UNCANNY SCALE
Introduction
Why were we equipped with this eerie sensation? Is it essential for human beings? (Mori,
1970, p. 33).
Indeed, we get an impression that many languages are without a word for this particular
shade of what is frightening. (Freud, 1919, p. 220).
It is not often that Japanese roboticists and Sigmund Freud are puzzled by the same phenomenon—yet uncanniness concerns them both. As engineers develop increasingly human- like robots, they risk creating ghoulish monsters instead of helpful companions (MacDorman &
Ishiguro, 2006; Hanson, 2005). And our Freudian nightmares do not end there; animators are becoming more skilled at mimicking life, but their designs risk plunging into the uncanny valley
(Mori, 1970; Tinwell et al., 2011). What emotions define these kinds of surreal and eerie experiences? Thus far, no one can precisely define uncanny feelings. In this paper, we explore the concept of uncanniness, with regard to what people actually experience when events are not quite as they expected. We developed a scale measuring uncanny feelings, drawing on an array of theoretical perspectives on the uncanny.
Freud and the Unfamiliar-Familiar
The field’s relative neglect of the uncanny is surprising considering just how long people have struggled to understand it. For example, Ernst Jentsch (1906), the first to explore the psychological terrain around uncanniness, framed it as a general sense of uncertainty, and characterized it as any experience that makes one feel ill-at-ease or uncertain. By this account, uncanny feelings arise from “the human desire for the intellectual mastery of one’s environment”
(p. 16).
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The most famous treatment of the uncanny came from Freud (1919), who characterized uncanniness not as uncertainty per se, but as something that has transformed from certain to uncertain. Freud’s uncanny is what was once familiar made unfamiliar; a dark thought that has been hidden from consciousness, or a sense of supernatural coincidence (Freud, 1919). One anticipates a tolerable level of uncertainty in their lives; unfamiliarity is disturbing precisely when one is prepared for familiarity. One feels alienated by having their expectations undermined.
The tension between the known and unknown was further elaborated on by Andre Breton
(1924/1969) in his “Manifesto of Surrealism.” Breton described the surrealist art movement as the uncomfortable juxtaposition between the familiar and the unfamiliar. Uncanny feelings abounded as audiences tried to make sense of Rene Magritte’s painstaking rendering of human feet that could be tied up with bootlaces or Salvador Dali’s clocks melting off the edge of the table. The surrealists created images that were familiar to us, yet these images took on an entirely different meaning when placed in novel and unnatural settings.
The Uncanny Valley
While the uncanny largely fell off the radar for psychologists for several decades, interest in the topic re-emerged in an unlikely context. A roboticist, Masahiro Mori, publishing in the
Japanese journal, Energy, proposed the uncanny valley hypothesis (Mori, 1970), stating that people are disturbed by objects that are almost, but not quite, human. Wax figures, humanoid robots, rubber hands, and corpses feel eerie because they fall in the uncanny valley: they straddle the boundary between human and object (Mori, 1970; see Figure 1). As an object becomes more human, it becomes more familiar, and therefore, likeable. For example, stuffed animals are more
2 UNCANNY SCALE likable than pet rocks—but only to a point. A stuffed animal that is too human-like would enter the uncanny valley, and register as foreign and creepy.
Consider, for example, a visit to Madame Tussaud’s wax museum. You might see Britney
Spears circa 2001, but subtle qualities of the figure suggest something is not right. For one,
Britney is not so lively anymore. In fact, she is completely frozen. Her lifeless form has physical abnormalities, like glazed eyes and different-textured skin. These qualities are alarming because they don’t belong to the real Britney Spears, or indeed, any live person. The sculpture lies squarely between our familiarity with Britney Spears and the unmistakable signs that this is just a pile of painted wax.
Figure 1. Illustration of the Uncanny Valley.
Note. Figure of The
Uncanny Valley adapted
by MacDorman (2005a).
The graph shows two
curves; objects that
move (dotted line) and
objects that are
stationary (solid line).
Mori’s (1970) predictions regarding the uncanny valley have received mixed empirical support (e.g., Seyama &
Nagayama, 2007; Mathur & Reichling, 2016; Burleigh, Schoenherr, & Lacroix, 2013;
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MacDorman et al., 2009). Though the exact shape and location of the uncanny valley are debated, the consensus is that objects with overly human-like qualities make people’s skin crawl
(see Wang et al., 2015).
Uncanniness as uncertainty
What is so eerie about uncanny objects? It is possible they elicit uncertainty. Uncertainty and disorientation are core to the psychoanalytic conception of uncanniness (Jentsch, 1906;
Freud, 1919) and is a plausible explanation for objects falling into the uncanny valley. In processing an uncanny figure, people may be experiencing perceptual tension due to uncertainties about its category membership (Moore, 2012; Feldman, Griffiths, & Morgan,
2009). Studies of the uncanny using morphed faces support a category uncertainty explanation, as participants attribute the least certainty, and least positive evaluations, to morphed human- cartoon faces at the same point in the continuum (Yamada, Kawabe, & Ihaya, 2013).
Uncanniness as violated expectations
Uncanny objects may be uncertain, or they may create a sense of perceptual tension by appearing simultaneously familiar and unfamiliar (Freud, 1919). The wax figure that resembles a celebrity, but upon closer inspection, deviates from their likeness; a Magritte painting of a realistic looking man, but with an apple inexplicably hovering in front of his face (Saygin et al.,
2012; Mitchell et al., 2011), are examples of familiar objects violating people’s expectations.
Perhaps the source of uncanniness is not uncertainty, but violated expectations (MacDorman &
Ishiguro, 2006; MacDorman et al., 2009; see also Wang, Lilienfeld, & Rochat, 2015).
