When categorization-based stranger avoidance explains the uncanny valley: A comment on MacDorman & Chattopadhyay (2016)
September 11, 2016 Β· Declared Dead Β· π Cognition
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Authors
Takahiro Kawabe, Kyoshiro Sasaki, Keiko Ihaya, Yuki Yamada
arXiv ID
1609.03191
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY,
cs.RO
Citations
22
Venue
Cognition
Last Checked
4 months ago
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.
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