Category Processing and the human likeness dimension of the Uncanny Valley Hypothesis: Eye-Tracking Data

Cheetham, Marcus; Pavlović, Ivana; Jordan, Nicola; Suter, Pascal; Jäncke, Lutz

doi:10.3389/fpsyg.2013.00108

Cited by 59 publications

(70 citation statements)

References 107 publications

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“…Consistently, one image morphing study has demonstrated that human-likeness manipulations of eyes explain most (albeit not all) of the perceived animacy of faces (Looser and Wheatley, 2010). Similarly, one eye tracking study has demonstrated that eyes receive longer gaze dwell time on categorically ambiguous than on categorically unambiguous artificial faces (Cheetham et al, 2013). To our knowledge, the previous suggestion that negative affinity would be caused by inconsistent static and dynamic information (Brenton et al, 2005; Pollick, 2010) also remains unexplored.…”

Section: Discussionmentioning

confidence: 95%

A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness

et al. 2015

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The uncanny valley hypothesis, proposed already in the 1970s, suggests that almost but not fully humanlike artificial characters will trigger a profound sense of unease. This hypothesis has become widely acknowledged both in the popular media and scientific research. Surprisingly, empirical evidence for the hypothesis has remained inconsistent. In the present article, we reinterpret the original uncanny valley hypothesis and review empirical evidence for different theoretically motivated uncanny valley hypotheses. The uncanny valley could be understood as the naïve claim that any kind of human-likeness manipulation will lead to experienced negative affinity at close-to-realistic levels. More recent hypotheses have suggested that the uncanny valley would be caused by artificial–human categorization difficulty or by a perceptual mismatch between artificial and human features. Original formulation also suggested that movement would modulate the uncanny valley. The reviewed empirical literature failed to provide consistent support for the naïve uncanny valley hypothesis or the modulatory effects of movement. Results on the categorization difficulty hypothesis were still too scarce to allow drawing firm conclusions. In contrast, good support was found for the perceptual mismatch hypothesis. Taken together, the present review findings suggest that the uncanny valley exists only under specific conditions. More research is still needed to pinpoint the exact conditions under which the uncanny valley phenomenon manifests itself.

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Section: Discussionmentioning

confidence: 95%

A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness

et al. 2015

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“…It predicts that the "difficulty distinguishing between a humanlike object and its natural human counterpart will evoke negatively valenced feelings and cognitions" [8, p. 1], known as the "uncanny valley". We define human likeness as the extent to which robots more closely resemble people that also includes the physical humanlike similarity to robots [29,8]. Figure 3 depicts the human perception of different entities in dependence to the degree of human likeness.…”

Section: Uncanny Valley Paradigm the Uncanny Valley Paradigm Was Firmentioning

confidence: 99%

Robotic Psychology. What Do We Know about Human-Robot Interaction and What Do We Still Need to Learn?

Stock¹,

Nguyễn²

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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"Robotization", the integration of robots in human life will change human life drastically. In many situations, such as in the service sector, robots will become an integrative part of our lives. Thus, it is vital to learn from extant research on human-robot interaction (HRI). This article introduces robotic psychology that aims to bridge the gap between humans and robots by providing insights into particularities of HRI. It presents a conceptualization of robotic psychology and provides an overview of research on service-focused human-robot interaction. Theoretical concepts, relevant to understand HRI with are reviewed. Major achievements, shortcomings, and propositions for future research will be discussed.

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“…The categorical perception hypothesis is in line with insights from evolutionary biology linking categorization to survival and the failure to categorize stimuli to negative emotional responses (Burleigh & Schoenherr, 2015). Psychological research has further demonstrated that category boundaries exist for identification of facial images along morphed spectra (Cheetham, Pavlovic, Jordan, Suter, & Jancke, 2013;Cheetham et al, 2011;Cheetham, Suter, & Jancke, 2014;Looser & Wheatley, 2010;Yamada, Kawabe, & Ihaya, 2013; see Figure 1 for an illustration of the category boundary concept), and that discrimination performance reaches its peak when agent images straddle the category boundary, indicating categorical ambiguity (Cheetham et al, 2011(Cheetham et al, , 2014Looser & Wheatley, 2010). Increased categorical ambiguity has been reported to coincide with negative stimulus evaluations in some studies (Burleigh, Schoenherr, & Lacroix, 2013;Ferrey, Burleigh, & Fenske, 2015;Yamada et al, 2013) but not in others (Cheetham et al, 2014;Looser & Wheatley, 2010;.…”

Section: Introductionmentioning

confidence: 57%

It matters to me if you are human: Categorical perception in human and nonhuman agent spectra

Wiese¹,

Weis²

2019

Preprint

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Humanlike but not perfectly human agents frequently evoke feelings of eeriness, a phenomenon termed the Uncanny Valley (UV). The Categorical Perception Hypothesis proposes that effects associated with the UV are due to uncertainty as to whether to categorize agents falling into the valley as “human” or “nonhuman”. However, since UV studies have traditionally looked at agents of varying human-likeness, it remains unclear whether UV-related effects are due to categorical uncertainty in general or are specifically evoked by categorizations that require decisions regarding an agent’s human-likeness. Here, we used mouse tracking to determine whether agent spectra with (i.e., robot-human) and without (i.e., robot-animal and robot-stuffed animal) a human endpoint cause phenomena related to categorical perception to comparable extents. Specifically, we compared human and nonhuman agent spectra with respect to existence and location of a category boundary (H1-1 and H2-1), as well as the magnitude of cognitive conflict around the boundary (H1-2 and H2-2). The results show that human and nonhuman spectra exhibit category boundaries (H1-1) at which cognitive conflict is higher than for less ambiguous parts of the spectra (H1-2). However, in human agent spectra cognitive conflict maxima were more pronounced than for nonhuman agent spectra (H2-1) and category boundaries were shifted towards the human endpoint of the spectrum (H2-2). Overall, these results suggest a quantitatively, though not qualitatively, different categorization process for spectra containing human endpoints. Possible reasons and the impact for virtual and robotic agent design are discussed.

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Category Processing and the human likeness dimension of the Uncanny Valley Hypothesis: Eye-Tracking Data

Cited by 59 publications

References 107 publications

A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness

A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness

Robotic Psychology. What Do We Know about Human-Robot Interaction and What Do We Still Need to Learn?

It matters to me if you are human: Categorical perception in human and nonhuman agent spectra

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