The success of Large Language Models (LLMs) in many application domains suggests that they may also change how we conceive cognition. LLMs possess capabilities traditionally considered exclusively human. Can the experience with language alone facilitate the acquisition of other complex cognitive abilities? Do linguistic, sensorimotor, and interoceptive experiences need to be integrated? Are there domains, like that of abstract concepts (e.g., freedom), where linguistic experience suffices to capture meaning? After introducing what LLMs are, we address their potential impact, discussing five differences from human cognition: they are not grounded, lack action, hardly capture pragmatics, are culturally biased, and do not reflect individual characteristics.

Exploring the prospects and challenges of large language models for language learning and production

Borghi A. M.;Mannella F.;Tummolini L.;Nolfi S.
2023

Abstract

The success of Large Language Models (LLMs) in many application domains suggests that they may also change how we conceive cognition. LLMs possess capabilities traditionally considered exclusively human. Can the experience with language alone facilitate the acquisition of other complex cognitive abilities? Do linguistic, sensorimotor, and interoceptive experiences need to be integrated? Are there domains, like that of abstract concepts (e.g., freedom), where linguistic experience suffices to capture meaning? After introducing what LLMs are, we address their potential impact, discussing five differences from human cognition: they are not grounded, lack action, hardly capture pragmatics, are culturally biased, and do not reflect individual characteristics.
2023
Istituto di Scienze e Tecnologie della Cognizione - ISTC
abstract concepts
ChatGPT
cultures
grounded cognition
large language models
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/524302
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