Hypothesized emotional response of subjects is plotted against anthropomorphism of a robot, following Masahiro Mori's statements. The uncanny valley is the region of negative emotional response towards robots that seem "almost" human. Movement amplifies the emotional response.

In aesthetics, the uncanny valley (Japanese: 不気味の谷, Hepburn: bukimi no tani) is a hypothesized relation between an object's degree of resemblance to a human being and the emotional response to the object. The concept suggests that humanoid objects that imperfectly resemble actual human beings provoke uncanny or strangely familiar feelings of uneasiness and revulsion in observers. "Valley" denotes a dip in the human observer's affinity for the replica—a relation that otherwise increases with the replica's human likeness.

Examples of the phenomenon exist among robotics, 3D computer animations and lifelike dolls. The rising prevalence of technologies e.g., virtual reality, augmented reality, and photorealistic computer animation has propagated discussions and citations of the "valley"; such conversation has enhanced the construct's verisimilitude. The uncanny valley hypothesis predicts that an entity appearing almost human will risk eliciting cold, eerie feelings in viewers.


Robotics professor Masahiro Mori first introduced the concept in 1970 from his book titled Bukimi No Tani (不気味の谷), phrasing it as bukimi no tani genshō (不気味の谷現象, lit.'uncanny valley phenomenon').[1] Bukimi no tani was literally translated as uncanny valley in the 1978 book Robots: Fact, Fiction, and Prediction written by Jasia Reichardt.[2] Over time, this translation created an unintended link of the concept to Ernst Jentsch's psychoanalytic concept of the uncanny established in his 1906 essay On the Psychology of the Uncanny (German: Zur Psychologie des Unheimlichen),[3][4] which was then famously critiqued and extended in Sigmund Freud's 1919 essay The Uncanny (German: Das Unheimliche).[5]


In an experiment involving the human lookalike robot Repliee Q2 (pictured above), the uncovered robotic structure underneath Repliee, and the actual human who was the model for Repliee, the human lookalike triggered the highest level of mirror neuron activity.[6]

Mori's original hypothesis states that as the appearance of a robot is made more human, some observers' emotional response to the robot becomes increasingly positive and empathetic, until it reaches a point beyond which the response quickly becomes strong revulsion. However, as the robot's appearance continues to become less distinguishable from a human being, the emotional response becomes positive once again and approaches human-to-human empathy levels.[7] When plotted on a graph, the reactions are indicated by a deep trough (hence the "valley" part of the name) in the areas where anthropomorphism is closest to reality.

This area of repulsive response aroused by a robot with appearance and motion between a "somewhat human" and "fully human" entity is the uncanny valley. The name captures the idea that an almost human-looking robot seems overly "strange" to some human beings, produces a feeling of uncanniness, and thus fails to evoke the empathic response required for productive human–robot interaction.[7]

Theoretical basis

A number of theories have been proposed to explain the cognitive mechanism underlying the phenomenon:


An empirically estimated uncanny valley for static robot face images[17]

A series of studies experimentally investigated whether uncanny valley effects exist for static images of robot faces. Mathur MB & Reichling DB[17] used two complementary sets of stimuli spanning the range from very mechanical to very human-like: first, a sample of 80 objectively chosen robot face images from Internet searches, and second, a morphometrically and graphically controlled 6-face series set of faces. They asked subjects to explicitly rate the likability of each face. To measure trust toward each face, subjects completed a one-shot investment game to indirectly measure how much money they were willing to "wager" on a robot's trustworthiness. Both stimulus sets showed a robust uncanny valley effect on explicitly-rated likability and a more context-dependent uncanny valley on implicitly-rated trust. Their exploratory analysis of one proposed mechanism for the uncanny valley, perceptual confusion at a category boundary, found that category confusion occurs in the uncanny valley but does not mediate the effect on social and emotional responses.

