Too real for comfort? Uncanny responses to computer generated faces
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As virtual humans approach photorealistic perfection, they risk making real humans uncomfortable. This intriguing phenomenon, known as the uncanny valley, is well known but not well understood. In an effort to demystify the causes of the uncanny valley, this paper proposes several perceptual, cognitive, and social mechanisms that have already helped address riddles like empathy, mate selection, threat avoidance, cognitive dissonance, and psychological defenses. In the four studies described herein, a computer generated human character's facial proportions, skin texture, and level of detail were varied to examine their effect on perceived eeriness, human likeness, and attractiveness. In Study I, texture photorealism and polygon count increased human likeness. In Study II, texture photorealism heightened the accuracy of human judgments of ideal facial proportions. In Study III, atypical facial proportions were shown to be more disturbing on photorealistic faces than on other faces. In Study IV, a mismatch in the size and texture of the eyes and face was especially prone to make a character eerie. These results contest the depiction of the uncanny valley as a simple relation between comfort level and human likeness. This paper concludes by introducing a set of design principles for bridging the uncanny valley.
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MacDorman et al. (2009) showed that extreme facial proportions were considered the most eerie at close to humanlike levels.
“Furthermore, the third study in the same article showed that extreme facial proportions were considered the most eerie at close to humanlike levels.”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as MacDorman et al., 2009
The same two studies demonstrated that the most negative affinity evaluations were elicited when artificially enlarged eyes were paired with the most realistic (fully human) faces (H4b).
“Two studies (Seyama and Nagayama, 2007; MacDorman et al., 2009) using continuous human-likeness manipulations demonstrated that the most negative affinity evaluations were elicited when the mismatch between the realism of eyes and faces was the greatest (H4a) and when artificially enlarged eyes were paired with the most realistic (fully human) faces (H4b).”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as MacDorman et al., 2009
MacDorman et al. (2009) demonstrated greater agreement for more realistic CG textures.
“Similar greater agreement for more realistic CG textures was demonstrated also in the second study of MacDorman et al. (2009).”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as MacDorman et al., 2009
Two studies (Seyama and Nagayama, 2007; MacDorman et al., 2009) using continuous human-likeness manipulations demonstrated that the most negative affinity evaluations were elicited when the mismatch between the realism of eyes and faces was greatest (H4a).
“Two studies (Seyama and Nagayama, 2007; MacDorman et al., 2009) using continuous human-likeness manipulations demonstrated that the most negative affinity evaluations were elicited when the mismatch between the realism of eyes and faces was the greatest (H4a) and when artificially enlarged eyes were paired with the most realistic (fully human) faces (H4b).”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as MacDorman et al., 2009
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Can robots elicit empathy? The effects of social robots’ appearance on emotional contagion
Yang, W., & Xie, Y. (2024) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2024.100049 · Cited by 42 · see citing works
The uncanny valley does not interfere with level-1 visual perspective taking
MacDorman, K. F., Srinivas, P., & Patel, H. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.01.051 · Cited by 37 · see citing works
Self-citationPerceived stigma and erotic technology: From sex toys to erobots
Dubé, S., Santaguida, M., Anctil, D., Zhu, C. Y., Thomasse, L., Giaccari, L., Oassey, R., Vachon, D., & Johnson, A. (2023) · Psychology & Sexuality · doi:10.1080/19419899.2022.2067783 · Cited by 29 · see citing works
- Authors
- MacDorman, K. F., Green, R. D., Ho, C.-C., & Koch, C. T.
- Affiliations
- Indiana University Indianapolis (US)
- Corresponding author
- MacDorman, Karl F.
- ORCID
- MacDorman, Karl F.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2009-05
- Volume
- 25
- Issue
- 3
- Pages
- 695-710
- ISSN
- 0747-5632 (ISSN-L)
- PMC
- PMC4264966
- OpenAlex
- W1986530040
- Cited by
- 533
- References
- 88
- Citations by year
- 2026: 23 · 2025: 36 · 2024: 41 · 2023: 37 · 2022: 44 · 2021: 32 · 2020: 33 · 2019: 42 · 2018: 28 · 2017: 30 · 2016: 37 · 2015: 48 · 2014: 18 · 2013: 26 · 2012: 12
- FWCI
- 24.80
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Computers in Human Behavior (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Purdue University Indianapolis (Indiana University) (submittedVersion)
- PMC
- Funders
- National Institute of General Medical Sciences (P20GM066402)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Keywords
- uncanny valley, computer-generated faces, photorealism, facial proportions, skin texture, polygon count, human-likeness, attractiveness, virtual characters, design principles
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