Open AccessConceptual and Methodological Problems with Comparative Work on Artificial Language Learning
Author(s) -
Jeffrey Watumull,
Marc D. Hauser,
Robert C. Berwick
Publication year - 2014
Publication title -
biolinguistics
Language(s) - English
Resource type - Journals
ISSN - 1450-3417
DOI - 10.5964/bioling.8995
Subject(s) - computer science , clarity , language acquisition , field (mathematics) , cognitive science , human language , focus (optics) , artificial intelligence , linguistics , psychology , mathematics education , biochemistry , chemistry , mathematics , philosophy , physics , pure mathematics , optics
Several theoretical proposals for the evolution of language have sparked a renewed search for comparative data on human and non-human animal computational capacities. However, conceptual confusions still hinder the field, leading to experimental evidence that fails to test for comparable human competences. Here we focus on two conceptual and methodological challenges that affect the field generally: 1) properly characterizing the computational features of the faculty of language in the narrow sense; 2) defining and probing for human language-like computations via artificial language learning experiments in non-human animals. Our intent is to be critical in the service of clarity, in what we agree is an important approach to understanding how language evolved.