Violated expectations can follow from exposure to surreal art and film (Proulx, Heine, &
Vohs, 2010; Randles, Heine, & Santos, 2013) or surprising occurrences, like finding oneself arguing for a position that one doesn’t endorse (e.g., Randles, Inzlicht, Proulx, Tullett, & Heine,
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2015). It can even follow low-level conflicts, like mismatched word pairs (Randles, Proulx, &
Heine, 2011) or seeing a red king of spades (e.g., Randles, Benjamin, Martens, & Heine, 2018).
To the extent that people favour familiarity, uncanny objects and situations can produce aversive emotions. Expectancy violations appear to activate neural regions associated with anxiety (Gray and McNaughton, 2000; McNaughton & Corr, 2004; see also Jonas et al., 2014). People experience negative arousal when worldviews are threatened, or sense-making goals are frustrated (Heine et al., 2006; Holbrook & Sousa, 2013; McGregor, Nash, Mann, & Phills, 2010).
Therefore, the uncanny may characterize anxious responses to expectancy violations.
As we have reviewed, there have been many different perspectives on what is uncanny.
But how does it feel to encounter the uncertain or unexpected? What is the eeriness that we feel around humanoid robots? Though the above theories explain qualities of uncanny objects, none describe the affective experience of “uncanniness”. The subjective experience of uncanniness remains shrouded in mystery.
Uncanny feelings
Uncanniness may be a distinct category of emotion (Freud, 1919) or derivative from others like fear, disgust, and surprise (Ho, MacDorman, & Pramono, 2008). It might be existential dread (MacDorman, 2005b), or negative affect caused by low-level cognitive conflict
(Moore, 2012; Cheetham et al., 2015; Proulx et al., 2010). Following Freud’s definition, we posit that uncanniness is unique, though related to anxious arousal and other negative affective experiences. First, we review some alternative accounts.
Disgust. Disgust is one candidate for the basic emotion underlying uncanniness
(MacDorman et al., 2009, MacDorman & Entezari, 2015). Disgust enables humans to avoid contamination (Rozin, 1987), which could explain avoidance of uncanny objects (MacDorman &
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Ishiguro, 2006). If an android moves rigidly or has subtle morphological differences from healthy people, it could look diseased. This is consistent with Mori’s (1970) depiction of corpses and zombies at the lowest point in the uncanny valley. If uncanny objects signal disease, then uncanniness might be similar to disgust.
Fear. In addition to disgust, fear has been explicitly linked to uncanniness. Freud (1919) characterized uncanny objects as subsets of fearful objects. Mori (1970) suggested uncanny objects can appear sinister and may signal threat. One explanation for uncanny feelings is that they cause existential terror (Ho et al., 2008). Besides being corpse-like, uncanny objects remind people of death on a conceptual level (MacDorman & Ishiguro, 2006). Humanoid robots might force people to confront fearful notions that humans are not unique, or are automatons themselves (Freud, 1919; MacDorman et al., 2009). This derives from Terror Management
Theory, which contends that reminders that humans are not unique can cause existential terror
(Goldenberg et al., 2001).
Uncanny feelings may be encapsulated by disgust, fear, and existential terror. Indeed, disgust may describe how people might feel when they encounter Britney Spears’ wax figure; pallid and corpse-like, and fear accompanies plenty of encounters with uncanny objects. Yet there are uncanny objects that are neither disgusting nor scary; for example, Disney’s computer- generated imagery version of the Lion King (2019) and the Polar Express (2004; Rivera, 2019;
Geller, 2008). Uncanniness also goes beyond disgust and fear to include broader concepts: the surreal, and unfamiliar. In describing eerie or surreal situations—a ghost town or abandoned city square—neither fear nor disgust is comprehensive.
Overview of studies
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Across three studies, we developed and validated a scale measuring uncanny feelings. In
Study 1, we generated and refined a set of uncanny items. In Study 2, we examined the factor structure using confirmatory factor analysis, and tested the validity of the scale by examining its relationship with related constructs. Study 3 investigated how people thought about and responded to the 2020 coronavirus pandemic and evaluated their responses to our novel 16-item uncanniness scale. These studies contribute to the psychological and interdisciplinary understanding of this strange, eerie phenomenon of being confronted with what looms just beyond our understanding.
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Study 1
Participants watched one of three videos that were either expected to elicit uncanny feelings or not. We created a list of items to assess uncanny feelings and conducted an exploratory factor analysis.
Methods
Participants. We aimed for an item-subject ratio of 10:1 within the experimental conditions. On this basis, we recruited 1512 Americans from Amazon’s Mechanical Turk
(Mturk). We excluded 119 participants for failing one of two attention check questions, or for reporting (1) they only watched part of the clip or (2) watched Rabbits with the sound turned off.
We were left with a sample of 1393 (see Table 1 for demographic data from Studies 1-3).
Table 1. Demographics for Studies 1-3.
% Ethnicity or Race
White or Black or Latinx Other Age M (SD) % Female Study European African 1 34.48 (11.33) 59 68 11 7 14
2 37.27 (11.88) 63 71 9 6 14
3 38.83 (13.57) 53 68 6 6 20
Note. Participants entered their own gender and ethnicity in a free-response textbox.
Item generation. We generated items based on how the concept of uncanniness has been discussed in Freud’s “The Uncanny”, Mori’s (1970) discussion of the uncanny valley, and other scales measuring people’s judgments about uncanny objects (MacDorman & Chattopadhyay,
2016; Ho & MacDorman, 2010). We also generated items based on translations of uncanny
(unheimlich) to other languages (French, Spanish, Hebrew, English). We created 44 items that
8 UNCANNY SCALE tapped into this construct in various ways (see the SOM). We asked participants to indicate on a
7-point scale how much each item characterized their current experience.
