Degree Of Human-likeness Research Articles

Influence of appearance and motion interaction on emotional state attribution to objects: The example of hugging shimeji mushrooms

Feeling that a non-human object has emotions (hereinafter referred to as emotional state attribution) is generally known as animacy perception. Previous studies have considered appearance and motion separately as factors that evoke emotional state attribution. Then, if both the degree of human likeness in shape and the presence or absence of motion are considered simultaneously, is there a possibility of strong emotional state attribution even for objects that are not human-like in terms of shape? In this study, we experimentally investigated the influence of human likeness in shape and movements evoking social relations on emotional state attribution, including their interaction, using three types of objects (human figure, shimeji mushroom, and match) that were assumed to differ from humans in terms of shape. We conducted three experiments. In Experiment 1, although the human figure was rated as more human-like than the shimeji mushroom in terms of shape, emotions were attributed more strongly to the shimeji mushroom than to the human figure when accompanied by movements that evoked social relationships. In Experiment 2, a follow-up to Experiment 1 was conducted by eliminating the influence of three-dimensionality, and similar results to Experiment 1 were obtained. In Experiment 3, the influence of face parts was examined, and emotions were attributed more strongly when motion was given to an object without face parts. The results suggest that people may attribute emotions more strongly to faceless objects that resemble humans only to a certain extent in shape when they show movements that evoke social relations.

Balancing Human Likeness in Social Robots: Impact on Children’s Lexical Alignment and Self-disclosure for Trust Assessment

While there is evidence that human-like characteristics in robots could benefit child-robot interaction in many ways, open questions remain about the appropriate degree of human likeness that should be implemented in robots to avoid adverse effects on acceptance and trust. This study investigates how human likeness, appearance and behavior, influence children’s social and competency trust in a robot. We first designed two versions of the Furhat robot with visual and auditory human-like and machine-like cues validated in two online studies. Secondly, we created verbal behaviors where human likeness was manipulated as responsiveness regarding the robot’s lexical matching. Then, 52 children (7-10 years old) played a storytelling game in a between-subjects experimental design. Results show that the conditions did not affect subjective trust measures. However, objective measures showed that human likeness affects trust differently. While low human-like appearance enhanced social trust, high human-like behavior improved children’s acceptance of the robot’s task-related suggestions. This work provides empirical evidence on manipulating facial features and behavior to control human likeness in a robot with a highly human-like morphology. We discuss the implications and importance of balancing human likeness in robot design and its impacts on task performance, as it directly impacts trust-building with children.

Human-robot interaction: the impact of robotic aesthetics on anticipated human trust.

BackgroundHuman senses have evolved to recognise sensory cues. Beyond our perception, they play an integral role in our emotional processing, learning, and interpretation. They are what help us to sculpt our everyday experiences and can be triggered by aesthetics to form the foundations of our interactions with each other and our surroundings. In terms of Human-Robot Interaction (HRI), robots have the possibility to interact with both people and environments given their senses. They can offer the attributes of human characteristics, which in turn can make the interchange with technology a more appealing and admissible experience. However, for many reasons, people still do not seem to trust and accept robots. Trust is expressed as a person’s ability to accept the potential risks associated with participating alongside an entity such as a robot. Whilst trust is an important factor in building relationships with robots, the presence of uncertainties can add an additional dimension to the decision to trust a robot. In order to begin to understand how to build trust with robots and reverse the negative ideology, this paper examines the influences of aesthetic design techniques on the human ability to trust robots.MethodThis paper explores the potential that robots have unique opportunities to improve their facilities for empathy, emotion, and social awareness beyond their more cognitive functionalities. Through conducting an online questionnaire distributed globally, we explored participants ability and acceptance in trusting the Canbot U03 robot. Participants were presented with a range of visual questions which manipulated the robot’s facial screen and asked whether or not they would trust the robot. A selection of questions aimed at putting participants in situations where they were required to establish whether or not to trust a robot’s responses based solely on the visual appearance. We accomplished this by manipulating different design elements of the robots facial and chest screens, which influenced the human-robot interaction.ResultsWe found that certain facial aesthetics seem to be more trustworthy than others, such as a cartoon face versus a human face, and that certain visual variables (i.e., blur) afforded uncertainty more than others. Consequentially, this paper reports that participant’s uncertainties of the visualisations greatly influenced their willingness to accept and trust the robot. The results of introducing certain anthropomorphic characteristics emphasised the participants embrace of the uncanny valley theory, where pushing the degree of human likeness introduced a thin line between participants accepting robots and not. By understanding what manipulation of design elements created the aesthetic effect that triggered the affective processes, this paper further enriches our knowledge of how we might design for certain emotions, feelings, and ultimately more socially acceptable and trusting robotic experiences.

