When categorization-based stranger avoidance explains the uncanny valley: A comment on MacDorman and Chattopadhyay (2016)

Takahiro Kawabe, Kyoshiro Sasaki, Keiko Ihaya, Yuki Yamada

Research output: Contribution to journalComment/debate

6 Citations (Scopus)

Abstract

Artificial objects often subjectively look eerie when their appearance to some extent resembles a human, which is known as the uncanny valley phenomenon. From a cognitive psychology perspective, several explanations of the phenomenon have been put forth, two of which are object categorization and realism inconsistency. Recently, MacDorman and Chattopadhyay (2016) reported experimental data as evidence in support of the latter. In our estimation, however, their results are still consistent with categorization-based stranger avoidance. In this Discussions paper, we try to describe why categorization-based stranger avoidance remains a viable explanation, despite the evidence of MacDorman and Chattopadhyay, and how it offers a more inclusive explanation of the impression of eeriness in the uncanny valley phenomenon.

Original languageEnglish
Pages (from-to)129-131
Number of pages3
JournalCognition
Volume161
DOIs
Publication statusPublished - Apr 1 2017

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Language and Linguistics
  • Developmental and Educational Psychology
  • Linguistics and Language
  • Cognitive Neuroscience

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