How communicative efficiency and social biases shape language in autistic and allistic learners

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In natural languages and in experimental studies of artificial language learning, case marking of grammatical arguments is more likely to be used in languages with flexible word order due to an efficiency trade-off between production effort and communicative accuracy. However, experimental evidence suggests that language learners are less efficient when there is a social bias in favour of a group whose productions are inefficient. Here, we examine the impact of autistic traits on efficient communication. We find that autistic people's use of case in the absence of a social bias is comparative to their neurotypical peers. However, we also find evidence that autistic people adhere more to social biases; they increase production effort in order to behave more like the group they are biased towards. We argue that some autistic people may be more likely to adhere to a social bias as a result of learnt social behaviours. More generally, these results underscore the importance of studying more diverse populations in language evolution research.
Original languageEnglish
Title of host publicationProceedings of the 45th Annual Conference of the Cognitive Science Society
PublisherCognitive Science Society
Pages2825-2832
Volume45
Edition45
Publication statusE-pub ahead of print - 12 Jul 2023
Event45th Annual Conference of the Cognitive Science Society: Cognition in Context - ICC Sydney, Sydney, Australia
Duration: 26 Jul 202329 Jul 2023
https://cognitivesciencesociety.org/cogsci-2023/

Publication series

NameProceedings of the Annual Meeting of the Cognitive Science Society
ISSN (Electronic)1069-7977

Conference

Conference45th Annual Conference of the Cognitive Science Society
Abbreviated titleCogSci 2023
Country/TerritoryAustralia
CitySydney
Period26/07/2329/07/23
Internet address

Keywords / Materials (for Non-textual outputs)

  • language evolution
  • neurodivergence
  • autism
  • artificial language learning
  • social biases
  • cultural evolution

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