One study conducted in 2009 examined the evolutionary mechanism behind the aversion associated with the uncanny valley. A group of five monkeys were shown three images: two different 3D monkey faces (realistic, unrealistic), and a real photo of a monkey's face. The monkeys' eye-gaze was used as a proxy for preference or aversion. Since the realistic 3D monkey face was looked at less than either the real photo, or the unrealistic 3D monkey face, this was interpreted as an indication that the monkey participants found the realistic 3D face aversive, or otherwise preferred the other two images. As one would expect with the uncanny valley, more realism can lead to less positive reactions, and this study demonstrated that neither human-specific cognitive processes, nor human culture explain the uncanny valley. In other words, this aversive reaction to realism can be said to be evolutionary in origin.[30]

As of 2011, researchers at University of California, San Diego and California Institute for Telecommunications and Information Technology were measuring human brain activations related to the uncanny valley.[31][32] In one study using fMRI, a group of cognitive scientists and roboticists found the biggest differences in brain responses for uncanny robots in parietal cortex, on both sides of the brain, specifically in the areas that connect the part of the brain's visual cortex that processes bodily movements with the section of the motor cortex thought to contain mirror neurons. The researchers say they saw, in essence, evidence of mismatch or perceptual conflict.[12] The brain "lit up" when the human-like appearance of the android and its robotic motion "didn't compute". Ayşe Pınar Saygın, an assistant professor from UCSD, stated that "The brain doesn't seem selectively tuned to either biological appearance or biological motion per se. What it seems to be doing is looking for its expectations to be met – for appearance and motion to be congruent."[14][33][34]

Viewer perception of facial expression and speech and the uncanny valley in realistic, human-like characters intended for video games and film is being investigated by Tinwell et al., 2011.[35] Consideration is also given by Tinwell et al. (2010) as to how the uncanny may be exaggerated for antipathetic characters in survival horror games.[36] Building on the body of work already undertaken in android science, this research intends to build a conceptual framework of the uncanny valley using 3D characters generated in a real-time gaming engine. The goal is to analyze how cross-modal factors of facial expression and speech can exaggerate the uncanny. Tinwell et al., 2011[37] have also introduced the notion of an 'unscalable' uncanny wall that suggests that a viewer's discernment for detecting imperfections in realism will keep pace with new technologies in simulating realism. A summary of Angela Tinwell's research on the uncanny valley, psychological reasons behind the uncanny valley and how designers may overcome the uncanny in human-like virtual characters is provided in her book, The Uncanny Valley in Games and Animation by CRC Press.

Design principles

A number of design principles have been proposed for avoiding the uncanny valley:


A number of criticisms have been raised concerning whether the uncanny valley exists as a unified phenomenon amenable to scientific scrutiny:

Similar effects

If the uncanny valley is the result of general cognitive processes, there should be evidence in evolutionary history and cultural artifacts.[20] An effect similar to the uncanny valley was noted by Charles Darwin in 1839:

The expression of this [Trigonocephalus] snake's face was hideous and fierce; the pupil consisted of a vertical slit in a mottled and coppery iris; the jaws were broad at the base, and the nose terminated in a triangular projection. I do not think I ever saw anything more ugly, excepting, perhaps, some of the vampire bats. I imagine this repulsive aspect originates from the features being placed in positions, with respect to each other, somewhat proportional to the human face; and thus we obtain a scale of hideousness.

— Charles Darwin, The Voyage of the Beagle[52]

A similar "uncanny valley" effect could, according to the ethical-futurist writer Jamais Cascio, show up when humans begin modifying themselves with transhuman enhancements (cf. body modification), which aim to improve the abilities of the human body beyond what would normally be possible, be it eyesight, muscle strength, or cognition.[53] So long as these enhancements remain within a perceived norm of human behavior, a negative reaction is unlikely, but once individuals supplant normal human variety, revulsion can be expected. However, according to this theory, once such technologies gain further distance from human norms, "transhuman" individuals would cease to be judged on human levels and instead be regarded as separate entities altogether (this point is what has been dubbed "posthuman"), and it is here that acceptance would rise once again out of the uncanny valley.[53] Another example comes from "pageant retouching" photos, especially of children, which some find disturbingly doll-like.[54]

