Browsing by Subject "Anthropomorphism"

Now showing 1 - 7 of 7
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    Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories
    (Association for Research in Vision and Ophthalmology, 2021-04) Diel, Alexander; MacDorman, Karl F.; Human-Centered Computing, School of Informatics and Computing
    In 1970, Masahiro Mori proposed the uncanny valley (UV), a region in a human-likeness continuum where an entity risks eliciting a cold, eerie, repellent feeling. Recent studies have shown that this feeling can be elicited by entities modeled not only on humans but also nonhuman animals. The perceptual and cognitive mechanisms underlying the UV effect are not well understood, although many theories have been proposed to explain them. To test the predictions of nine classes of theories, a within-subjects experiment was conducted with 136 participants. The theories’ predictions were compared with ratings of 10 classes of stimuli on eeriness and coldness indices. One type of theory, configural processing, predicted eight out of nine significant effects. Atypicality, in its extended form, in which the uncanny valley effect is amplified by the stimulus appearing more human, also predicted eight. Threat avoidance predicted seven; atypicality, perceptual mismatch, and mismatch+ predicted six; category+, novelty avoidance, mate selection, and psychopathy avoidance predicted five; and category uncertainty predicted three. Empathy's main prediction was not supported. Given that the number of significant effects predicted depends partly on our choice of hypotheses, a detailed consideration of each result is advised. We do, however, note the methodological value of examining many competing theories in the same experiment.
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    Does mind perception explain the uncanny valley effect? A meta-regression analysis and (de)humanization experiment.
    (Elsevier, 2024) MacDorman, Karl F.
    Gray and Wegner (2012) proposed that when robots look human, their appearance prompts attributions of experience, including sensations and feelings, which is uncanny. This theory, confusingly termed mind perception, differs from perceptual theories of the uncanny valley in that the robots' eeriness is not stimulus-driven. To explore this seminal theory, we conducted a meta-regression analysis of 10 experiments and a (de)humanization experiment. In the first part, experiments were identified in the literature that manipulated artificial entity's experience using descriptions. However, experiments with no observable stimuli yielded larger effects for experience and eeriness than those with robots and virtual reality characters. This finding undermines a theory that purports to explain how a robot's human likeness causes eeriness. Further, a second issue concerns Gray and Wegner's protocol based on a vignette design. Reading about an entity with experience activates thoughts that may not be activated when encountering it, and these thoughts may increase its eeriness. Therefore, the paper's second part focuses on an experiment we conducted with a novel humanization–dehumanization protocol. Participants' attitudes on robots' similarity to humans were gradually shifted to manipulate robots' perceived humanness, experience, and agency. However, the manipulation's effect on eeriness and coldness was mostly nonsignificant or counter to prediction. Differences in the robots' physical appearance had a much larger effect on their eeriness and coldness. In fact, as a mediator, experience mitigated the stimulus's overall effect of increasing eeriness. These results favor perceptual theories, rather than mind perception, in explaining the uncanny valley.
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    Familiar faces rendered strange: Why inconsistent realism drives characters into the uncanny valley
    (ARVO, 2016-09-01) Chattopadhyay, Debaleena; MacDorman, Karl F.; Department of Human Centered Computing, School of Informatics and Computing
    Computer-modeled characters resembling real people sometimes elicit cold, eerie feelings. This effect, called the uncanny valley, has been attributed to uncertainty about whether the character is human or living or real. Uncertainty, however, neither explains why anthropomorphic characters lie in the uncanny valley nor their characteristic eeriness. We propose that realism inconsistency causes anthropomorphic characters to appear unfamiliar, despite their physical similarity to real people, owing to perceptual narrowing. We further propose that their unfamiliar, fake appearance elicits cold, eerie feelings, motivating threat avoidance. In our experiment, 365 participants categorized and rated objects, animals, and humans whose realism was manipulated along consistency-reduced and control transitions. These data were used to quantify a Bayesian model of categorical perception. In hypothesis testing, we found reducing realism consistency did not make objects appear less familiar, but only animals and humans, thereby eliciting cold, eerie feelings. Next, structural equation models elucidated the relation among realism inconsistency (measured objectively in a two-dimensional Morlet wavelet domain inspired by the primary visual cortex), realism, familiarity, eeriness, and warmth. The fact that reducing realism consistency only elicited cold, eerie feelings toward anthropomorphic characters, and only when it lessened familiarity, indicates the role of perceptual narrowing in the uncanny valley.
