Persuaded by the machine : The effect of virtual nonverbal cues and individual differences on compliance in economic bargaining

Receiving a touch or smile increases compliance in natural face-to-face settings. It has been unclear, however, whether a virtual agent’s touch and smile also promote compliance or whether there are individual differences in proneness to nonverbal persuasion. Utilising a multimodal virtual reality, we investigated whether touch and smile promoted compliance to a virtual agent’s requests and whether receiver’s personality modulated the effects. Compliance was measured using the ultimatum game, in which participants were asked to either reject or accept an agent’s monetary offers. Decision-making data were accompanied by offer-related cardiac responses, both of which were analyzed as a function of expression (anger, neutral, and happiness), touch (visuo-tactile, visual, no touch), and three personality traits: behavioral inhibition/activation system sensitivity (BIS/BAS) and justice sensitivity. People accepted unfair offers more often if the agents smiled or touched them. The effect of touch was more enhanced in those with low justice sensitivity and BAS, whereas facial expressions affected those with high BIS the most. Unfair offers amplified the cardiac response, but this effect was not dependent on nonverbal cues. Together, the results suggest that virtual nonverbal behaviors of virtual agents increase compliance and that there is substantial interindividual variation in proneness to persuasion.Receiving a touch or smile increases compliance in natural face-to-face settings. It has been unclear, however, whether a virtual agent's touch and smile also promote compliance or whether there are individual differences in proneness to nonverbal persuasion. Utilizing a multimodal virtual reality, we investigated whether touch and smile promoted compliance to a virtual agent's requests and whether receiver's personality modulated the effects. Compliance was measured using the ultimatum game, in which participants were asked to either reject or accept an agent's monetary offers. Decision-making data were accompanied by offer-related cardiac responses, both of which were analyzed as a function of expression (anger, neutral, and happiness), touch (visuo-tactile, visual, no touch), and three personality traits: behavioral inhibition/activation system sensitivity (BIS/BAS) and justice sensitivity. People accepted unfair offers more often if the agents smiled or touched them. The effect of touch was more enhanced in those with low justice sensitivity and BAS, whereas facial expressions affected those with high BIS the most. Unfair offers amplified the cardiac response, but this effect was not dependent on nonverbal cues. Together, the results suggest that virtual nonverbal behaviors of virtual agents increase compliance and that there is substantial interindividual variation in proneness to persuasion.Peer reviewe

Developing social action capabilities in a humanoid robot using an interaction history architecture

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ICHR.2008.4756013We present experimental results for the humanoid robot Kaspar2 engaging in a simple “peekaboo” interaction game with a human partner. The robot develops the capability to engage in the game by using its history of interactions coupled with audio and visual feedback from the interaction partner to continually generate increasingly appropriate behaviour. The robot also uses facial expressions to feedback its level of reward to the partner. The results support the hypothesis that reinforcement of time-extended experiences through interaction allows a robot to act appropriately in an interaction

Spectators’ aesthetic experiences of sound and movement in dance performance

In this paper we present a study of spectators’ aesthetic experiences of sound and movement in live dance performance. A multidisciplinary team comprising a choreographer, neuroscientists and qualitative researchers investigated the effects of different sound scores on dance spectators. What would be the impact of auditory stimulation on kinesthetic experience and/or aesthetic appreciation of the dance? What would be the effect of removing music altogether, so that spectators watched dance while hearing only the performers’ breathing and footfalls? We investigated audience experience through qualitative research, using post-performance focus groups, while a separately conducted functional brain imaging (fMRI) study measured the synchrony in brain activity across spectators when they watched dance with sound or breathing only. When audiences watched dance accompanied by music the fMRI data revealed evidence of greater intersubject synchronisation in a brain region consistent with complex auditory processing. The audience research found that some spectators derived pleasure from finding convergences between two complex stimuli (dance and music). The removal of music and the resulting audibility of the performers’ breathing had a significant impact on spectators’ aesthetic experience. The fMRI analysis showed increased synchronisation among observers, suggesting greater influence of the body when interpreting the dance stimuli. The audience research found evidence of similar corporeally focused experience. The paper discusses possible connections between the findings of our different approaches, and considers the implications of this study for interdisciplinary research collaborations between arts and sciences

An Approach of Facial Expression Modeling with Changing Trend in the History of Belief States

An Embodied Conversational Agent (ECA) is an intelligent agent that interacts with users through verbal and nonverbal expressions. When used as the front-end of software applications, these agents provide online assistance that transcends the limits of time, location, and even language. To help improve user experience, there is an increasing need to make ECA more realistic, which can be achieved by using more naturalistic facial expressions. The proposed thesis research is going to work on the modeling of facial expressions based on the changing trend in the history of belief states and fuzzy logic. This work enhances the software customization system developed previously in our research group with a modification that links the changing value of belief states with the change of emotion expressions at both the mode and scale levels. In addition, the operation of the proposed method is implemented in an online bookstore system, and its success is verified with a usability study

Artificial Intelligence Is No Match for Human Stupidity: Ethical Reflections on Avatars and Agents

What should our ethical concerns be in a future with ‘Artificially Intelligent’ agents? The zeitgeist of AI agents often envisions a future encompassing a hyper intelligent singularity. In this worldview, AI “monsters” appear very separate from us as, abstracted, ethically ungrounded omnipotent overlords. A world of superintelligences that have moved beyond our comprehension, with no ethical restraint. In this polemic, I explore a different future. I examine how realistic digital humans pose a very real ethical dilemma, as we assume intelligence based on their appearance, leading to an abdication of responsibility. I explore the future of realistic digital agents and avatars, and ask: what does this human-like form say about us? How will we judge ourselves when the computer, looks like us? I argue that the singularity is unlikely and thus the primary ethical concern is not some superhuman AI intelligence, but in how we, ourselves, treat these digital humans