Procedure
Participants watched one of three videos; the first video showed a series of highly realistic animations and humanoid robots (Robots condition); the second video showed a clip from a short surreal David Lynch (2002) film called “Rabbits” (Rabbits condition; previous studies have used this clip to elicit uncanniness; e.g., Randles et al., 2013); the third clip showed a clip from the
Peanuts TV series (neutral condition; all clips available on the OSF: https://osf.io/b4v9y/? view_only=83e0202e9de446cbaac17252cd2f3734). The first two clips were expected to elicit uncanny feelings so we expected that those who viewed them would report feeling more uncanny feelings than those in the neutral condition.
Results and Discussion
Exploratory Factor Analysis. We conducted a maximum likelihood factor analysis with direct oblimin rotation, allowing factors to correlate. The factor analysis was only conducted amongst participants assigned to the two uncanny conditions (as we expected that only these participants would be experiencing uncanny feelings). The sample size of those who viewed either of the uncanny videos was N=967. We had no a priori expectations of the factor structure.
We used an iterative strategy to determine the most effective measure of uncanniness; evaluating the initial factor structure, eliminating items with low loadings or high cross-loadings, and conducting a follow-up factor analysis. First, we investigated the number of factors to retain using the procedure of parallel analysis (Horn, 1965; Dinno, 2009). Parallel analysis compares the eigenvalues with those generated by simulated data to determine if they are capturing more
9 UNCANNY SCALE than random noise (Horn, 1965). This procedure revealed a five-factor solution would fit the data; the first five eigenvalues were 22.62, 2.81, 1.39, and 0.98, and 0.93.
We investigated the loadings to determine if the factors represented meaningful semantic categories. No items loaded onto the fourth or fifth factors higher than .454, and the first three factors accounted for 48% of the variance. Therefore, we eliminated items that did not load onto any of the first three factors (totalling six items). We investigated the three-factor structure
(eigenvalues were 19.81, 2.74, and 1.11). The third factor accounted for only 5.9% percent of the variance, compared to 22.5% (factor 1) and 16.9% (factor 2). Also, the third factor was a less face valid measure of uncanniness; it seemed to capture superstition rather than uncanniness (“I feel like something unearthly has taken place, “I feel like something mysterious has taken place”). We thus proceeded with a two-factor model (we present results of the three-factor model in the SOM). We eliminated items that did not load onto either of the two factors (14), as well as items with high cross-loadings (3). Among the remaining 21 items, eigenvalues for the two factors were 11.27 and 2.38.
A perusal of the items that loaded on to the first factor reveals that they were largely semantically related to strange feelings, whereas those that loaded on to the second factor were primarily related to disorientation. Though we had not predicted this structure, the two factors fit descriptions of (1) eerie, or unnerved feelings, and (2) feelings of the world being unpredictable and unfamiliar. We called these factors “unnerved” and “disoriented”, respectively. We continued to eliminate items with high cross-loadings (totaling six items). We present the final scale and factor loadings in Table 2.
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Table 2. Item loadings for the two-factor structure.
Factor Loadings Item Unnerved Disoriented I feel creeped out .891 -.131 I am uncomfortable .871 -.039 I am unsettled .861 -.019 I have an eerie sensation .818 . 022 I feel freaked out .781 . 063 I am uneasy .781 . 087 I feel very disturbed .772 .090 I feel weird .720 .108 I have a feeling that I’m not in charge of my actions -.073 .807 Right now, I lack control over my thoughts -.017 .804 Right now, many of my thoughts are about death -.047 .772 I feel like I don’t know anything anymore .059 .728 I feel like I’m stuck in a pattern I can’t get out of -.042 .693 I feel like I’m being followed .065 .689 I’m having dark thoughts right now .147 .659 I’m feeling alienated .143 .628
The two factors explained 33.5% and 26.6% of the variance, respectively. They were correlated at r = .631. Various indices suggested that this was a well-fitting model (RMSEA =
.043, .90 CI [.037, .049], χ2(89, N=965) = 248.72, p <.001, CFI = .985). Cronbach’s alpha was high (unnerved α=0.94, disoriented α=0.91, overall α = 0.94) suggesting high internal consistency.
Test of condition. Our measure should differentiate between an uncanny and neutral experience, and thus participants in the uncanny conditions should score higher on the scale than people in the control condition. Further, we sought to determine whether the Rabbits or the
Robots videos elicited more uncanny feelings.
We conducted a one-way ANOVA predicting the 16-item scale from experimental condition, which revealed a significant effect, F(2, 1247) = 101.67, p <.001, .95 CI [0.21, 0.38],
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η2 = .14. The most uncanniness was elicited by the Rabbits video (M = 3.26, SD = 1.22) followed by the Robots video (M = 2.67, SD = 1.29). The control condition elicited the least uncanniness (M = 1.98, SD = 1.10). We conducted follow-up tests with Holm-Bonferroni adjustments, finding that both uncanny conditions scored higher than the control condition;
Rabbits: t(666.18) = 15.10, p < .001, .95 CI [1.11, 1.44], d = 1.10, and Robots: t(691.45) =
7.92, .95 CI [0.86, 0.52], p < .001, d = 0.57. The Rabbits video also elicited greater responses than Robots, t(951) = 7.25, p <.001, .95 CI [0.43, 0.75], d = 0.47.
In summary, Study 1 established a measure of uncanny feelings that performs well across two distinct elicitors. We were curious if uncanniness could be differentiated from other candidate emotions (e.g., disgust, fear) and would converge with related personality variables that correspond with discomfort with uncertainty (e.g., personal need for structure, neuroticism).
