Human Perception of Animacy in Light of the Uncanny Valley Phenomenon

Abstract

The uncanny valley hypothesis by Japanese roboticist Masahiro Mori posits a nonlinear relation between human replicas' human likeness and the emotional responses they elicit. In three studies, we corroborated the uncanny valley hypothesis, using the uncanny phenomenon as a vehicle to shed a new light on human animacy perception. In Study 1, 62 participants rated emotional responses and human likeness of 89 artificial and human faces. In Study 2, another 62 participants conducted a visual looming task with the same 89 faces allowing for the measurement of perceived threat. Results support the uncanny valley hypothesis, suggesting that the uncanny feeling may serve a function to wary humans of the potential danger of entities crossing the animate-inanimate boundary. In Study 3, 36 participants sorted faces as either real or unreal as quickly as possible in a reaction time sorting task allowing for the measurement of categorical uncertainty associated with animacy perception. Faces associated with longer sorting reaction times were also those associated with the highest ratings of negative emotions, suggesting that categorical uncertainty in animacy detection is related to the uncanny feeling. Results are discussed in light of human animacy perception and new directions for future research are suggested.

Different Realism Designs of 2D Virtual Agents and i ts' Arousal Effect on Students’ Emotions in Learning

“…Thus, the flat looking 2D cartoon-like agent was less attractive to the students compared to other agents. This strengthens the argument by Wang and Rochat (2017) who stated that the unreal faces were significantly less attractive than the real faces. Consequently, students were less intense to the design of the cartoon-like agent and thus caused the lowest arousal rate among them.…”

The Uncanny Valley Phenomenon and the Temporal Dynamics of Face Animacy Perception

“…We recruited 58 undergraduate students ( M age = 19.01, SD = 1.78) from Emory University with normal or corrected-to-normal vision for our study. The sample size was determined based on previous research (Wang & Rochat, 2017). Participants received course credits and were debriefed after testing.…”

“…The stimuli were 57 static, color, images of faces used in our previous research (Wang & Rochat, 2017; Wang et al., 2020) featuring humans ( n = 19), androids ( n = 25), and mechanical-looking robots ( n = 13; see Appendix A). We cropped, resized, and converted these images to PNG format.…”

“…They argue that the uncanny valley is due to humans’ ascription of minds to robots, which violates humans’ expectations for machines lacking human capacities to feel and sense (H. M. Gray et al., 2007; Mind Perception Hypothesis ). Nevertheless, the authors did not address why the ascription of mind would be associated with eerie feelings mostly in entities highly resembling humans, such as androids (Mathur & Reichling, 2016; Wang & Rochat, 2017), but not among pets, cartoon characters, or mechanical-looking robots (Misselhorn, 2009).…”

Reducing the Noise of Reality

“…In the pursuit of ecological validity, researchers tempted to faithfully reproduce a snapshot of reality have a higher risk to encounter this effect than researchers limiting themselves to simpler, less realistic, stimuli. Research on this uncanny valley effect lacks consistency regarding the prevalence and explanation of the effect (Cheetham, 2017;Lay, Brace, Pike, & Pollick, 2016;Wang & Rochat, 2017). However, it may be that the effect is related to a discrepancy between expectations raised by an anthropomorphic "entity" and its observed behavior (Złotowski et al, 2015).…”