Research on human-robot collaboration or human-robot teaming, has focused predominantly on understanding and enabling collaboration between a single robot and a single human. Extending human-robot collaboration research beyond the dyad, raises novel questions about how a robot should allocate resources among group members and about what the consequences of such allocation are for a group’s social dynamics and outcomes. Methodological advances are needed to answer these questions allow researchers to collect data about a robot’s impact not only on interactions with the robot but also on interactions of people with each other. This paper presents Robot Assisted Tower Construction, a novel task that allows researchers to examine the impact of a robot’s allocation behavior on the dynamics of a group or team collaborating on a task. By focusing on the question of whether and how a robot’s allocation of resources (wooden blocks required for a building task) affects collaboration dynamics and outcomes, a case is provided of how this task can be applied in a laboratory study with 124 participants to collect data about human robot collaboration that involves a group of people. We highlight the kinds of insights the task can yield and how it can be adapted to various human robot collaboration contexts.

Many of the problems we face are solved in small groups. Using decades of research from psychology, HRI research is increasingly trying to understand how robots impact the dynamics and outcomes of these small groups. Current work almost exclusively uses humanoid robots that take on the role of an active group participant to influence interpersonal dynamics. We argue that this has limitations and propose an alternative design approach of using a peripheral robotic object. This paper presents Micbot, a peripheral robotic object designed to promote participant engagement and ultimately performance using nonverbal implicit interactions. The robot is evaluated in a 3 condition (no movement, engagement behaviour, random movement) laboratory experiment with 36 three-person groups (N=108). Results showed that the robot was effective in promoting not only increased group engagement but also improved problem solving performance. In the engagement condition, participants displayed more even backchanneling toward one another, compared to no movement, but not to the random movement. This more even distribution of backchanneling predicted better problem solving performance.

Interpersonal distance behaviors can vary significantly across countries and impact human social interaction. Do these cross-cultural differences play out when one of the interaction partners participates through a teleoperated robot? Emerging research shows that when being approached by a robot, people tend to hold similar cultural preferences as they would for an approaching human. However, no work yet has investigated this question from a robot teleoperator's perspective. Toward answering this, we conducted an online study (N = 774) using a novel simulation paradigm across two countries (U.S. and India). Results show that in the role of a telepresence robot operator, participants exhibited cross-cultural differences in interpersonal distance behavior in line with human-human proxemic research, indicating that culture-specific distance behavior can manifest in the way a robot operator controls a robot. We discuss implications for designers who seek to automate path planning and navigation for teleoperated robots.

Foreign language students must learn to use language creatively to overcome knowledge gaps and keep readers or listeners interested. However, few tools exist to support practicing this skill. Therefore, we set out to explore design of storytelling games for practicing creative language use. Through an iterative design process, we identified narrative grounding (establishing common ground for collaborative narrative) as key to student engagement and learning. However, designing games for narrative grounding while keeping the game flexible enough to easily accommodate teacher goals is challenging. Considering this challenge, we designed a collaborative storytelling game where students help scaffold the narrative and teachers can easily integrate language goals with "language cards". In an in-classroom evaluation with 36 students, we show the importance of narrative grounding for learning. Qualitative evidence also suggests narrative grounding makes the game more engaging for players. We conclude with discussion of design implications for digital language learning tools.

The ability to constructively resolve interpersonal conflicts is a crucial set of social skills people need to effectively work and live well together. Is it possible to design social robots to support the early development of children's interpersonal conflict resolution skills? To investigate this question, 64 (32 pairs of) children ages 3-6 years engaged in a 50-minute play session consisting of 5 activities facilitated by the robot Keepon. Children were randomly assigned to 1 of 2 conditions. In the mediation condition, Keepon directed the play session flow by indicating when and which activity to switch to, and whenever possible, signaled the onset of object possession conflicts that occurred between the pair and offered prompts for constructive conflict resolution. In the control condition, Keepon only facilitated and directed the play session and did not intervene during children's conflicts. Results show that children were more likely to resolve conflicts constructively in the mediation condition than in the control condition, and that a key function for a robot mediator within the conflict process is to successfully flag the conflict onset. Drawing from these findings, we discuss design recommendation for a robot mediator.

Authentic foreign language videos are effective for developing pragmatic competence, or sensitivity to meanings expressed by tone and word choice, and the ability to effectively express these meanings. However, established methods for learning from foreign language videos are primarily text-based (e.g.captioning). Using text, learners do not practice aspects of oral performance (e.g. intonation, pausing, and pitch) that are important to pragmatic competence. In this paper we present a voice-driven system where learners practice and learn a foreign language by repeating phrases out loud from any video. Utterances are transcribed and translated and, if captions are available, the system indicates the correctness of the utterance. In an evaluation with 27 participants, we show that participants more frequently used the voice-driven system than a comparison text-based system. Furthermore, ina field study of 130 independent learners, we show potential for community-driven resource collection.