Thus, we conducted Study 2 to establish convergent and discriminant validity and to conduct a confirmatory factor analysis.
Study 2
We compared participants who each watched 1 of 4 videos: an uncanny video, a disgusting video, a fearful video, or a neutral video. We hypothesized that participants who watched an uncanny clip would score the highest on the Uncanny scale. All materials for this study are pre-registered at https://osf.io/qg6st/? view_only=6a406a6175df438abfa11334977884d2.
Methods
Participants. According to our pre-registered recruitment plan, we recruited 900 participants anticipating that 100 would fail attention checks. A sample size of 800 participants would allow us to detect small effects with a probability of over 80%. We obtained 917
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American Mturk participants. We excluded participants who failed both of our attention checks or reported that they did not watch the clip completely. Fifty-seven participants were excluded, leaving a sample of 860 participants.
Procedure. After completing some personality measures (see below) participants were randomly assigned to watch a 90 second clip that we selected to be either uncanny, disgusting, fearful, or neutral. The uncanny clip was Rabbits (see Study 1) but was shortened to 90 seconds.
The fear clip was from “Scream 2” and showed a woman pursued by a masked killer. The disgusting clip was from “Indiana Jones and the Last Crusade” and showed a seething mass of rats in a cave. The neutral clip was from “Lost in Translation” and showed a woman and a man interacting. Past research shows these latter 3 clips specifically elicit their target emotions, without eliciting much of other measured emotions (e.g., Schaefer, 2010; Jenkins, 2012).
After watching one of the clips, participants responded to two attention check questions about its content. Then, they completed the 16-item measure of uncanniness, where they indicated whether each statement described their feelings right now on a 7-point scale ranging from 1=Not at all to 7=Very much. Next, participants completed our measures of discriminant and convergent validity (see below) followed by a demographics form, another attention check, and a quality check (indicating whether they watched the entire clip).
Measures
We hypothesized that uncanny feelings would be related to state anxiety, on the basis of past research connecting arousal to existential threats (McGregor, Prentice, & Nash, 2013; Jonas et al., 2014) and connecting anxiety to sensitivity to objects believed to fall into the uncanny valley (Ho et al., 2008; MacDorman & Entezari, 2015). We used the State-Trait Anxiety
Inventory (STAI; Spielberger et al., 1999) to measure state anxiety. We also measured
13 UNCANNY SCALE personality variables that we hypothesized would correlate with sensitivity to uncanniness. We included the Ten Item Personality Inventory (TIPI; Rammstedt & John, 2007), anticipating that neuroticism would predict feelings of uncanniness (neuroticism has been found to predict negative evaluations of uncanny valley objects; MacDorman & Entezari, 2015). We also measured people’s desire for structure in their experiences using the Personal Need for Structure scale (PNS; Newberg & Newsom, 1993), and also the Behavioral Inhibition and Behavioral
Activation measure (BIS/BAS; Carver & White, 1994).
One goal of the present study was to establish that uncanny feelings are different from fear and disgust. To this end, we developed two-item disgust measures (i.e., “How disgusted did the video make you feel?”, and “How grossed out did the video make you feel?”), two-item fear measures (i.e., “How scared did the video make you feel?”, and “How afraid did the video make you feel?”), and two-item uncanny measures (i.e., “How unnerved did the video make you feel?”, and “How disoriented did the video make you feel?”), all with scale endpoints ranging from 1 = Not at all to 10= Very. We included this last measure to establish convergent validity with the 16-item scale.
Results and Discussion
Our pre-registered predictions were that people higher in BIS sensitivity, Personal Need for Structure (PNS), and Neuroticism would experience greater uncanniness. We also predicted that State Anxiety would positively correlate with uncanniness (all four conditions were analyzed together; see Table 4).
The measure of BIS sensitivity was modestly correlated with the uncanny scale r = .159, p < .001, suggesting people who are higher in behavioral inhibition are somewhat more likely to report uncanny feelings. We also measured neuroticism as part of the TIPI. Neuroticism was also
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moderately correlated with the uncanny scale, r = .345, p < .001, suggesting that neuroticism is
associated with people’s tendency to report uncanniness. State anxiety was highly correlated
with scores on the uncanny scale, r = .689, p < .001, showing strong convergent validity. This
supports the theoretical model we are forwarding; anxiety and uncanniness are highly related.
Contrary to our expectations, people’s need for a structured orderly life (measured by the
PNS scale) was not a predictor of sensitivity to uncanniness using the 16-item scale, r = .025, p =
.466. It was neither correlated with the unnerved subscale, r = .041, p = .229, nor with the
disoriented subscale, r = .003, p = .933. Past studies suggest the need for structure is indeed
relevant to individuals’ processing of uncanny stimuli (see Lischetzke et al., 2017) so we
continued to probe this relationship in follow-up studies.
Table 4. Means and correlations between items.
Mean 1 2 3 4 5 6 7 8 9 (SD) 2.48 0.941* 0.907* 0.845* 0.184* 0.777* 0.635* 0.484* 1 Uncanny Scale (α= 0.97) - 0.075 (1.52) ** ** ** ** ** ** ** 2.70 0.711* 0.928* 0.212* 0.765* 0.686* 0.502* 2 Subscale 1 (α= 0.97) .956*** - 0.091* (1.74) ** ** ** ** ** ** 2.27 0.601* 0.118* 0.662* 0.466* 0.382* 3 Subscale 2 (α= 0.94) .938*** .794*** - 0.043 (1.47) ** * ** ** ** 3.50 0.163* 0.654* 0.679* 0.492* 4 Neuroticism .345*** .329*** .324*** - 0.078* (1.37) ** ** ** ** 4.68 0.423* 5 Personal Need for Structure (α= 0.82) .025 .041 .003 .224*** - 0.100* 0.059 0.041 (0.73) ** 2.92 0.362* 6 Behavioral Inhibition (α= 0.81) .159*** .189*** .105** .549*** .396*** - 0.082* 0.038 (0.59) ** 2.44 0.504* 0.352* 7 State Anxiety (α= 0.95) .689*** .695*** .603*** .547*** .112*** .345*** - (0.90) ** ** 2.59 0.616* 8 Fear .713*** .740*** .600*** .193*** .050 .065 .475*** - (2.99) ** 2.55 9 Disgust .555*** .540*** .508*** . 082* .041 -.019 .287*** .671*** - (2.99)
Note. Means and correlations were calculated using all four experimental conditions.
