Uncanniliy Human - Experimental Investigation of the Uncanny Valley Phenomenon

Seit seiner Einführung in den wissenschaftlichen Diskurs im Jahr 1970 (Mori, 1970; Mori et al., 2012) ist das Uncanny Valley eine der meist diskutierten und referenzierten Theorien in der Robotik. Obwohl die Theorie vor mehr als 40 Jahren postuliert wurde, wurde sie kaum empirisch untersucht. Erst in den letzten sieben Jahren haben Wissenschaftler aus dem Bereich Robotik, aber auch aus anderen Disziplinen, angefangen, das Uncanny Valley systematischer zu erforschen. Allerdings blieben bisher viele Fragen offen. Einiger dieser Fragen wurden in dem vorliegenden Forschungsprojekt im Rahmen von vier aufeinander aufbauenden Studien untersucht. Der Schwerpunkt der Arbeit liegt auf der systematischen Untersuchung des Einflusses von statischen und dynamischen Merkmalen von Robotern, wie etwa dem Design bzw. Erscheinungsbild und der Bewegung, auf die Wahrnehmung und Evaluation von diesen Robotern. Eine Besonderheit der vorliegenden Arbeit ist der multi-methodologische Ansatz, bei dem die durch verschiedenste Methoden und Messinstrumente beobachteten Effekte auf ihre Relevanz für die Uncanny Valley Theorie hin untersucht wurden. Zudem wurden die in der bisherigen Literatur postulierten Erklärungsansätze für den Uncanny Valley Effekt empirisch getestet. In der ersten Studie wurde anhand von qualitativen Interviews, in denen Probanden Bilder und Videos von humanoiden und androiden Robotern gezeigt wurden, untersucht, wie Probanden sehr menschenähnliche Roboter evaluieren, ob sie emotionale Reaktionen zeigen, und wie ihre Einstellungen gegenüber diesen Robotern sind. Die Ergebnisse zeigen, dass emotionale Reaktion, wenn überhaupt vorhanden, individuell sehr verschieden ausfallen. Das Erscheinungsbild der Roboter war sehr wichtig, denn bestimmte Designmerkmale wurden mit bestimmten Fähigkeiten gleichgesetzt. Ein menschliches Erscheinungsbild ohne Funktionalität wurde eher negativ bewertet. Zudem schienen die Probanden bei androiden Robotern dieselben Maßstäbe zur Bewertung von Attraktivität anzulegen wie sie dies bei Menschen tun. Die Analyse zeigte auch die Relevanz der Bewegungen der Roboter und des Kontextes, in welchem der jeweilige Roboter präsentiert wurde. Es wurde erste Evidenz gefunden für die Annahme, dass Menschen Unsicherheit verspüren bei der Kategorisierung von androiden Robotern als entweder Roboter oder Mensch. Zudem fühlten sich die Probanden unwohl bei dem Gedanken, dass Roboter sie ersetzten könnten. Die zweite Studie untersuchte den Einfluss von robotischer Bewegung. In einem quasi-experimentellen Feldexperiment wurden Passanten mit dem androiden Roboter Geminoid HI-1 konfrontiert, der sich entweder still verhielt oder Bewegungsverhalten zeigte. Die Interaktionen wurden analysiert hinsichtlich des nonverbalen Verhaltens der Passanten (z.B. auf den Roboter gerichtete Aufmerksamkeit, interpersonale Distanz zum Roboter). Die Resultate zeigen, dass das Verhalten der Passanten von dem Verhalten des Roboters beeinflusst wurde, zum Beispiel waren die Interaktionen länger, die Probanden stellten mehr Blickkontakt her und testeten die Fähigkeiten des Roboters wenn dieser Bewegungsverhalten zeigte. Zudem diente das Verhalten des Roboters als Hinweisreiz für die richtige Kategorisierung des Roboters als solchen. Der Aspekt des Erscheinungsbildes wurde in der dritten Studie systematisch untersucht. Zu diesem Zweck wurden in einem webbasierten Fragebogen 40 standardisierte Bilder von Robotern evaluiert, um die Evaluation beeinflussende Designmerkmale zu identifizieren. Eine Clusteranalyse ergab sechs Cluster von Robotern, die auf sechs Dimensionen unterschiedlich bewertet wurden. Mögliche Beziehungen zwischen Designmerkmalen und Evaluationen der Cluster wurden aufgezeigt und diskutiert. Zudem wurde die Aussagekraft des Uncanny Valley Graphen untersucht. Ausgehend von Mori’s Überlegungen ist der Uncanny Valley Effekt eine kubische Funktion. Demnach müssten sich die Daten am besten durch eine kubische Funktion erklären lassen. Die Ergebnisse zeigten allerdings eine bessere Modellpassung für lineare oder quadratische Zusammenhänge. In der letzten Studie wurden perzeptions-orientiert und evolutionsbiologische Erklärungsansätze für das Uncanny Valley systematisch getestet. In dieser Studie wurden Daten aus Selbstauskunft, Verhaltensdaten und funktionelle Bildgebung kombiniert, um zu untersuchen ob sich die Effekte auf Basis der Selbstauskunft und der Verhaltensdaten erklären lassen durch a) zusätzliche Verarbeitungsleistung während der Perzeption von Gesichtern, b) automatisch ablaufende Prozesse sozialer Kognition, oder c) eine Überempfindlichkeit des sogenannten Verhaltensimmunsystems (behavioral immune system). Die Ergebnisse unterstützen die perzeptions-orientierten Erklärungen für den Uncanny Valley Effekt. Zum einen scheinen die Verhaltenseffekte durch neuronale Prozesse während der Wahrnehmung von Gesichtern begründet zu sein. Zum anderen gibt es Befunde, die auf eine kategoriale Wahrnehmung von Robotern und Menschen hinweisen. Evolutionsbiologische Erklärungen konnten durch die vorliegenden Daten