Human-Like Robots and the Uncanny Valley

Abstract. In the field of human-robot interaction, the well-known uncanny valley hypothesis proposes a curvilinear relationship between a robot’s degree of human likeness and the observers’ responses to the robot. While low to medium human likeness should be associated with increased positive responses, a shift to negative responses is expected for highly anthropomorphic robots. As empirical findings on the uncanny valley hypothesis are inconclusive, we conducted a random-effects meta-analysis of 49 studies (total N = 3,556) that reported 131 evaluations of robots based on the Godspeed scales for anthropomorphism (i.e., human likeness) and likeability. Our results confirm more positive responses for more human-like robots at low to medium anthropomorphism, with moving robots rated as more human-like but not necessarily more likable than static ones. However, because highly anthropomorphic robots were sparsely utilized in previous studies, no conclusions regarding proposed adverse effects at higher levels of human likeness can be made at this stage.

Exploring the Perceptions of Cognitive and Affective Capabilities of Four, Real, Physical Robots with a Decreasing Degree of Morphological Human Likeness

This paper describes an investigation of student perceptions of the cognitive and affective capabilities of four robots that have a decreasing degree of morphological human likeness. We showed and illustrated the robots (i.e., InMoov, Padbot, Joy Robot and Turtlebot) to 62 students. After showing the students each of these robots, and explaining their main features and capabilities, we administered a fill-in questionnaire to the students. Our main hypothesis was that the perception of a robot’s cognitive and affective capabilities varied in correspondence with their appearance and in particular with their different degree of human likeness. The main results of this study indicate that the scores attributed to the cognitive and emotional capabilities of these robots are not modulated correspondingly to their different morphological similarity to humans. Furthermore, overall, the scores given to all of these robots regarding their ability to explicate mental functions are low, and even lower scores are given to their ability to feel emotions. There is a split between InMoov, the robot which has the highest degree of human likeness, and all of the others. Our results also indicate that: (1) morphological similarity of a robot to humans is not perceived automatically as such by observers, which is not considered a value in itself for the robot; and (2) even at lower levels of robot–human likeness, an uncanny valley effect arises but is quite mitigated by curiosity.

User Responses to a Humanoid Robot Observed in Real Life, Virtual Reality, 3D and 2D.

Humanoid robots (i.e., robots with a human-like body) are projected to be mass marketed in the future in several fields of application. Today, however, user evaluations of humanoid robots are often based on mediated depictions rather than actual observations or interactions with a robot, which holds true not least for scientific user studies. People can be confronted with robots in various modes of presentation, among them (1) 2D videos, (2) 3D, i.e., stereoscopic videos, (3) immersive Virtual Reality (VR), or (4) live on site. A systematic investigation into how such differential modes of presentation influence user perceptions of a robot is still lacking. Thus, the current study systematically compares the effects of different presentation modes with varying immersive potential on user evaluations of a humanoid service robot. Participants (N = 120) observed an interaction between a humanoid service robot and an actor either on 2D or 3D video, via a virtual reality headset (VR) or live. We found support for the expected effect of the presentation mode on perceived immediacy. Effects regarding the degree of human likeness that was attributed to the robot were mixed. The presentation mode had no influence on evaluations in terms of eeriness, likability, and purchase intentions. Implications for empirical research on humanoid robots and practice are discussed.

