Domain-general and -specific individual difference predictors of an uncanny valley and uncanniness effects

Alexander Diel , Michael Lewis
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Abstract

Near humanlike artificial entities can appear eerie or uncanny. This uncanny valley is here investigated by testing five individual difference measures as predictors of uncanniness throughout a variety of stimuli. Coulrophobia predicted uncanniness of distorted faces, bodies, and androids and clowns; disgust sensitivity predicted the uncanniness of some distorted faces; the anxiety facet of neuroticism predicted the uncanniness of some distorted faces, bodies, and voices; deviancy aversion and need for structure predicted uncanniness of distorted places and voices. Taken together, the results suggest that while uncanniness can be caused by multiple, domain-independent (e.g., deviancy aversion) and domain-specific (e.g., disease avoidance) mechanisms, the uncanniness of androids specifically may be related to a fear of clowns, potentially due to a dislike of exaggerated human proportions.

不思议谷和不思议效应的一般领域和特定领域个体差异预测因素
近似人类的人造实体会显得阴森恐怖或不可思议。本文通过测试五种个体差异测量方法来预测各种刺激物的不可怖程度,从而研究这种不可怖谷。恐尸症预测了扭曲的面孔、身体、机器人和小丑的不可怖性;厌恶敏感性预测了某些扭曲的面孔的不可怖性;神经质的焦虑面预测了某些扭曲的面孔、身体和声音的不可怖性;离经叛道的厌恶和对结构的需求预测了扭曲的地方和声音的不可怖性。总之,研究结果表明,虽然不可爱可能是由多种独立于领域的机制(如偏执厌恶)和特定领域的机制(如疾病回避)造成的,但具体来说,机器人的不可爱可能与对小丑的恐惧有关,这可能是由于不喜欢夸张的人体比例造成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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