nicht gestützt werden.Since its introduction into scientific discourse in 1970 (Mori, 1970; Mori et al., 2012) the uncanny valley has been a highly discussed and referenced theory in the field of robotics. Although the theory was postulated more than 40 years ago, it has barely been tested empirically. However, in the last seven years robot scientists addressed themselves to the task of investigating the uncanny valley more systematically. But there are still open questions, some of which have been addressed within this research in the course of four consecutive studies. This project focussed on the systematic investigation of how static and dynamic characteristics of robots such as appearance and movement determine evaluations of and behavior towards robots. The work applied a multi-methodological approach and the various observed effects were examined with regard to their importance for the assumed uncanny valley. In addition, previously proposed explanations for the uncanny valley effect were tested. The first study utilized qualitative interviews in which participants were presented with pictures and videos of humanoid and android robots to explore participants’ evaluations of very human-like robots, their attitudes about these robots, and their emotional reactions towards these robots. Results showed that emotional experiences, if existent, were very individual. The robots’ appearance was of great importance for the participants, because certain characteristics were equalized with certain abilities, merely human appearance without a connected functionality was not appreciated, and human rules of attractiveness were applied to the android robots. The analysis also demonstrated the importance of the robots’ movements and the social context they were placed in. First evidence was found supporting the assumption that participants experienced uncertainty how to categorize android robots (as human or machine) and that they felt uncomfortable at the thought to be replaced by robots. The influence of movement, as one of the important factors in the uncanny valley hypothesis, was examined in the second study. In a quasi-experimental observational field study people were confronted with the android robot Geminoid HI-1 either moving or not moving. These interactions between humans and the android robot were analyzed with regard to the participants’ nonverbal behavior (e.g. attention paid to the robot, proximity). Results show that participants’ behavior towards the android robot was influenced by the behavior the robot displayed. For instance, when the robot established eye-contact participants engaged in longer interactions, also established more eye-contact and tried to test the robots’ capabilities. The robot’s behavior served as cue for the participants to categorize the robot as such. The aspect of robot appearances was examined systematically in the third study in order to identify certain robot attractiveness indices or design characteristics which determine how people perceive robots. A web-based survey was conducted with standardized pictures of 40 different mechanoid, humanoid and android robots. A cluster analysis revealed six clusters of robots which were rated significantly different on six dimensions. Possible relationships of design characteristics and the evaluation of robots have been outlined. Moreover, it has been tested whether the data of this study can best be explained by a cubic funtion as would be suggested by the graph proposed by Mori. Results revealed that the data can be best explained by linear or quadratic relationships. The last study systematically tested perception-oriented and evolutionary-biological approaches for the uncanny valley. In this multi-methodological study, self-report and behavioral data were combined with functional magnetic resonance imaging techniques in order to examine whether the observed effects in self-report and behavior occur due to a) additional processing during face perception of human and robotic stimuli, b) automatically elicited processes of social cognition, or c) oversensitivity of the behavioral immune system. The study found strong support for perception-oriented explanations for the uncanny valley effect. First, effects seem to be driven by face perception processes. Further, there were indicators for the assumption that categorical perception takes place. In the contrary, evolutionary-biological driven explanations assuming that uncanny valley related reactions are due to oversensitivity of the behavioral immune system were not supported by this work. Altogether, this dissertation explored the importance of characteristics of robots which are relevant for the uncanny valley hypothesis. Uncanny valley related responses were examined using a variety of measures, for instance, self-reporting, behavior, and brain activation, allowing conclusions with regard to the influence of the choice of measurements on the detection of uncanny valley related responses. Most importantly, explanations for the uncanny valley were tested systematically and support was found for cognitive-oriented and perception-oriented explanations