Learning from captioned foreign language videos is highly effective, but the availability of such videos is limited. By using speech-to-text technology to generate partially correct transcripts as a starting point, we see an opportunity for learners to build accurate foreign language captions while learning at the same time. We present a system where learners correct captions using automatic transcription and machine-generated suggested alternative words for scaffolding. In a lab study of 49 participants, we found that compared to watching the video with accurate caption, learning and quality of experience were not significantly impaired by the secondary caption correction task using interface designs either with or without scaffolding from speech-to-text generated alternative words. Nevertheless, aggregating corrections reduced word error rate from 19% to 5.5% without scaffolding from suggested-alternatives, and 1.8% with scaffolding. Feedback from participants suggest that emphasizing the learning community contribution aspect is important for motivating learners and reducing frustration.

Is it possible to design robots of the future so that they can enhance people's creative endeavors? Forty-eight young adults were asked to produce their most creative ideas in a small Zen rock garden in a laboratory setting. Participants were randomly assigned to one of two conditions. In one condition, the robot Robovie (through a Wizard of Oz interface) encouraged participants to generate creative ideas (e.g., “Can you think of another way to do that?”), and pulled relevant images and video clip from the web for each participant to look at which could help spur the participant into more creative expressions. In a second condition, participants engaged in the same Zen rock garden task with the same core information, but through the modality of a self-paced PowerPoint presentation. Results showed that participants engaged in the creativity task longer and provided almost twice the number of creative expressions in the robot condition compared to the PowerPoint condition. Discussion focuses on a vision of social robotics coupled with advances in natural language processing to enhance the human creative mind and spirit.

Will people keep the secret of a socially compelling robot who shares, in confidence, a "personal" (robot) failing? Toward answering this question, 81 adults participated in a 20-minute interaction with (a) a humanoid robot (Robovie) interacting in a highly social way as a lab tour guide, and (b) with a human being interacting in the same highly social way. As a baseline comparison, participants also interacted with (c) a humanoid robot (Robovie) interacting in a more rudimentary social way. In each condition, the tour guide asks for the secret keeping behavior. Results showed that the majority of the participants (59%) kept the secret of the highly social robot, and did not tell the experimenter when asked directly, with the robot present. This percentage did not differ statistically from the percentage who kept the human's secret (67%). It did differ statistically when the robot engaged in the more rudimentary social interaction (11%). These results suggest that as humanoid robots become increasingly social in their interaction, that people will form increasingly intimate and trusting psychological relationships with them. Discussion focuses on design principles (how to engender psychological intimacy in human-robot interaction) and norms (whether it is even desirable to do so, and if so in what contexts).

This paper shows how humor can be used as an interaction pattern to help establish sociality in human-robot interaction. Drawing illustratively from our published research on people interacting with ATR's humanoid robot Robovie, we highlight four forms of humor that we successfully implemented: wit and the ice-breaker, corny joke, subtle humor, and dry humor and self-deprecation.

We offer three illustrative examples from one of our recent studies in HRI to suggest that it's possible for people to engage in mutual deliberation with a social robot. Each example illustrates discourse and argument, but ends through different means: Accepting the Robot as Arbitrator; Delegitimizing the Robot; and Agreeing to Disagree.

This research builds on the UbiComp vision of systems that do not do things for people but engage people in their computational environment so that people can do things for themselves better. In this investigation, we sought to make good on a proof-of-concept where people interact with a social robot whereby the robot helps people to be more humanly creative. Twenty seven participants interacted with ATR's humanoid robot Robovie (through a WoZ interface) in a creativity task. Results supported our proof of concept insofar as 100% of the participants generated creative ideas, and 63% incorporated the robot's ideas into their own ideas for their creative output. Of the participants who had the highest creativity scores, 83% incorporated the robot's ideas into their own. Discussion focuses on next steps toward building the Natural Language Processing system, and integrating the system into a more extensive networked UbiComp environment.

Robots will increasingly take on roles in our social lives where they can cause humans harm. When robots do so, will people hold robots morally accountable? To investigate this question, 40 undergraduate students individually engaged in a 15-minute interaction with ATR's humanoid robot, Robovie. The interaction culminated in a situation where Robovie incorrectly assessed the participant's performance in a game, and prevented the participant from winning a $20 prize. Each participant was then interviewed in a 50-minute session. Results showed that all of the participants engaged socially with Robovie, and many of them conceptualized Robovie as having mental/emotional and social attributes. Sixty-five percent of the participants attributed some level of moral accountability to Robovie. Statistically, participants held Robovie less accountable than they would a human, but more accountable than they would a vending machine. Results are discussed in terms of the New Ontological Category Hypothesis and robotic warfare.

This paper discusses converging evidence to support the hypothesis that personified robots and other embodied personified computational systems may represent a new ontological category, where ontology refers to basic categories of being, and ways of distinguishing them.

This conceptual paper draws upon moral philosophy to broach the question: Are robots moral agents?

This conceptual paper broaches possibilities and limits of establishing psychological intimacy in HRI.