In the uncanny valley, transportation predicts narrative enjoyment more than empathy, but only for the tragic hero

The uncanny valley is a term used to describe the phenomenon that human simulations that are nearly but not quite realistic often give viewers an uneasy, eerie feeling. Given the prevalence of computer-animated human characters and a narrative framework in videogames, serious games, and health-related scenarios, it is important to examine how the uncanny valley influences narrative empathy and enjoyment. In a 2 × 2 × 2 between-groups posttest-only experiment, 738 participants took the role of a patient in a virtual consultation with a doctor; the consultation varied in the doctor's character (hero or villain), its subplot ending (happy or tragic), and its depiction (computer animated or real). The participants' posttest results showed greater emotional empathy and enjoyment in the hero condition and no significant difference in emotional empathy for the computer animation but greater narrative enjoyment and persuasion. Just endings (hero rewarded, villain punished) elicited much greater pleasure than unjust endings. In comparing computer animation with recorded video, emotional empathy was a significantly stronger predictor of narrative enjoyment than transportation only for the real hero with a tragic ending. The enjoyment and persuasiveness of the computer-animated doctor–patient consultation bodes well for the use of animation in interactive visual narratives

Protosymbols that integrate recognition and response

We explore two controversial hypotheses through robotic implementation: (1) Processes involved in recognition and response are tightly coupled both in their operation and epigenesis; and (2) processes involved in symbol emergence should respect the integrity of recognition and response while exploiting the periodicity of biological motion. To that end, this paper proposes a method of recognizing and generating motion patterns based on nonlinear principal component neural networks that are constrained to model both periodic and transitional movements. The method is evaluated by an examination of its ability to segment and generalize different kinds of soccer playing activity during a RoboCup match

The Influence of Holistic and Analytic Cognitive Styles on Online Information Design: Toward a communication theory of cultural cognitive design

Although studies have linked culture to online user preferences and performance, few communication researchers have recognized the impact of culture on online information design and usability. It is important to ask if people are better able to use and prefer Web sites created by designers from their own culture. We propose that to improve computer-mediated communication, Web site design should accommodate culturally diverse user groups. First, a body of research is presented that aligns East Asian cultures with more holistic cognitive styles and Western cultures with more analytical cognitive styles. Building on this contrast, a theory of cultural cognitive design is proposed as a means of understanding how cognitive styles that develop under the influence of culture lead to different ways of designing and organizing information for the Web

Reducing consistency in human realism increases the uncanny valley effect; increasing category uncertainty does not

Human replicas may elicit unintended cold, eerie feelings in viewers, an effect known as the uncanny valley. Masahiro Mori, who proposed the effect in 1970, attributed it to inconsistencies in the replica’s realism with some of its features perceived as human and others as nonhuman. This study aims to determine whether reducing realism consistency in visual features increases the uncanny valley effect. In three rounds of experiments, 548 participants categorized and rated humans, animals, and objects that varied from computer animated to real. Two sets of features were manipulated to reduce realism consistency. (For humans, the sets were eyes–eyelashes–mouth and skin–nose–eyebrows.) Reducing realism consistency caused humans and animals, but not objects, to appear eerier and colder. However, the predictions of a competing theory, proposed by Ernst Jentsch in 1906, were not supported: The most ambiguous representations—those eliciting the greatest category uncertainty—were neither the eeriest nor the coldest

Familiar faces rendered strange: Why inconsistent realism drives characters into the uncanny valley

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

Sending an Avatar to Do a Human’s Job: Compliance with Authority Persists Despite the Uncanny Valley

Just as physical appearance affects social influence in human communication, it may also affect the processing of advice conveyed through avatars, computer-animated characters, and other human-like interfaces. Although the most persuasive computer interfaces are often the most human-like, they have been predicted to incur the greatest risk of falling into the uncanny valley, the loss of empathy attributed to characters that appear eerily human. Previous studies compared interfaces on the left side of the uncanny valley, namely, those with low human likeness. To examine interfaces with higher human realism, a between-groups factorial experiment was conducted through the internet with 426 midwestern U.S. undergraduates. This experiment presented a hypothetical ethical dilemma followed by the advice of an authority figure. The authority was manipulated in three ways: depiction (digitally recorded or computer animated), motion quality (smooth or jerky), and advice (disclose or refrain from disclosing sensitive information). Of these, only the advice changed opinion about the ethical dilemma, even though the animated depiction was significantly eerier than the human depiction. These results indicate that compliance with an authority persists even when using an uncannily realistic computer-animated double

Categorization-based stranger avoidance does not explain the uncanny valley effect

