Pascal Suter
Papers
1
Total Citations
71
H-Index
1
About
Pascal Suter is a cognitive scientist whose research explores the intersection of perception, emotion, and social cognition, with a particular focus on the Uncanny Valley phenomenon. His most cited work, "Perceptual discrimination difficulty and familiarity in the Uncanny Valley: more like a 'Happy Valley'" (2014, 71 citations), challenges traditional interpretations of the Uncanny Valley Hypothesis by demonstrating that difficulty in discriminating between human and humanlike stimuli does not necessarily evoke negative affect. Instead, Suter’s findings suggest that such perceptual ambiguity can lead to positive emotional responses, reframing the "uncanny" as potentially "happy." This contribution has reshaped debates in robotics, computer graphics, and psychology, offering a nuanced understanding of how humans respond to realistic artificial agents. Suter’s work is widely cited for its methodological rigor, employing signal detection theory and ABX discrimination tasks to disentangle perceptual from affective processes. His research has implications for designing more acceptable humanoid robots and virtual characters, making him a key figure in human-robot interaction and affective computing.
Research Focus
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Top Papers
- 1