Modelling User Preference for Embodied Artificial Intelligence and Appearance in Realistic Humanoid Robots

Realistic humanoid robots (RHRs) with embodied artificial intelligence (EAI) have numerous applications in society as the human face is the most natural interface for communication and the human body the most effective form for traversing the manmade areas of the planet. Thus, developing RHRs with high degrees of human-likeness provides a life-like vessel for humans to physically and naturally interact with technology in a manner insurmountable to any other form of non-biological human emulation. This study outlines a human–robot interaction (HRI) experiment employing two automated RHRs with a contrasting appearance and personality. The selective sample group employed in this study is composed of 20 individuals, categorised by age and gender for a diverse statistical analysis. Galvanic skin response, facial expression analysis, and AI analytics permitted cross-analysis of biometric and AI data with participant testimonies to reify the results. This study concludes that younger test subjects preferred HRI with a younger-looking RHR and the more senior age group with an older looking RHR. Moreover, the female test group preferred HRI with an RHR with a younger appearance and male subjects with an older looking RHR. This research is useful for modelling the appearance and personality of RHRs with EAI for specific jobs such as care for the elderly and social companions for the young, isolated, and vulnerable.

Gender Effects in Observation of Robotic and Humanoid Actions.

Robots are gaining an increasingly important role in industrial production. Notably, a high level of acceptance is an important factor for co-working situation between human and robot. The aim of the present study was to investigate the differences in the perception of anthropomorphic and robotic movements using models consisting of a virtual robot and a digital human. Videos of each model displayed different degrees of human likeness or robot likeness in speed and trajectories of placing movements. Female and male participants were asked to rate on a Likert scale the perceived levels of human likeness or robot likeness in the two models. Overall, results suggest that males were sensitive to the differences between robotic and anthropomorphic movements, whereas females showed no difference between them. However, compared to males, female participants attributed more anthropomorphic features to robotic movements. The study is a first step toward a more comprehensive understanding of the human ability to differentiate between anthropomorphic and robotic movements and suggests a crucial role of gender in the human-robot interaction.

Human-likeness assessment for the Uncanny Valley Hypothesis

Abstract The Uncanny Valley Hypothesis (UVH, proposed in the 1970s) suggests that looking at or interacting with almost human-like artificial characters would trigger eeriness or discomfort. We studied how well subjects can assess degrees of human likeness for computer-generated characters. We conducted two studies, where subjects were asked to assess human likeness of given computer-generated models (Study 1) and to point the most typical model for a given category (Study 2). The results suggest that evaluation of the way human likeness is assessed should be an internal part of UVH research.

3D 캐릭터 모델의 추상화와 리얼리즘이 언캐니 밸리 현상에 미치는 영향

본 연구의 목적은 언캐니 밸리 현상을 회피하는 가이드라인으로 언급되는 카툰-리얼리즘이 실제 효과가 있는지를 정량적, 실증적으로 검증하는 것이다. 이를 위해, 3D 모델의 외형을 만화처럼 추상화하고, 여기에 피부 질감을 인간의 피부처럼 사실적으로 표현하는 방법이 언캐니 밸리와 관련된 부정적 감성을 실제로 감소시킬 수 있는지를 실험을 통해 조사하였다. 실험결과, 만화형 3D 모델에 인간 피부재질을 적용하게 되면 섬뜩함의 정도가 통계적으로 유의하게(p<0.05) 높아지게 되며, 인간다움의 정도에는 변화가 없는 것으로 나타났다. 또한 인간형 3D모델에 만화형식의 피부재질을 적용하면 섬뜩한 정도(또는 친근함)에 통계적으로 유의한 차이가 나타나지 않으나, 인간다움의 정도는 통계적으로 유의하게(p<0.05) 낮아지는 것으로 분석되었다. 이러한 결과는 카툰-리얼리즘이 실제로는 큰 효과가 없으며, 오히려 지각단서의 충돌을 야기하여 언캐니 밸리를 유발할 수 있음을 보여준다. 본 연구의 결과는 추후 언캐니 밸리를 극복하는 디자인 가이드라인을 개발하는 데 있어 정량적이며, 실증적인 기초 자료로 활용 가능할 것으로 기대된다. The purpose of this study is to quantitatively and empirically investigate whether cartoon-realism, which is referred to as a guideline for avoiding the uncanny valley phenomenon, is actually effective. An experiment was carried out to investigate whether or not methods that try to realistically express the texture of human skin while making 3D models whose outward appearance abstract like a cartoon actually reduce the negative sentiments associated with the uncanny valley phenomenon. The results found that when human skin textures were applied to cartoon-type 3D models, the degree of eeriness significantly increased (p<0.05), while there was no change in the degree of human likeness. When cartoon-style skin textures were applied to human-type 3D models, there was no significant difference in the degree of eeriness, but the degree of human likeness significantly decreased (p<0.05). These results show that, cartoon realism is not actually effective, and rather creates a perceptual conflict and induces the uncanny valley phenomenon. The results of this study are expected to be used as quantitative and empirical data for developing design guidelines that will overcome the uncanny valley phenomenon in the future.