The uncanny valley hypothesis predicts that an entity appearing almost human risks eliciting cold, eerie feelings in viewers. Categorization-based stranger avoidance theory identifies the cause of this feeling as categorizing the entity into a novel category. This explanation is doubtful because stranger is not a novel category in adults; infants do not avoid strangers while the category stranger remains novel; infants old enough to fear strangers prefer photographs of strangers to those more closely resembling a familiar person; and the uncanny valley’s characteristic eeriness is seldom felt when meeting strangers. We repeated our original experiment with a more realistic 3D computer model and found no support for categorization-based stranger avoidance theory. By contrast, realism inconsistency theory explains cold, eerie feelings elicited by transitions between instances of two different, mutually exclusive categories, given that at least one category is anthropomorphic: Cold, eerie feelings are caused by prediction error from perceiving some features as features of the first category and other features as features of the second category. In principle, realism inconsistency theory can explain not only negative evaluations of transitions between real and computer modeled humans but also between different vertebrate species

Measuring the Uncanny Valley Effect

Using a hypothetical graph, Masahiro Mori proposed in 1970 the relation between the human likeness of robots and other anthropomorphic characters and an observer’s affective or emotional appraisal of them. The relation is positive apart from a U-shaped region known as the uncanny valley. To measure the relation, we previously developed and validated indices for the perceptual-cognitive dimension humanness and three affective dimensions: interpersonal warmth, attractiveness, and eeriness. Nevertheless, the design of these indices was not informed by how the untrained observer perceives anthropomorphic characters categorically. As a result, scatter plots of humanness vs. eeriness show the stimuli cluster tightly into categories widely separated from each other. The present study applies a card sorting task, laddering interview, and adjective evaluation ( N=30 ) to revise the humanness, attractiveness, and eeriness indices and validate them via a representative survey ( N=1311 ). The revised eeriness index maintains its orthogonality to humanness ( r=.04 , p=.285 ), but the stimuli show much greater spread, reflecting the breadth of their range in human likeness and eeriness. The revised indices enable empirical relations among characters to be plotted similarly to Mori’s graph of the uncanny valley. Accurate measurement with these indices can be used to enhance the design of androids and 3D computer animated characters

Uncanny valley and motor empathy

poster abstractThe uncanny valley phenomenon (Mori, 1970/2012) is the tendency to perceive as eerie human-looking characters with nonhuman features. It has been repeatedly claimed that falling into the uncanny valley can lead to a loss of empathy for a character (Hodgins, Jörg, O’Sullivan, Park, & Mahler, 2010). Empathy is the tendency to orient one’s responses to the situation of another instead of one’s own (de Vignemont & Singer, 2006). Empathy has been shown to be a combination of dissociable neurocognitive processes broadly grouped as cognitive, emotional, and motor empathy (Blair, 2005). It takes on such forms as perspective taking, sympathy, nonconscious mimicry, and the synchronizing of facial expressions, postures, and movements. To determine whether the uncanny valley suppresses motor empathy, operationalized as movement synchronization, a pilot study was undertaken by 25 participants. The study required participants to perform an action while viewing videos of a human character or its silhouette performing the same action. The frequency of actions performed by participants fell within their individual frequency and that of the character regardless of whether the participants were asked to coordinate or not coordinate their movement with the character. No significant difference in performance was noticed between the human character and its silhouette for all the conditions. Participants were observed to adjust their individual frequency in a similar manner for both the human character and its silhouette. Future studies with systematic variation in the human realism of the character’s features (e.g., skin texture or eye size) and its type of movement (biological vs. mechanical) can help ascertain the extent to which the uncanny valley phenomenon suppresses motor empathy

Facilitators and Barriers to Adopting Robotic-Assisted Surgery: Contextualizing the Unified Theory of Acceptance and Use of Technology

Robotic-assisted surgical techniques are not yet well established among surgeon practice groups beyond a few surgical subspecialties. To help identify the facilitators and barriers to their adoption, this belief-elicitation study contextualized and supplemented constructs of the unified theory of acceptance and use of technology (UTAUT) in robotic-assisted surgery. Semi-structured individual interviews were conducted with 21 surgeons comprising two groups: users and nonusers. The main facilitators to adoption were Perceived Usefulness and Facilitating Conditions among both users and nonusers, followed by Attitude Toward Using Technology among users and Extrinsic Motivation among nonusers. The three main barriers to adoption for both users and nonusers were Perceived Ease of Use and Complexity, Perceived Usefulness, and Perceived Behavioral Control. This study's findings can assist surgeons, hospital and medical school administrators, and other policy makers on the proper adoption of robotic-assisted surgery and can guide future research on the development of theories and framing of hypotheses