Role of Gaze Cues in Interpersonal Motor Coordination: Towards Higher Affiliation in Human-Robot Interaction

Background The ability to follow one another's gaze plays an important role in our social cognition; especially when we synchronously perform tasks together. We investigate how gaze cues can improve performance in a simple coordination task (i.e., the mirror game), whereby two players mirror each other's hand motions. In this game, each player is either a leader or follower. To study the effect of gaze in a systematic manner, the leader's role is played by a robotic avatar. We contrast two conditions, in which the avatar provides or not explicit gaze cues that indicate the next location of its hand. Specifically, we investigated (a) whether participants are able to exploit these gaze cues to improve their coordination, (b) how gaze cues affect action prediction and temporal coordination, and (c) whether introducing active gaze behavior for avatars makes them more realistic and human-like (from the user point of view). Methodology/Principal Findings 43 subjects participated in 8 trials of the mirror game. Each subject performed the game in the two conditions (with and without gaze cues). In this within-subject study, the order of the conditions was randomized across participants, and subjective assessment of the avatar's realism was assessed by administering a post-hoc questionnaire. When gaze cues were provided, a quantitative assessment of synchrony between participants and the avatar revealed a significant improvement in subject reaction-time (RT). This confirms our hypothesis that gaze cues improve the follower's ability to predict the avatar's action. An analysis of the pattern of frequency across the two players' hand movements reveals that the gaze cues improve the overall temporal coordination across the two players. Finally, analysis of the subjective evaluations from the questionnaires reveals that, in the presence of gaze cues, participants found it not only more human-like/realistic, but also easier to interact with the avatar. Conclusion/Significance This work confirms that people can exploit gaze cues to predict another person's movements and to better coordinate their motions with their partners, even when the partner is a computer-animated avatar. Moreover, this study contributes further evidence that implementing biological features, here task-relevant gaze cues, enable the humanoid robotic avatar to appear more human-like, and thus increase the user's sense of affiliation

Assessment of Society\u27s Awareness, Acceptance, and Demand for Robotic Wait Staff in Restaurant Operations

This research study consists of an assessment of participants\u27 awareness of robotics in general and also their acceptance and consumer demand for mobile, humanoid robots in the role of robotic waiters in restaurants. The study also includes the awareness and consumer demand for Microsoft Surface Computers to be potentially used as restaurant tables capable of electronic order entry, payment, and entertainment. The social impacts of such high technology upon the human occupation of waiter or waitress were also examined relative to the resistance to automation from current human wait staff. The overall results of the study were luke-warm demand for robotic waiters, strong demand for Microsoft Surface Computers, and resistance to robotic waiters among most wait staff

Humanization of robots: is it really such a good idea?

