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Notice

AISB opportunities Bulletin Item

CALL FOR COMMENTARIES: "Individual differences predict sensitivity to the uncanny valley" by Karl F. MacDorman & Steven O. Entezari


Contact: k.dautenhahn@herts.ac.uk

*******Call for Commentaries*******

Individual differences predict sensitivity to the uncanny valley

by

Karl F. MacDorman & Steven O. Entezari

 
has been accepted for publication as a Target Article in the journal Interaction Studies
http://benjamins.com/#catalog/journals/is/main

The article can be accessed here:
http://homepages.stca.herts.ac.uk/~comqkd/Previous-get/MacDorman-2014-Target-Article.pdf
Commentaries are invited, up to 2000 words, including references.

Abstract of article:

It can be creepy to notice that something human-looking is not real. But can sensitivity to

this phenomenon, known as the uncanny valley, be predicted from superficially

unrelated traits? Based on results from at least 489 participants, this study examines the

relation between nine theoretically motivated trait indices and uncanny valley sensitivity,

operationalized as increased eerie ratings and decreased warmth ratings for androids

presented in videos. Animal Reminder Sensitivity, Neuroticism, its Anxiety facet, and

Religious Fundamentalism significantly predicted uncanny valley sensitivity. In addition,

Concern over Mistakes and Personal Distress significantly predicted android eerie

ratings but not warmth. The structural equation model indicated that Religious

Fundamentalism operates indirectly, through robot-related attitudes, to heighten

uncanny valley sensitivity, while Animal Reminder Sensitivity increases eerie ratings

directly. These results suggest that the uncanny valley phenomenon may operate

through both sociocultural constructions and biological adaptations for threat avoidance,

such as the fear and disgust systems. Trait indices that predict uncanny valley sensitivity

warrant investigation by experimental methods to explicate the processes underlying the

uncanny valley phenomenon.


Please send intentions to submit a commentary to Kerstin Dautenhahn 
([k.dautenhahn@herts.ac.uk]k.dautenhahn@herts.ac.uk 
 ) 
as soon as possible, suggesting a tentative title of the commentary.

Deadline for sending the commentary: 30  June 2014