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We determined if the scale discriminates between emotions that are theoretically similar to uncanniness; namely, fear and disgust. Using the two-item measures of disgust and of fear, we tested whether the Uncanny scale was functionally separate from these two constructs. We determined that Fear correlated highly with the overall scale, r = .713, p < .001. Disgust also correlated highly with the overall scales, r = .555, p < .001. These correlations suggest that uncanniness has much similarity with both fear and disgust. We address this issue with analyses described below.
Effect of Condition. Given the high correlations between Disgust, Fear, and the
Uncanny measures, we assessed whether these emotions are differently predicted by the uncanny scale, As pre-registered, we next tested whether our scale can discriminate between participants who watched an uncanny clip from those who watched a scary or disgusting clip1.
A one-way ANOVA revealed that condition predicted uncanniness, F(3, 856) = 18.52, p
<.001, η2 = .06. The most uncanniness was elicited by the Rabbits clip (M = 2.95, SD = 1.53) followed by fear (M = 2.59, SD = 1.56) and disgust (M = 2.40, SD = 1.58). The control clip elicited the least uncanniness (M = 1.88, SD = 1.13). We used Holm-Bonferroni adjustments, finding that the control video elicited less uncanniness than any other condition; Uncanny: t(405.43) = 8.13, p < .001, .95 CI [0.81, 1.33], d = 0.78; Fear: t(403.93) = 5.36, p < .001, .95 CI
[0.45, 0.97], d = 0.52; Disgust: t(396.94) = 3.85, p = .001, .95 CI [0.25, 0.78], d = 0.37. The fear and disgust conditions did not differ from each other, t(445.61) = 1.31, p = .166, .95 CI [-0.01,
0.48], d = 0.12, but participants in the uncanny condition scored higher than those in the fear condition, t(449.87) = 2.46, p = .020, .95 CI [0.07, 0.64], d = 0.23, and those in the disgust condition, t(445.03) = 3.75, p < .001, .95 CI [0.26, 0.84], d = 0.36.
1 Our pre-registered analysis plan was to test dummy-coded variables in a linear regression analysis, which we present in the SOM. 16 UNCANNY SCALE
Are disgust and fear better predictors of the other two clips? Our next goal was to establish that the disgust stimulus elicits the most disgust, and the fear stimulus elicits the most fear. We predicted the two-item fear and disgust measures from experimental condition, treating these analyses as manipulation checks.
First, a one-way ANOVA showed that condition predicted the disgust two-item measure,
F(3, 850) = 37.07, p <.001, η2 = .12. As expected, the most disgust was elicited by the Indiana
Jones clip (M = 4.05, SD = 3.23) followed by the Scream clip (M = 2.44, SD = 2.94) and the
Rabbits video (M = 2.36, SD = 2.81) whereas the Snoopy control clip elicited the least disgust
(M = 1.12, SD = 2.02). Adjusting for multiple comparisons with the Holm-Bonferroni method, we confirmed that the disgust video elicited significantly more disgust than any other condition, ts > 4.20, ps < .001.
Second, participants’ experimental condition predicted the fear two-item measure, F(3,
850) = 38.32, p <.001, η2 = .12. As expected, the most fear was elicited by the Scream fear clip
(M = 3.64, SD = 3.27) followed by the Rabbits clip (M = 3.13, SD = 3.01) and Indiana Jones disgust clip (M = 2.43, SD = 2.84), whereas the Snoopy control clip elicited the least disgust (M
= 0.80, SD = 1.70). The Scream clip elicited significantly more fear than the Indiana Jones and
Snoopy clips, ts > = 4.20, ps < .001, and marginally more than the Rabbits clip, t (446.34) =
1.73, p = .053, .95 CI [-0.06, 1.09], d = 0.16.
Do fear and disgust elicit uncanny feelings, controlling for these emotions? We pre- registered that we would determine if the fear and disgust clips still predict the 16-item measure when controlling for our two-item emotion measures. Our initial plan was to test these relationships with dummy-coded regression variables; these analyses, included in the SOM, show the same overall trends as the results we present below.
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First, we conducted an ANCOVA predicting uncanniness from experimental condition, controlling for the two-item disgust and fear measures. Our hypothesis was that only the uncanny clip would predict uncanniness, controlling for the fear and disgust two-item measures. The main effect of condition was present, F(3, 845) = 37.24, p <.001, η2 = .06. To interpret this pattern, we evaluated the estimated marginal means (Figure 2).
We determined that controlling for the two-item measures of fear and disgust, Rabbits was the only condition that positively predicted uncanniness (estimated marginal mean = 0.21,
SE = 0.05, .95 CI [0.12, 0.30]). Estimated marginal means for the Scream and Indiana Jones clips were smaller than the control clip (Scream: -0.13, SE = 0.05, .95 CI[-0.23, -0.04]; Indiana
Jones: -0.10, SE = 0.05, .95 CI[-0.20, -0.002]; Snoopy: 0.05, SE = 0.05, .95 CI [-0.06, 0.15].
