English

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

Human-Computer Interaction 2016-09-21 v3 Computers and Society Robotics

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.

Cite

@article{arxiv.1609.03191,
  title  = {When categorization-based stranger avoidance explains the uncanny valley: A comment on MacDorman & Chattopadhyay (2016)},
  author = {Takahiro Kawabe and Kyoshiro Sasaki and Keiko Ihaya and Yuki Yamada},
  journal= {arXiv preprint arXiv:1609.03191},
  year   = {2016}
}

Comments

published in Cognition

R2 v1 2026-06-22T15:46:15.421Z