In visual effects

A number of films that use computer-generated imagery to show characters have been described by reviewers as giving a feeling of revulsion or "creepiness" as a result of the characters looking too realistic. Examples include the following:

Virtual actors

An increasingly common practice is to feature virtual actors in films: CGI likenesses of real actors used because the original actor either looks too old for the part or is deceased. Sometimes a virtual actor is created with involvement from the original actor (who may contribute motion capture, audio, etc.), while at other times the actor has no involvement. Reviewers have often criticized the use of virtual actors for its uncanny valley effect, saying it adds an eerie feeling to the movie. Examples of virtual actors that have received such criticism include replicas of Arnold Schwarzenegger in Terminator Salvation (2009)[91][92] and Terminator Genisys (2015),[93] Jeff Bridges in Tron: Legacy (2010),[94][95][96] Peter Cushing and Carrie Fisher in Rogue One (2016),[97][98] and Will Smith in Gemini Man (2019).[99]

The use of virtual actors is in contrast with digital de-aging, which can involve simply removing wrinkles from actors' faces. This practice has generally not faced uncanny valley criticism. One exception is the 2019 film The Irishman, in which Robert De Niro, Al Pacino and Joe Pesci were all de-aged to try to make them look up to 50 years younger: one reviewer wrote that the actors' "hunched and stiff" body language stood in marked contrast to their facial appearance,[100] while another wrote that when De Niro's character was in his 30s, he looked like he was 50.[101]

Deepfake software, which first began to be widely used in 2017, uses machine learning to graft one person's facial expressions onto another's appearance, thus providing an alternate approach to both creating virtual actors and digital de-aging. Various individuals have created web videos that use deepfake software to re-create some of the notable previous uses of virtual actors and de-aging in film.[101][102][103] Journalists have tended to praise these deepfake imitations, calling them "more naturalistic"[102] and "objectively better"[101] than the originals.

