title: When categorization-based stranger avoidance explains the uncanny valley: A comment on MacDorman and Chattopadhyay (2016).
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.
authors.affiliation: NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Japan. Electronic address: kawabe.takahiro@lab.ntt.co.jp.
authors.forename: Takahiro
authors.initials: T
authors.lastname: Kawabe
authors.affiliation: Faculty of Arts and Science, Kyushu University, Japan; Japan Society for the Promotion of Science, Japan.
authors.forename: Kyoshiro
authors.initials: K
authors.lastname: Sasaki
authors.affiliation: Admission Center, Kyushu University, Japan.
authors.forename: Keiko
authors.initials: K
authors.lastname: Ihaya
authors.affiliation: Faculty of Arts and Science, Kyushu University, Japan.
authors.forename: Yuki
authors.initials: Y
authors.lastname: Yamada
mesh_terms: D006801:Humans; D012919:Social Behavior
keywords: Appearance; Categorization difficulty; Stranger avoidance; Uncanny valley