Though the Scream and Indiana Jones clips positively predicted uncanniness in our simple model, this model with covariates suggests that fear and disgust entirely explain this relationship.
Figure 2. Estimated marginal means controlling for the two-item measures of fear and disgust.
Note. The mean of the fear scale = 2.58, disgust scale = 2.55.
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We also evaluated how well each clip predicted fear and disgust, controlling for the other two emotions. First, we conducted an ANCOVA predicting fear from experimental condition, controlling for the two-item disgust and uncanny measures. As expected, only the Scream clip positively predicted the fear scale (estimated marginal mean = 0.34, SE = 0.04, .95 CI [0.27,
0.40]). Estimated marginal means for the Rabbits and Indiana Jones clips were smaller than the control clip (Rabbits: -0.13, SE = 0.04, .95 CI[-0.20, -0.06]; Indiana Jones: -0.11, SE = 0.03, .95
CI[-0.19, -0.04]; control: 0.12, SE = 0.04, .95 CI [-0.20, -0.05]. Second, we conducted an
ANCOVA predicting disgust from experimental condition, controlling for the two-item fear and uncanny measures. Also expected, only the Indiana Jones clip positively predicted the fear scale
(estimated marginal mean = 0.57, SE = 0.04, .95 CI [0.49, 0.66]). Estimated marginal means for the Rabbits and Scream clips were smaller than the control clip (Rabbits: -0.32, SE = 0.05, .95
CI[-0.41, -0.23]; Scream: -0.20, SE = 0.04, .95 CI[-0.29, -0.11]; control: -0.04, SE = 0.04, .95 CI
[-0.41, -0.23]. On this basis, we concluded that each stimulus was responsible for eliciting a different emotional experience.
Confirmatory Factor Analysis. A secondary aim of Study 2 was to determine whether the two-factor structure held in the present study (see Table 3) among those in all four conditions. Using the R package lavaan, we used maximum likelihood estimation to analyze the factor structure. Our pre-registered plan was to make a holistic evaluation of the four fit indices:
The chi-square statistic, the RMSEA, SRMR, and the CFI. These are the recommended minimum goodness-of-fit tests to conduct for CFA (Kline, 2005).
The RMSEA was higher than the cut-off of .08 (.095) suggesting that the model does not have acceptable fit to the data, .90 CI [.089, .100]. The CFI was .945, which exceeds .900, but falls short of the more conservative cut-off of .950; the value we pre-registered and were aiming
19 UNCANNY SCALE to exceed. However, the Standardized Root Mean Square Residual (SRMR) was below the cut- off of 0.08 (0.044) suggesting good fit. Chi-square was χ2(103, N = 860) = 891.611, p <.001.
According to this sensitive model fit index, the model is not perfect. The chi-square test is the most sensitive fit statistic; at larger sample sizes, it is unlikely that the null is retained (Bagozzi
& Yi, 1988; Kline, 2005). Thus, we reject exact-fit hypothesis, but do not take this as evidence that the model should be rejected. Model fit was not meaningfully improved when we tested only the 226 participants who watched the eerie clip. We report the full results of this pre-registered analysis in the SOM.
Table 3. Item loadings for the two-factor structure. Factor Loadings Unnerv Disorient Item ed ed I feel creeped out .881 I am uncomfortable .865 I am unsettled .887 I have an eerie sensation .914 I feel freaked out .895 I am uneasy .896 I feel very disturbed .837 I feel weird .890 I have a feeling that I’m not in charge of my actions .852 Right now, I lack control over my thoughts .868 Right now, many of my thoughts are about death .833 I feel like I don’t know anything anymore .828 I feel like I’m stuck in a pattern I can’t get out of .698 I feel like I’m being followed .807 I’m having dark thoughts right now .796 I’m feeling alienated .813
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We were concerned given the RMSEA and CFI that model fit was not acceptable. In follow-up studies, we considered a few possibilities; the first is that our sample was too small, and the second was that our stimulus was shorter than in Study 1 (90 seconds vs. three minutes).
Thus, we conducted a third confirmatory study using the three-minute Rabbits clip from Study 1 and 446 participants. This study, detailed in the SOM, showed good model fit according to the
RMSEA, .071, .90 CI [.06, .08], CFI, .960, and SRMR, 0.045. The Chi Square test, χ2(103, N =
446) = 336.47, p < .001, was also improved, but we still reject the exact-fit hypothesis. Materials and analyses for this study are pre-registered at https://osf.io/wahfe/? view_only=c846327e64de44618ba6497636a91410.
Thus far, we have tested uncanny feelings using eerie stimuli. We were interested to see whether a naturalistic source of eeriness would have similar consequences. In particular, would a global pandemic cause uncanniness in much the same way as eerie objects? We hypothesized that the 2020 coronavirus pandemic could elicit uncanny feelings through two pathways: (1) surreal, world-changing events may violate people’s expectations, and (2) a drastic change in routine could disrupt people’s understanding of their roles and identities.
Study 3
We tested whether the 2020 coronavirus pandemic elicited uncanny feelings, as well as providing another confirmatory test of our model fit. We reasoned that world-changing events are a source of uncanny feelings, and further, people’s experience of the pandemic would interact with how they perceive other uncanny stimuli.
