Interaction Studies - Volume 16, Issue 1, 2015

Young children often treat robots as social agents after they have witnessed interactions that can be interpreted as social. We studied in three experiments whether four-year-olds from three cultures (China, Japan, UK) and adults from two cultures (Japan, UK) will attribute ownership of objects to a robot that engages in social gaze with a human. Participants watched videos of robot-human interactions, in which objects were possessed or new objects were created. Children and adults applied the same ownership rules to humans and robots – irrespective of whether the robot engaged in social gaze or not. However, there was cultural variation in the types of ownership rules used. In Experiment 3, we removed further social cues, finding that just showing a pair of self-propelled robot-arms elicited ownership attributions. The role of social gaze in social attributions to robots and cross-cultural differences in ownership understanding are discussed.

Because robots are physically embodied agents, touch is one of the important modalities through which robots communicate with humans. Among the several factors that affect human-robot interaction, this research focuses on the effect of a user’s personality traits on tactile interactions with a robot. Participants interacted freely with a robot and their tactile interaction patterns were analyzed. Several classifiers were used to examine the effect of a participant’s degree of extroversion on tactile communication patterns with the robot and our results showed that a user’s personality traits affected the way in which they interacted with the robot. Specifically, important features of Bayesian networks, such as the Markov blanket and what-if/goal-seeking power were tested and showed the effect of personality on tactile interaction with respect to where and how participants touched the robot. We also found that, by using Bayesian network classifiers, a user’s personality traits can be inferred based on tactile communication patterns.

Until recently, it was assumed that co-representation of others’ actions, an essential part in joint action, is biologically tuned. However, research demonstrated that we also simulate actions of non-biological interaction partners under certain conditions. In the present study, we investigated whether perceived intentionality or perspective taking is the underlying mechanisms of this phenomenon. Participants saw a short video fragment of a non-biological agent (i.e. a triangle) as main character. The movements of this agent were either described as intentional or as unintentional. Furthermore, participants were instructed to either take the perspective of this non-biological agent or not. Results show that perspective taking and perceived intentionality both lead to action co-representation of non-biological actions. Possible explanations for these findings are discussed.

An emerging topic in robot design and scholarly research is socially assistive robots (SAR) for senior citizens. Compared to robots in other sectors, SARs can augment their assistive-utilitarian functions by offering social, emotional, and cognitive support to seniors. This study draws upon interviews with 45 senior citizens to understand this group’s expectations for human-robot interactions (HRI) and their anticipated needs for robots. Our grounded theory analysis suggests that senior citizens expect robots to meet three types of needs: physical, informational, and interactional. Furthermore, they seek assurances that they will have complete control over interactions with robots. Findings show that seniors’ mental models about robots are shaped by their recent experiences with advanced communications technologies and mediated representations of robots in popular culture. Findings are discussed in light of practical design considerations and two theoretical perspectives.

This article investigates the challenge of developing a robot capable of determining if a social situation demands trust. Solving this challenge may allow a robot to react when a person over or under trusts the system. Prior work in this area has focused on understanding the factors that influence a person’s trust of a robot (Hancock, et al., 2011). In contrast, by using game-theoretic representations to frame the problem, we are able to develop a set of conditions for determining if an interactive situation demands trust. In two separate experiments, human subjects were asked to evaluate either written narratives or mazes in terms of whether or not they require trust. The results indicate a ϕ1= +0.592 and ϕ2 = +0.406 correlation respectively between the subjects’ evaluations and the condition’s predictions. This is a strong correlation for a study involving human subjects.

Human beings possess external stores in which they put all sorts of goods to use them at some later time. In this paper we investigate this typically human adaptation using agent-based simulations. We show that the use of external stores explains many aspects of human life, allowing the agents to reduce their dependence on both the environment and the current state of their body and to be more efficient in extracting the energy contained in the environment. We analyse the spatial behaviour of agents with external stores located in specific positions of the environment and we find that these agents tend to develop a sedentary life. We discuss how stores can be at the origin of many human mental and social phenomena such as the acquisition of a more extended temporal perspective, specialisation in producing different types of goods, and exchange of goods.