Trust in Automated Agents is Modulated by the Combined Influence of Agent and Task Type

Trust in automation is an important topic in the field of human factors and has a substantial impact on both attitudes towards and performance with automated systems. One variable that has been shown to influence trust is the degree of human-likeness that is displayed by the automated system with the main finding being that increased human-like appearance leads to increased ratings of trust. In the current study, we investigate whether humanness unanimously leads to higher trust or whether the degree to which an agent is trusted depends on context variables (i.e., task type). For that purpose, we created a task with a social (i.e., judging emotional states from the eye region) and an analytical component (i.e., mathematical task) and measured how strongly participants complied to human, avatar or computer agents when performing the social versus the analytical version with them. We hypothesized that human-like agents are trusted more on social tasks, while machine-like agents are trusted more on analytical tasks. In line with our hypothesis, the results show that, human agents are in general not trusted more than automated agents but that the degree to which an agent is trusted depends on the anticipated expertise of an agent for a given task. The findings suggest that when designing automated systems that are supposed to interact with humans, the degree of humanness of the agent needs to match the degree to which a task requires social skills.

Observation and imitation of actions performed by humans, androids, and robots: an EMG study.

Understanding others’ actions is essential for functioning in the physical and social world. In the past two decades research has shown that action perception involves the motor system, supporting theories that we understand others’ behavior via embodied motor simulation. Recently, empirical approach to action perception has been facilitated by using well-controlled artificial stimuli, such as robots. One broad question this approach can address is what aspects of similarity between the observer and the observed agent facilitate motor simulation. Since humans have evolved among other humans and animals, using artificial stimuli such as robots allows us to probe whether our social perceptual systems are specifically tuned to process other biological entities. In this study, we used humanoid robots with different degrees of human-likeness in appearance and motion along with electromyography (EMG) to measure muscle activity in participants’ arms while they either observed or imitated videos of three agents produce actions with their right arm. The agents were a Human (biological appearance and motion), a Robot (mechanical appearance and motion), and an Android (biological appearance and mechanical motion). Right arm muscle activity increased when participants imitated all agents. Increased muscle activation was found also in the stationary arm both during imitation and observation. Furthermore, muscle activity was sensitive to motion dynamics: activity was significantly stronger for imitation of the human than both mechanical agents. There was also a relationship between the dynamics of the muscle activity and motion dynamics in stimuli. Overall our data indicate that motor simulation is not limited to observation and imitation of agents with a biological appearance, but is also found for robots. However we also found sensitivity to human motion in the EMG responses. Combining data from multiple methods allows us to obtain a more complete picture of action understanding and the underlying neural computations.

Eerie Prostheses and Kinky Strap-Ons: Mori’s uncanny valley and ableist ideology

In his paper ‘The Uncanny Valley’ (1970), Masahiro Mori advises designers to avoid high degrees of human likeness in prosthetic body parts in order not to evoke uncanniness. Building on a discussion of the difference in the commonly experienced uncanniness of ‘realistic’ looking prosthetic hands and strap-on dildos, this paper argues that Mori’s hypothesis and his approach to design are based on an essentialist concept of the human body, which is complicit in the persistence of ableist body ideologies. Reading recent empirical research on the uncanny valley in the context of Jentsch’s and Freud’s writing, it is suggested that the design of body-related artefacts should promote, rather than avoid, repetitious uncanny experiences. Such a project aims to diminish uncanniness through ‘force of habit’, thus facilitating the acceptance of a broader variety of bodies as equal.