Uncanniness in world events
If uncontrollable or unexpected events can elicit unease, and if the once-familiar unfamiliar is traditionally a source of uncanny feelings, can threatening world events create
21 UNCANNY SCALE uncanny feelings? The 2020 coronavirus pandemic caused many profound and irrevocable changes in people’s lives. The virus affected every aspect of life; economic and political (Long
& Van Dam, 2020; Cassidy, 2020), and individual, as people struggled to regain a sense of order and routine (Simon, 2020). Most Americans felt greater proximity to existential threats than ever before as the death toll in America exceeded 150,000 by August (WHO, 2020). Moreover, people described the crisis as surreal and strange (Simon, 2020; Chuck, 2020), the empty streets as having an eerie atmosphere (Coleman & Brian, 2020; McKenzie, 2020; Elliott, 2020).
The 2020 pandemic seems to fit Freud’s definition of the uncanny. People were still ensconced in their familiar worlds, yet nothing was quite as it was before: ordinary trips to the grocery store were life-threatening; people immediately lost their sense of financial security; ordinary activities such as gatherings with friends have disappeared, replaced with new hobbies of baking and amassing toilet paper; one wonders whether they’ll ever see their elderly relatives again; meanwhile, the president of the United States discussed injecting bleach as a cure. Indeed, people were comfortable describing their pandemic experiences as surreal; the lack of strong leadership and disruption in routine was described as Kafkaesque (Simon, 2020). In our lab, we determined that Google searches on the terms “surreal” and “eerie” corresponded with searches on “pandemic”, “COVID-19”, and “coronavirus”. The time series data was highly correlated, r =
.760. The full results of this analysis are in the SOM.
We hypothesized people felt more uncanniness during the pandemic. To test our prediction, we administered our scale to novel American Mturk participants; half viewed the same neutral clip used throughout, and half viewed the highly life-like humanoid subjects from
Study 1.
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We hypothesized that participants assigned to the control condition would feel more uncanny than those who were exposed to the same neutral stimulus during Study 1. For the experimental condition, we had two competing hypotheses: (1) the effects of the surrealness of the pandemic and viewing humanoid androids would compound, and participants would experience greater uncanniness in the experimental condition compared to Study 1; or (2) the effects would not compound, and uncanniness would be similar to Study 1.
Methods
We collected the data on April 10, 2020, near the first peak of daily confirmed cases of coronavirus in the US: 1,925 deaths were reported on this particular day (World Health
Organization, 2020). Cumulatively, American cases had exceeded 500,000, with 22,500 deaths
(John Hopkins, 2020). All US states had closures and lock-down procedures at various levels of severity. America experienced an unprecedented spike in depression, stress, and anxiety (Wan,
2020). Unemployment was extreme, and relief was uncertain (Cohen & Hsu, 2020). The effects and long-term consequences of COVID-19 remained mysterious, and the virus was spreading rapidly. In contrast, Study 1 was conducted on November 26, 2018, well before the pandemic.
Participants. Aiming for an item-subject ratio of at least 1:10, we recruited 519 participants from Mturk. As in our previous studies, we excluded participants who failed both attention checks or reported that they did not watch the clip completely. We excluded 48 participants, leaving 471 participants.
Procedure. Participants were randomly assigned to see either the neutral video or the video of humanoid robots from Study 1. They then completed the 16-item measure of uncanniness and measures of fear and disgust, state anxiety, neuroticism, BIS, and PNS,
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replicating the design from Study 22. Participants also completed a novel measure of COVID-19
preoccupation, consisting of 10 items evaluating either thoughts and emotions of the pandemic
(e.g., “The COVID-19 scare has caused me to feel lonely”; 1=strongly disagree, 7=strongly
agree; see the SOM for the full scale). We included exploratory measures associated with other
projects, all available on the OSF at https://osf.io/gckas/?
view_only=b1cb7332dce3411abb2c3d80ecedc8a7.
Results and Discussion
As in Study 2, we detected a strong positive correlation between state anxiety and
uncanny feelings (r = .644). We also detected a strong relationship between uncanniness and fear
(r = .762) and uncanniness and disgust (r = .783). As predicted, COVID preoccupation and
uncanniness had a moderate-to-large correlation (r = .479) serving as evidence that world-
disrupting events produce uncanny feelings. Pandemic preoccupation was similarly related to
unnerved feelings (r = .470) as it was disorientation (r = .443). COVID preoccupation and state
anxiety also had a moderate-to-large correlation (r = .495), as well as fear (r = .468) and disgust
(r = .371). Therefore, that the pandemic likely caused fear and disgust, and uncanniness.
We found a moderate relationship between neuroticism and uncanny feelings (r = .344)
and between BIS and uncanny feelings (r = .371; see Table 5 for the full correlation matrix3).
The relationship between PNS and uncanny feelings was null (r = -.020), replicating Study 2.
Table 5. Means and correlations between items.
Mean 1 2 3 4 5 6 7 8 9 (SD) 1 Pandemic Preoccupation (α = .88) 4.46 -
2 Though studies 1-2 did not show strong relationships between PNS and uncanniness, we included PNS given the theoretical relation between these constructs. 3 Note that in study 3, there is good evidence that the experimental and control conditions both elicited uncanny feelings. Therefore, we report correlations for the entire subject pool, rather than the experimental condition. 24 UNCANNY SCALE
(1.30) 2.73 2 Uncanny Scale (α = 0.98) .479*** - (1.72) 2.88 3 Subscale 1 (α= 0.97) .470*** .958*** - (1.84) 2.59 4 Subscale 2 (α = 0.96) .443*** .952*** .824*** - (1.74) 3.39 5 Neuroticism .314*** .344*** .325*** .333*** - 0.679*** (1.40) 4.26 6 Personal Need for Structure (α = 0.83) .151** -.020 .018 -.059 .192*** - 0.059 (0.91) 3.84 7 Behavioral Inhibition (α = 0.81) .371*** .092 .145** .026 .441*** .513*** - 0.082* (1.10) 2.46 8 State Anxiety (α = 0.94) .495*** .644*** .652*** .575*** .465*** .028 .267*** - (0.83) 2.80 9 Fear .468*** .762*** .751*** .702*** .318*** .030 .088 .635*** - (3.09) 2.39 10 Disgust .371*** .783*** .751*** .745*** .253*** -.023 .009 .541*** .762*** (3.05)
Note. Means and correlations were calculated using both conditions.
