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

Building Persuasive Robots with Social Power Strategies

Can social power endow social robots with the capacity to persuade? This paper represents our recent endeavor to design persuasive social robots. We have designed and run three different user studies to investigate the effectiveness of different bases of social power (inspired by French and Raven's theory) on peoples' compliance to the requests of social robots. The results show that robotic persuaders that exert social power (specifically from expert, reward, and coercion bases) demonstrate increased ability to influence humans. The first study provides a positive answer and shows that under the same circumstances, people with different personalities prefer robots using a specific social power base. In addition, social rewards can be useful in persuading individuals. The second study suggests that by employing social power, social robots are capable of persuading people objectively to select a less desirable choice among others. Finally, the third study shows that the effect of power on persuasion does not decay over time and might strengthen under specific circumstances. Moreover, exerting stronger social power does not necessarily lead to higher persuasion. Overall, we argue that the results of these studies are relevant for designing human--robot-interaction scenarios especially the ones aiming at behavioral change

AI and Gender in Persuasion: Using Chatbots to Prevent Driving Under The Influence of Marijuana

Will new media techniques, such as artificial intelligence (AI), help refresh public safety advertising campaigns and help better target specific populations, and aid in persuasive, preventative marketing? This paper used hypocrisy induction as a persuasive tool for standalone artificial intelligence chatbots to test potential behavioral change in the context of marijuana. This research further tested whether the chatbots\u27 gender and language styles impact how persuasive and effective the chat agents are perceived to be using hypocrisy induction. An online experiment conducted with 705 participants (Mage = 42.9, 392 women). where participants interact with a chatbot that is manipulated as male/female and uses formal/causal language. Half of the participants received the hypocrisy induction manipulation. hypocrisy induction is more effective when chatbot gender and linguistic styles are appropriately paired. Participants in the hypocrisy induction condition exhibited higher WTP than those in the non-hypocrisy induction condition when the chatbot they interacted with was female in gender and used casual language. However, hypocrisy induction increased WTP than those who did not receive the hypocrisy induction manipulation when the gender of the chatbot they interacted with was male and used formal language. To the researchers\u27 knowledge, this is among the first studies testing the persuasive power of hypocrisy induction using new media platforms in public safety and health advertising in marijuana studies. Findings not only help to shed light on the persuasiveness of gender and language in standalone chatbots but also provide practical implications for practitioners on the future usage of chatbots

Theory of Robot Communication: II. Befriending a Robot over Time

In building on theories of Computer-Mediated Communication (CMC), Human-Robot Interaction, and Media Psychology (i.e. Theory of Affective Bonding), the current paper proposes an explanation of how over time, people experience the mediated or simulated aspects of the interaction with a social robot. In two simultaneously running loops, a more reflective process is balanced with a more affective process. If human interference is detected behind the machine, Robot-Mediated Communication commences, which basically follows CMC assumptions; if human interference remains undetected, Human-Robot Communication comes into play, holding the robot for an autonomous social actor. The more emotionally aroused a robot user is, the more likely they develop an affective relationship with what actually is a machine. The main contribution of this paper is an integration of Computer-Mediated Communication, Human-Robot Communication, and Media Psychology, outlining a full-blown theory of robot communication connected to friendship formation, accounting for communicative features, modes of processing, as well as psychophysiology.Comment: Hoorn, J. F. (2018). Theory of robot communication: II. Befriending a robot over time. arXiv:cs, 2502572(v1), 1-2

Talking Nets: A Multi-Agent Connectionist Approach to Communication and Trust between Individuals

A multi-agent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other, and as such is a network of networks. The individual recurrent networks simulate the process of information uptake, integration and memorization within individual agents, while the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents’ existing beliefs, and results in changes of the connections between individual networks, called trust weights. Thus activation spreading and weight change between individual networks is analogous to standard connectionist processes, although trust weights take a specific function. Specifically, they lead to a selective propagation and thus filtering out of less reliable information, and they implement Grice’s (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intra-personal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions

Perceived gender and its effect on attributions toward avatars in the video game Spore

In this study, 174 undergraduates from the University of Central Florida were asked to rate individual human and animal avatar features from the video game Spore on their level of femininity, masculinity, likability, and how well the feature represented them on a 7 point Likert scale of agreeability. Avatar features were presented on a neutral gray, quadruped body in two different views. It was expected that participants would show higher likability for avatar features that they perceived as corresponding to their Personal Attribute Questionnaire (PAQ) gender. Males liked feminine features approximately the same as females, however, in many categories females liked the most masculine features more than the most feminine features. Males liked the most masculine body detail feature more than females, and females liked the most masculine body detail more than males. It also was anticipated that avatar features rated as having both low femininity and low masculinity would be the features rated lowest in likability overall. These features did not have the lowest likability, but were somewhat close to neutral in likability. These results have implications for likable avatar creation for businesses, the military, and education

Affect and believability in game characters:a review of the use of affective computing in games

Virtual agents are important in many digital environments. Designing a character that highly engages users in terms of interaction is an intricate task constrained by many requirements. One aspect that has gained more attention recently is the effective dimension of the agent. Several studies have addressed the possibility of developing an affect-aware system for a better user experience. Particularly in games, including emotional and social features in NPCs adds depth to the characters, enriches interaction possibilities, and combined with the basic level of competence, creates a more appealing game. Design requirements for emotionally intelligent NPCs differ from general autonomous agents with the main goal being a stronger player-agent relationship as opposed to problem solving and goal assessment. Nevertheless, deploying an affective module into NPCs adds to the complexity of the architecture and constraints. In addition, using such composite NPC in games seems beyond current technology, despite some brave attempts. However, a MARPO-type modular architecture would seem a useful starting point for adding emotions