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Related Experiment Video

Updated: Mar 8, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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Categorization-based stranger avoidance does not explain the uncanny valley effect.

Karl F MacDorman1, Debaleena Chattopadhyay2

  • 1Indiana University School of Informatics and Computing, 535 West Michigan St., Indianapolis, IN 46202, USA.

Cognition
|January 23, 2017
PubMed
Summary

The uncanny valley effect, or eeriness from near-human entities, is not due to stranger categorization. Realism inconsistency theory better explains these negative feelings from conflicting perceptual cues.

Keywords:
AnthropomorphismComputer animationFace perceptionNoveltyStranger avoidance

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Area of Science:

  • Cognitive Psychology
  • Human-Computer Interaction
  • Robotics

Background:

  • The uncanny valley hypothesis suggests near-human entities evoke eeriness.
  • Categorization-based stranger avoidance theory posits this is due to novel category assignment.
  • Existing evidence and infant studies challenge the stranger avoidance explanation.

Purpose of the Study:

  • To test the validity of categorization-based stranger avoidance theory for the uncanny valley.
  • To investigate an alternative explanation: realism inconsistency theory.

Main Methods:

  • Replicated an experiment using a more realistic 3D computer model.
  • Analyzed viewer responses to near-human entities.

Main Results:

  • The study found no support for categorization-based stranger avoidance theory.
  • Realism inconsistency theory provides a more plausible explanation for uncanny valley phenomena.

Conclusions:

  • The uncanny valley is likely caused by prediction errors arising from conflicting perceptual cues between categories.
  • Realism inconsistency theory can explain negative responses to entities like computer-generated humans and even different species.