer science
- Computing & information technology
- 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
- language-endowed intelligent agent systems
- language-endowed intelligent agents
- Lexicography
- linguistic and extralinguistic scope
- Linguistics
- Machine learning
- managing complexity
- Maryland Virtual Patient
- microtheories
- Model and system evaluation
- Modification
- Natural Language Processing
- natural language understanding
- NLP
- non-literal language
- OntoAgent cognitive architecture
- personal pronouns
- Pre-semantic analysis
- proposition-level semantic enhancements
- Reference, information & interdisciplinary subjects
- Residual ambiguities
- systems and models
- thema EDItEUR::C Language and Linguistics::CF Linguistics::CFM Lexicography
- thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GT Interdisciplinary studies::GTK Cognitive studies
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
- Theories
- Theory and methodology
- treating underspecified elements
- underspecification
- understanding
- unknown words
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