Uncanny but not confusing: Multisite study of perceptual category confusion in the Uncanny Valley

Mathur, Maya B.; Reichling, David B.; Lunardini, Francesca; Geminiani, Alice; Antonietti, Alberto; Ruijten, Peter A. M.; Levitan, Carmel; Nave, Gideon; Manfredi, Dylan; Bessette-Symons, Brandy; Szuts, Attila; Aczél, Balázs

doi:10.1016/j.chb.2019.08.029

Cited by 55 publications

(35 citation statements)

References 33 publications

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“…Empirical studies have focused mainly on determining whether the UV effect exists or on testing the predictions of one of these theories ( Kätsyri, Förger, Mäkäräinen, & Takala, 2015 ; Lay, Brace, Pike, & Pollick, 2016 ; Zhang et al, 2020 ). More than two-thirds of UV studies have found that the UV effect exists ( Burleigh, Schoenherr, & Lacroix, 2013 ; Kim, Bruce, Brown, Visser, & Phillips, 2020 ; MacDorman & Ishiguro, 2006 ; Mathur & Reichling, 2015 ; Mathur et al, 2020 ; McDonnell, Breidt, & Bülthoff, 2012 ; Seyama & Nagayama, 2007 ). The effect has also been found in infants, children, and nonhuman primates ( Brink, Gray, & Wellman, 2019 ; Lewkowicz & Ghazanfar, 2012 ; Siebert et al, 2020 ; Tinwell & Sloan, 2014 ; Steckenfinger & Ghazanfar, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, with only a few exceptions (e.g. MacDorman & Chattopadhyay, 2016 , 2017 ; Mathur et al, 2020 ), emphasis has not been placed on theory comparison and falsification. Both are needed, given the large number of UV theories that have been proposed.…”

Section: Introductionmentioning

confidence: 99%

“… Schwind, Leicht, Jäger, Wolf, & Henze, 2018 ). Incremental transitions along the dimension are created by morphing ( MacDorman & Ishiguro, 2006 ), editing ( Mäkäräinen et al, 2014 ), or selecting stimuli ( Mathur et al, 2020 ). Stimuli have been derived from photographs of humans, animals, robots, dolls, cartoon and computer-animated characters, and other sources.…”

Section: Introductionmentioning

confidence: 99%

“…One aim of UV research is to replicate the UV curve using stimuli that vary in human likeness (e.g. Kim et al, 2020 , Mathur et al, 2020 ; McDonnell et al, 2012 ). Replicating the curve is not our current research goal.…”

Section: Introductionmentioning

confidence: 99%

“…Broadly construed, category uncertainty theories include explanations of the UV based on balance theory ( Tondu & Bardou, 2011 ), categorical perception ( Burleigh et al, 2013 ; Cheetham, Pavlovic, Jordan, Suter, & Jäncke, 2013 ; Looser & Wheatley, 2010 ; Wang, Cheong, Dilks, & Rochat, 2020 ), categorization difficulty ( Cheetham, Wu, Pauli, & Jäncke, 2015 ), categorization disfluency ( Carr, Hofree, Sheldon, Saygin, & Winkielman, 2017 ; Seyama & Nagayama, 2009 ), category ambiguity ( Burleigh & Schoenherr, 2015 ), category confusion aversion ( Mathur et al, 2020 ), cognitive dissonance ( MacDorman et al, 2009a ), cognitive load ( Yamada, Kawabe, & Ihaya, 2013 ), conflicting representations ( Ferrey, Burleigh, & Fenske, 2015 ), and sorites paradoxes ( Ramey, 2005 ). Despite the differences among these theories, they all imply that the UV effect correlates with categorization difficulty.…”

Section: Introductionmentioning

confidence: 99%

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Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories

Diel

MacDorman

2021

Journal of Vision

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In 1970, Masahiro Mori proposed the uncanny valley (UV), a region in a human-likeness continuum where an entity risks eliciting a cold, eerie, repellent feeling. Recent studies have shown that this feeling can be elicited by entities modeled not only on humans but also nonhuman animals. The perceptual and cognitive mechanisms underlying the UV effect are not well understood, although many theories have been proposed to explain them. To test the predictions of nine classes of theories, a within-subjects experiment was conducted with 136 participants. The theories’ predictions were compared with ratings of 10 classes of stimuli on eeriness and coldness indices. One type of theory, configural processing, predicted eight out of nine significant effects. Atypicality, in its extended form, in which the uncanny valley effect is amplified by the stimulus appearing more human, also predicted eight. Threat avoidance predicted seven; atypicality, perceptual mismatch, and mismatch+ predicted six; category+, novelty avoidance, mate selection, and psychopathy avoidance predicted five; and category uncertainty predicted three. Empathy's main prediction was not supported. Given that the number of significant effects predicted depends partly on our choice of hypotheses, a detailed consideration of each result is advised. We do, however, note the methodological value of examining many competing theories in the same experiment.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories

Diel

MacDorman

2021

Journal of Vision

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Natural conversations with a virtual being: How user experience with a current conversational AI model compares to expectations

Khvan

Choi

2023

Computer Animation & Virtual

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The present work investigates the effect of natural conversations with virtual beings on user perceptions with a current conversational AI model (Meta's BlenderBot). To this aim, we designed a virtual being from a deep learning‐generated face and a conversational AI model acting as a virtual conversation partner in an online conferencing software and evaluated it in 11 perceptions of social attributes. Compared to prior expectations, participants perceived the virtual being as distinctly higher in warmth (engaging, empathic, and approachable) but lower in realism and credibility after 5 days of 10 min daily conversations (Study 1). Further, we explored the idea of simplifying the technical setup to reduce the technical entry barrier for such AI applications (Study 2). To this aim, we conducted several trials of fine‐tuning a small conversational model of 90 million parameters until its performance metrics improved. Testing this fine‐tuned model with users revealed that this model was not perceived differently from a large conversational model (1.4 billion parameters). In summary, our findings show that recent progress in conversational AI has added warmth‐related aspects to the user experience with virtual beings, and that fine‐tuning a conversational AI model can be effective to reduce technical complexity.

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A Literature Review of the Research on the Uncanny Valley

Zhang

et al. 2020

Lecture Notes in Computer Science

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Uncanny but not confusing: Multisite study of perceptual category confusion in the Uncanny Valley

Cited by 55 publications

References 33 publications

Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories

Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories

Natural conversations with a virtual being: How user experience with a current conversational AI model compares to expectations

A Literature Review of the Research on the Uncanny Valley

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