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    Human emotions toward stimuli in the uncanny valley: laddering and index construction
    (2015) Ho, Chin-Chang; MacDorman, Karl F.; Pfaff, Mark S.; Fedorikhin, Alexander; Huang, Edgar
    Human-looking computer interfaces, including humanoid robots and animated humans, may elicit in their users eerie feelings. This effect, often called the uncanny valley, emphasizes our heightened ability to distinguish between the human and merely humanlike using both perceptual and cognitive approaches. Although reactions to uncanny characters are captured more accurately with emotional descriptors (e.g., eerie and creepy) than with cognitive descriptors (e.g., strange), and although previous studies suggest the psychological processes underlying the uncanny valley are more perceptual and emotional than cognitive, the deep roots of the concept of humanness imply the application of category boundaries and cognitive dissonance in distinguishing among robots, androids, and humans. First, laddering interviews (N = 30) revealed firm boundaries among participants’ concepts of animated, robotic, and human. Participants associated human traits like soul, imperfect, or intended exclusively with humans, and they simultaneously devalued the autonomous accomplishments of robots (e.g., simple task, limited ability, or controlled). Jerky movement and humanlike appearance were associated with robots, even though the presented robotic stimuli were humanlike. The facial expressions perceived in robots as improper were perceived in animated characters as mismatched. Second, association model testing indicated that the independent evaluation based on the developed indices is a viable quantitative technique for the laddering interview. Third, from the interviews several candidate items for the eeriness index were validated in a large representative survey (N = 1,311). The improved eeriness index is nearly orthogonal to perceived humanness (r = .04). The improved indices facilitate plotting relations among rated characters of varying human likeness, enhancing perspectives on humanlike robot design and animation creation.
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    Investigating the Effect of a Digital Doctor on Persuasion
    (2021-10) Dai, Zhengyan; MacDormann, Karl F.; Miller, Andrew; Brady, Erin; Chakraborty, Sunandan
    The treatment of chronic diseases requires patient adherence to medical advice. Nonadherence worsens health outcomes and increases healthcare costs. Consultations with a virtual physician could increase adherence, given the shortage of healthcare professionals. However, if the virtual physician is a computer animation, acceptance of its advice may be hampered by the uncanny valley effect, a negative affective reaction to human simulations. Two experiments were conducted to investigate the impact of the virtual physician on patients’ adherence. The first study, a 2 ´ 2 ´ 2 between-groups posttestonly experiment, involved 738 participants playing the role of a patient in a hypothetical virtual consultation with a doctor. The consultation varied in the doctor’s Character, Outcome, and Depiction. Character, Outcome, and Depiction were designed to manipulate the doctor’s level of warmth, competence, and realism. The second study, a 2 ´ 5 between-groups experiment, involved 441 participants assuming a patient’s role in a similar hypothetical virtual consultation with a doctor. The experiment varied the doctor’s Character and Depiction. These independent variables were designed to manipulate the doctor’s level of warmth and eeriness. The first study found that warmth and competence increased adherence intention and consultation enjoyment, but realism did not. On the contrary, the computer-animated doctor increased adherence intention and consultation enjoyment significantly more than the doctor portrayed by a human actor. The enjoyment of the animated consultation caused the doctor to appear warmer and more real, compensating for his realism inconsistency. In the second study, Depiction had a nonsignificant effect on adherence intention, even though the computer animated doctor was perceived as eerier than the real human. The low-warmth, high-eeriness doctor prompted heuristic processing of information, while the high-warmth doctor prompted systematic processing. This pattern runs counter to the literature on persuasion. The doctor’s eeriness, measured in a pretest, had no significant effect on adherence intention via the heuristic-systematic model. Although virtual characters can elicit the uncanny valley effect, they were comparable to a real person in increasing adherence intention, adherence and health behavior. This finding should encourage the development and acceptance of virtual consultation to address the shortage of healthcare professionals.
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    A Meta-analysis of the Uncanny Valley's Independent and Dependent Variables
    (ACM, 2022-03) Diel, Alexander; Weigelt, Sarah; MacDorman, Karl F.; Human-Centered Computing, School of Informatics and Computing
    The uncanny valley (UV) effect is a negative affective reaction to human-looking artificial entities. It hinders comfortable, trust-based interactions with android robots and virtual characters. Despite extensive research, a consensus has not formed on its theoretical basis or methodologies. We conducted a meta-analysis to assess operationalizations of human likeness (independent variable) and the UV effect (dependent variable). Of 468 studies, 72 met the inclusion criteria. These studies employed 10 different stimulus creation techniques, 39 affect measures, and 14 indirect measures. Based on 247 effect sizes, a three-level meta-analysis model revealed the UV effect had a large effect size, Hedges’ g = 1.01 [0.80, 1.22]. A mixed-effects meta-regression model with creation technique as the moderator variable revealed face distortion produced the largest effect size, g = 1.46 [0.69, 2.24], followed by distinct entities, g = 1.20 [1.02, 1.38], realism render, g = 0.99 [0.62, 1.36], and morphing, g = 0.94 [0.64, 1.24]. Affective indices producing the largest effects were threatening, likable, aesthetics, familiarity, and eeriness, and indirect measures were dislike frequency, categorization reaction time, like frequency, avoidance, and viewing duration. This meta-analysis—the first on the UV effect—provides a methodological foundation and design principles for future research.
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    Too real for comfort? Uncanny responses to computer generated faces
    (ScienceDirect, 2014-12-12) MacDorman, Karl F.; Green, Robert D.; Ho, Chin-Chang; Koch, Clinton T.; Department of Human-Centered Computing, IU School of Informatics and Computing
    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.