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General and cited sources

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  • Burleigh, T. J. & Schoenherr (2015). A reappraisal of the uncanny valley: categorical perception or frequency-based sensitization? Frontiers in Psychology, 5, 1488. doi:10.3389/fpsyg.2014.01488.
  • Burleigh, T. J., Schoenherr, J. R., & Lacroix, G. L. (2013). Does the uncanny valley exist? An empirical test of the relationship between eeriness and the human likeness of digitally created faces. Computers in Human Behavior, 29(3), 759–771. doi:10.1016/j.chb.2012.11.021
  • Chaminade, T., Hodgins, J. & Kawato, M. (2007). Anthropomorphism influences perception of computer-animated characters' actions. Social Cognitive and Affective Neuroscience, 2(3), 206–216.Journal of Vision, 16(11):7, 1–25. doi:10.1167/16.11.7
  • Cheetham, M., Suter, P., & Jancke, L. (2011). The human likeness dimension of the "uncanny valley hypothesis": Behavioral and functional MRI findings. Frontiers in Human Neuroscience, 5, 126.
  • Ferrey, A., Burleigh, T. J., & Fenske, M. (2015). Stimulus-category competition, inhibition and affective devaluation: A novel account of the Uncanny Valley. Frontiers in Psychology, 6, 249. doi:10.3389/fpsyg.2015.00249
  • Goetz, J., Kiesler, S., & Powers, A. (2003). Matching robot appearance and behavior to tasks to improve human-robot cooperation. Proceedings of the Twelfth IEEE International Workshop on Robot and Human Interactive Communication. Lisbon, Portugal.
  • Ishiguro, H. (2005). Android science: Toward a new cross-disciplinary framework. CogSci-2005 Workshop: Toward Social Mechanisms of Android Science, 2005, pp. 1–6.
  • Kageki, N. (2012). An uncanny mind (An interview with M. Mori). IEEE Robotics & Automation Magazine, 19(2), 112–108. doi:10.1109/MRA.2012.2192819
  • Kätsyri, J. & Förger, K. & Mäkäräinen, M. & Takala, T. (2015). A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness. Frontiers in Psychology, 6, 390. doi:10.3389/fpsyg.2015.00390
  • Misselhorn, C. (2009). Empathy with inanimate objects and the uncanny valley. Minds and Machines, 19(3), 345–359.
  • Moore, R. K. (2012). A Bayesian explanation of the 'Uncanny Valley' effect and related psychological phenomena. Scientific Reports, 2, 864, doi:10.1038/srep00864.
  • Mori, M. (1970/2012). The uncanny valley IEEE Robotics & Automation Magazine, 19(2), 98–100. doi:10.1109/MRA.2012.2192811
  • Mori, M. (2005). On the Uncanny Valley. Proceedings of the Humanoids-2005 workshop: Views of the Uncanny Valley. 5 December 2005, Tsukuba, Japan.
  • Pollick, F. E. (forthcoming). In search of the uncanny valley. In Grammer, K. & Juette, A. (Eds.), Analog communication: Evolution, brain mechanisms, dynamics, simulation. The Vienna Series in Theoretical Biology. Cambridge, Mass.: The MIT Press.
  • Ramey, C.H. (2005). The uncanny valley of similarities concerning abortion, baldness, heaps of sand, and humanlike robots. In Proceedings of the Views of the Uncanny Valley Workshop, IEEE-RAS International Conference on Humanoid Robots.
  • Saygin, A.P., Chaminade, T., Ishiguro, H. (2010) The Perception of Humans and Robots: Uncanny Hills in Parietal Cortex. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2716–2720). Austin, TX: Cognitive Science Society.
  • Saygin, A.P., Chaminade, T., Ishiguro, H., Driver, J. & Frith, C. (2011). The thing that should not be: Predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Social Cognitive and Affective Neuroscience, 7(4), 413–422. doi:10.1093/scan/nsr025
  • Schoenherr, J. R. & Burleigh, T. J. (2014). Uncanny sociocultural categories. Frontiers in Psychology, 5, 1456. doi:10.3389/fpsyg.2014.01456
  • Seyama, J., & Nagayama, R. S. (2007). The uncanny valley: Effect of realism on the impression of artificial human faces. Presence: Teleoperators and Virtual Environments, 16(4), 337–351. doi:10.1162/pres.16.4.337
  • Tinwell, A., Grimshaw, M., & Williams, A. (2010) Uncanny Behaviour in Survival Horror Games. Journal of Gaming and Virtual Worlds, 2(1), pp. 3–25.
  • Tinwell, A., Grimshaw, M., & Williams, A. (2011) The Uncanny Wall. International Journal of Arts and Technology, 4(3), pp. 326–341.
  • Tinwell, A., Grimshaw, M., Abdel Nabi, D., & Williams, A. (2011) Facial expression of emotion and perception of the Uncanny Valley in virtual characters. Computers in Human Behavior, 27(2), pp. 741–749.
  • Urgen, B. A. & Saygin, A. P. (2018). Uncanny valley as a window into predictive processing in the social brain. Neuropsychologia, 114, 181–185. doi:10.1016/j.neuropsychologia.2018.04.027
  • Vinayagamoorthy, V. Steed, A. & Slater, M. (2005). Building Characters: Lessons Drawn from Virtual Environments. Toward Social Mechanisms of Android Science: A CogSci 2005 Workshop. 25–26 July, Stresa, Italy, pp. 119–126.
  • Yamada, Y., Kawabe, T., & Ihaya, K. (2013). Categorization difficulty is associated with negative evaluation in the "uncanny valley" phenomenon. Japanese Psychological Research, 55(1), 20–32.
  • Zysk, W., Filkov, R., Feldmann, S. (2013). Bridging the Uncanny Valley - From 3D humanoid Characters to Virtual Tutors. The Second International Conference on E-Learning and E-Technologies in Education, ICEEE (2013),p. 54-59. ISBN 978-1-4673-5093-8, 2013 IEEE. doi:10.1109/ICeLeTE.2013.6644347
Views on the Uncanny Valley