The aim of this review was to examine the pros and cons of humanizing social robots following a psychological perspective. As such, we had six goals. First, we defined what social robots are. Second, we clarified the meaning of humanizing social robots. Third, we presented the theoretical backgrounds for promoting humanization. Fourth, we conducted a review of empirical results of the positive effects and the negative effects of humanization on human–robot interaction (HRI). Fifth, we presented some of the political and ethical problems raised by the humanization of social robots. Lastly, we discussed the overall effects of the humanization of robots in HRI and suggested new avenues of research and development.info:eu-repo/semantics/publishedVersio

Human emotions toward stimuli in the uncanny valley: laddering and index construction

Indiana University-Purdue University Indianapolis (IUPUI)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

Digital Manipulation of Human Faces: Effects on Emotional Perception and Brain Activity

The study of human face-processing has granted insight into key adaptions across various social and biological functions. However, there is an overall lack of consistency regarding digital alteration styles of human-face stimuli. In order to investigate this, two independent studies were conducted examining unique effects of image construction and presentation. In the first study, three primary forms of stimuli presentation styles (color, black and white, cutout) were used across iterations of non-thatcherized/thatcherized and non-inverted/inverted presentations. Outcome measures included subjective reactions measured via ratings of perceived “grotesqueness,” and objective outcomes of N170 event-related potentials (ERPs) measured via encephalography. Results of subjective measures indicated that thatcherized images were associated with an increased level of grotesque perception, regardless of overall condition variant and inversion status. A significantly larger N170 component was found in response to cutout-style images of human faces, thatcherized images, and inverted images. Results suggest that cutout image morphology may be considered a well-suited image presentation style when examining ERPs and facial processing of otherwise unaltered human faces. Moreover, less emphasis can be placed on decision making regarding main condition morphology of human face stimuli as it relates to negatively valent reactions. The second study explored commonalities between thatcherized and uncanny images. The purpose of the study was to explore commonalities between these two styles of digital manipulation and establish a link between previously disparate areas of human-face processing research. Subjective reactions to stimuli were measured via participant ratings of “off-putting.” ERP data were gathered in order to explore if any unique effects emerged via N170 and N400 presentations. Two main “morph continuums” of stimuli, provided by Eduard Zell (see Zell et al., 2015), with uncanny features were utilized. A novel approach of thatcherizing images along these continuums was used. thatcherized images across both continuums were regarded as more off-putting than non-thatcherized images, indicating a robust subjective effect of thatcherization that was relatively unimpacted by additional manipulation of key featural components. Conversely, results from brain activity indicated no significant differences of N170 between level of shape stylization and their thatcherized counterparts. Unique effects between continuums and exploratory N400 results are discussed

High Social Acceptance of Head Gaze Loosely Synchronized with Speech for Social Robots

This research demonstrates that robots can achieve socially acceptable interactions, using loosely synchronized head gaze-speech, without understanding the semantics of the dialog. Prior approaches used tightly synchronized head gaze-speech, which requires significant human effort and time to manually annotate synchronization events in advance, restricting interactive dialog, and requiring the operator to act as a puppeteer. This approach has two novel aspects. First, it uses affordances in the sentence structure, time delays, and typing to achieve autonomous synchronization of head gaze-speech. Second, it is implemented within a behavioral robotics framework derived from 32 previous implementations. The efficacy of the loosely synchronized approach was validated through a 93-participant 1 x 3 (loosely synchronized head gaze-speech, tightly synchronized head gaze-speech, no-head gazespeech) between-subjects experiment using the “Survivor Buddy” rescue robot in a victim management scenario. The results indicated that the social acceptance of loosely synchronized head gaze-speech is similar to tightly synchronized head gazespeech (manual annotation), and preferred to the no head gaze-speech case. These findings contribute to the study of social robotics in three ways. First, the research overall contributes to a fundamental understanding of the role of social head gaze in social acceptance, and the production of social head gaze. Second, it shows that autonomously generated head gaze-speech coordination is both possible and acceptable. Third, the behavioral robotics framework simplifies creation, analysis, and comparison of implementations

A Meta-analysis of the Uncanny Valley's Independent and Dependent Variables

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