Comparing the effects of the pandemic to past studies. Our first hypothesis
(Hypothesis 1) is that participants who watched the control video during the pandemic would
have higher uncanniness than those who watched it before the pandemic. For Robots, we had
two competing hypotheses: those who watched the clip during the pandemic would experience
more uncanniness, or similar uncanniness to those who watched it before the pandemic.
We evaluated these hypotheses by comparing results to past studies; specifically, Study
1’s control and Robots conditions. This yielded a sample size of N = 1355 (including Study 1
and post-pandemic responses). We tested our hypotheses using ANOVA.
We compared participants first within the control condition, and then within the
experimental condition. Supporting Hypothesis 1, in the control condition, mean uncanniness in
Study 3, the present study (M = 2.56, SD = 1.77) was greater than in Study 1 (M = 1.98, SD =
25 UNCANNY SCALE
1.10), t(393.92) = 4.31, p < .001, .95 CI [0.21, 0.57]4, d = 0.40. In contrast, in the experimental condition, uncanniness was not greater in Study 3 (M = 2.90, SD = 1.65) than in Study 1 (M =
2.67, SD = 1.20), t(378.11) = 1.41, p = .160, .95 CI [-0.04, 0.08], d = 0.12. This suggests participants who watched an uncanny video during the pandemic experienced more uncanniness than in Study 1 (see Figure 3).
4 Confidence intervals associated with t-tests indicate estimates for the mean differences. 26 UNCANNY SCALE
Figure 3. Comparing experimental conditions in Studies 1 and 3.
Confirmatory Factor Analysis. We evaluated the two-factor structure (see the full analyses and factor loadings in the SOM). Because we suspected both groups would be experiencing uncanny feelings, we included both groups in our analyses of model fit. As in
Studies 1-2, we used maximum likelihood estimation.
The RMSEA suggested acceptable fit, .070, .90 CI (.061, .078) as did the CFI (.974) and
SRMR (0.019). Chi square was χ2(103, N = 471) = 336.576, p < .001. The only index that showed less than perfect fit was the chi square, but this measure is overly sensitive and not indicative of how useful the two-factor model is.
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General Discussion
These studies defined and tested uncanniness; a concept that eluded early psychoanalysts and continues to confound artists and engineers to this day. Across three studies, we developed a scale measuring uncanny feelings, determined whether it can differentiate between uncanniness and related affective experiences (fear, disgust), and evaluated its capacity to probe disorienting and surreal circumstances in people’s lives during the 2020 coronavirus pandemic.
This program of research makes two theoretical contributions. First, we developed and tested the first measure of uncanny feelings. Further, we distinguished this experience from fear and disgust. Surrealist artists and filmmakers create unease using tools that go beyond these emotions, yet it is unclear what these tools are. We argue that objects that violate people’s schemas elicit uncanniness; a feeling of being unnerved and disoriented; distinguishable from other affective experiences. We hope that many researchers find novel uses for this measure.
Second, we contribute to the discussion about the definition and breadth of uncanny experiences. Uncanny objects may be the product of perceiving human-like objects (Mori, 1970), or being reminded of death (MacDorman and Ishiguro, 2006) or low-level cognitive processes, like perceptual mismatch (Katsyri et al., 2015) or prediction errors (Saygin et al., 2012). Our definition fits with each of these processes: Uncanniness happens when objects or events violate people’s expectations. This broad conception enables researchers to approach uncanny valley robots and animations, and life through a pandemic, as examples of the many experiences that elicit uncanniness.
Though we find evidence that different ‘eerie’ objects elicit uncanniness, the manipulations were still somewhat weak. Participants responded below the scale midpoint in all three studies. It is possible a stronger manipulation would reveal something new about
28 UNCANNY SCALE uncanniness. For example, coming face-to-face with a lifelike robot might elicit a new brand of strangeness, not captured by our measure. Further, Study 2 suggests the uncanny scale performs best when the manipulation is stronger; even shortening the video by one minute affected its performance. How this scale performs with stronger stimuli remains an open question.
We suspect participants were consciously aware of the strangeness of our manipulations and attributed their feelings to those situations accordingly. Though anomalies can affect behaviour even outside of conscious awareness (Proulx & Heine, 2008; Randles et al., 2011;
2018) the question remains: How salient must a surreal experience be before participants report uncanny feelings?
Another question is whether some specific quality of uncanny objects drives these effects more than others. Though we define uncanniness generally as unnerved-disoriented feelings, the greatest cause of these feelings is still undetermined. For example, a wax figure’s zombie-like qualities could be more disturbing than their physical abnormalities. Further, perhaps individual differences moderate what people find disturbing, and when they begin to embrace the strange.
Surrealist artists sought to liberate their audiences from the “incurable mania for reducing the unknown to the known, to the classifiable.” (Breton, 1924, p. 7). Breton suggests that eeriness is to be embraced. But is the mania of reducing the unknown truly incurable, and for whom is it most pronounced? We found no relation between uncanniness and the need for structure, but neuroticism and BIS might be important moderators of uncanny feelings. Culture, and beliefs about human uniqueness might affect what people find most disturbing.
From early psychoanalytic accounts of the familiar-unfamiliar to recent brushes with disturbing humanoids (Mori, 1970; Tinwell et al., 2011), the uncanny has been a topic of interest for over 100 years. Now we are beginning to understand what it is.
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