Scoping review of the neural evidence on the uncanny valley

Vaitonytė, Julija; Alimardani, Maryam; Louwerse, Max M.

doi:10.1016/j.chbr.2022.100263

Cited by 12 publications

(8 citation statements)

References 96 publications

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“…A well-known effect in human-technology interaction is the uncanny valley (Mori, 1970), named after the nonlinear nature of humans' assessment of nonhuman entities. While people's assessment becomes more positive when artifacts feature human-like qualities, this trend sharply reverses as soon as entities are almost human-like, but still can be identified as non-human (for overviews, see Vaitonytė et al, 2023;Wang et al, 2015). This effect with its primary roots in visual appearance has been transferred to the psychological level in the form of an uncanny valley of the mind (Stein & Ohler, 2017).…”

Section: Anthropomorphization or Assistance?mentioning

confidence: 99%

Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization

Skulmowski

2024

Educ Psychol Rev

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Generative AIs have been embraced by learners wishing to offload (parts of) complex tasks. However, recent research suggests that AI users are at risk of failing to correctly monitor the extent of their own contribution when being assisted by an AI. This difficulty in keeping track of the division of labor has been shown to result in placebo and ghostwriter effects. In case of the AI-based placebo effect, users overestimate their ability while or after being assisted by an AI. The ghostwriter effect occurs when AI users do not disclose their AI use despite being aware of the contribution made by an AI. These two troubling effects are discussed in the context of the conflict between cognitive externalization and anthropomorphization. While people tend to offload cognitive load into their environment, they also often perceive technology as human-like. However, despite the natural conversations that can be had with current AIs, the desire to attribute human-like qualities that would require the acknowledgment of AI contributions appears to be lacking. Implications and suggestions on how to improve AI use, for example, by employing embodied AI agents, are discussed.

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Section: Anthropomorphization or Assistance?mentioning

confidence: 99%

Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization

Skulmowski

2024

Educ Psychol Rev

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“…Lastly, they suggest that less realistic faces may circumvent the unsettling 'uncanny valley' effect, which refers to the discomfort people experience when encountering human-like entities that are almost, but not quite, lifelike (Mori et al, 2012). Faces that fall into the uncanny valley are less liked (Thepsoonthorn et al, 2021), evoke unique eye movement patterns (Cheetham et al, 2013;Thepsoonthorn et al, 2021), and elicit distinct neural responses in humans (Vaitonytė et al, 2022). Given that people do not perceive avatars and 3D models as "real" faces, the emotional and neural responses they elicit may not accurately represent the intended phenomenon being measured, highlighting the need for continued research and development of more suitable alternatives.…”

Section: Controlling Face Dynamicsmentioning

confidence: 99%

Can deepfakes be used to study emotion perception? A comparison of dynamic face stimuli

Becker,

Conduit,

Chouinard

et al. 2024

Behav Res

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Video recordings accurately capture facial expression movements; however, they are difficult for face perception researchers to standardise and manipulate. For this reason, dynamic morphs of photographs are often used, despite their lack of naturalistic facial motion. This study aimed to investigate how humans perceive emotions from faces using real videos and two different approaches to artificially generating dynamic expressions – dynamic morphs, and AI-synthesised deepfakes. Our participants perceived dynamic morphed expressions as less intense when compared with videos (all emotions) and deepfakes (fearful, happy, sad). Videos and deepfakes were perceived similarly. Additionally, they perceived morphed happiness and sadness, but not morphed anger or fear, as less genuine than other formats. Our findings support previous research indicating that social responses to morphed emotions are not representative of those to video recordings. The findings also suggest that deepfakes may offer a more suitable standardized stimulus type compared to morphs. Additionally, qualitative data were collected from participants and analysed using ChatGPT, a large language model. ChatGPT successfully identified themes in the data consistent with those identified by an independent human researcher. According to this analysis, our participants perceived dynamic morphs as less natural compared with videos and deepfakes. That participants perceived deepfakes and videos similarly suggests that deepfakes effectively replicate natural facial movements, making them a promising alternative for face perception research. The study contributes to the growing body of research exploring the usefulness of generative artificial intelligence for advancing the study of human perception.

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“…The concept of uncanny valley ( bukimi no tani in Japanese) was initially introduced by Japanese roboticist Masahiro Mori in 1970 [ 6 ]. The UV proposes that our affinity for representations become stronger as they become more human-like, reaching a peak before a sudden descent into revulsion when these representations are “almost like humans but not quite authentically human” [ 7 ]. This nonlinear relation between human-likeness or similarity to humanness (x-axis) and affinity (y-axis) is represented as the UV curve [ 8 , 9 ] ( Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Many attempts have been made to verify the UV effect and to explain the UV effect through theories and hypotheses [ 7 , [10] , [11] , [12] ]. For example, the pathogen avoidance hypothesis [ 13 , 14 ] states that uncanny stimuli have imperfections that may signal transmissible diseases, hence triggering avoidance and disgust.…”

Section: Introductionmentioning

confidence: 99%