Haptic Human–Robot Collaboration: Comparison of Robot Partner Implementations in Terms of Human-Likeness and Task Performance

In the past, working spaces of humans and robots were strictly separated, but recent developments have sought to bring robots into closer interaction with humans. In this context, physical human–robot interaction represents a major challenge, as it is based on continuous bilateral information and energy exchanges which result in a mutual adaptation of the partners. To address the challenge of designing robot collaboration partners, making them as human-like as possible is an approach often adopted. In order to compare different implementations with each other, their degree of human-likeness on a continuous scale is required. So far, the human-likeness of haptic interaction partners has only been studied in the form of binary choices. In this paper, we first introduce methods that allow measuring the human-likeness of haptic interaction partners on a continuous scale. In doing so, two subjective rating methods are proposed and correlated with a task performance measure. To demonstrate the applicability and validity of the proposed measures, they are applied to a joint kinesthetic manipulation task and used to compare two different implementations of a haptic interaction partner: a feedforward model based on force replay, and a feedback model. This experiment demonstrates the use of the proposed measures in building a continuous human-likeness scale and the interpretation of the scale values achieved for formulating guidelines for future robot implementations.

Empathy and Dyspathy with Androids: Philosophical, Fictional, and (Neuro)Psychological Perspectives

The fact that we develop feelings towards androids, i.e., objects with a humanlike appearance, has fascinated people since ancient times. However, as a short survey of the topic in history, science fiction literature and film shows, our emotional reactions towards them are ambivalent. On the one hand, we can develop feelings of empathy almost as we do with real human beings; on the other hand, we feel repulsion or dyspathy when those creatures show a very high degree of human likeness. Recently, Japanese roboticist Masahiro Mori coined the term “uncanny valley” to refer to this effect. The aim of this essay is, first, to give an explanation as to why we feel empathy towards androids although we know that they do not have feelings themselves. This presupposes a perception-based concept of empathy which is going to be developed on the basis of some of Theodor Lipps’ ideas. The second question to be answered is why empathy with androids turns into dyspathy when they become very humanlike. As I will argue, this is due to a particular kind of interference between perception and the imagination when confronted with very humanlike objects. This makes androids quite special objects right at the divide between humans and non-humans. They are non-human, but we feel ill at ease when treating them as mere objects.

Recognizing Emotion in Virtual Agent, Synthetic Human, and Human Facial Expressions

A growing interest in the HCI community is the design and development of embodied agents in virtual environments. For virtual environments where social interaction is needed, an agent's facial expression may communicate emotive state to users both young and old. However, younger and older adults differ in how they label human facial expressions (Ruffman et al., 2008). Such possible age-related differences in labeling virtual agent expressions may impact the user's social experience in a virtual environment. The purpose of the current research was to investigate age-related differences in emotion recognition of several on-screen characters of varying degrees of human-likeness. Participants performed a recognition task with three characters demonstrating four basic emotions or neutral. The results indicated age-related differences for all character types. Older adults commonly mislabeled the human and synthetic human emotions of anger, fear, sadness, and neutral. For the virtual agent face, older adults commonly mislabeled the emotions of anger, fear, happiness, and neutral.

Revisiting the uncanny valley theory: Developing and validating an alternative to the Godspeed indices

Mori (1970) proposed a hypothetical graph describing a nonlinear relation between a character’s degree of human likeness and the emotional response of the human perceiver. However, the index construction of these variables could result in their strong correlation, thus preventing rated characters from being plotted accurately. Phase 1 of this study tested the indices of the Godspeed questionnaire as measures of humanlike characters. The results indicate significant and strong correlations among the relevant indices ( Bartneck, Kulić, Croft, & Zoghbi, 2009). Phase 2 of this study developed alternative indices with nonsignificant correlations ( p > .05) between the proposed y-axis eeriness and x-axis perceived humanness ( r = .02). The new humanness and eeriness indices facilitate plotting relations among rated characters of varying human likeness.