Slow but Likeable? Inefficient Robots as Caring Team Members

This position paper discusses the notion of efficiency as a criterion for designing and evaluating the contributions that robots might make to human work teams. Participation in teams requires the coordination and prosecution of task-centric work activity but also requires the investment of caring social behavior as a distinctive kind of positive contribution to group interaction. Team spirit, emotional support, trust and reputation are all the outcome of such investments; they reinforce the capabilities of a team for particular joint activities, and contribute to its resilience over time. The requisite social behavior for these qualities of a team might be treated as a given in design considerations for human work teams. But the picture must change for human-robot teams: socially supportive behavior can only exist if it is explicitly designed in, and the consequent “task inefficiencies” are treated as a core part of the design equation. We draw on our own research on relational effort in social communication to offer some initial considerations about how task-inefficient action might be required for robots to engage in caring interactions with human collaborators

How to Include Humanoid Robots into Experimental Research: A Multi-Step Approach

Robots have penetrated many areas of daily life, including increased uses of humanoid robots in personal and organizational settings such as health care, eldercare, and service encounters with customers. Little research examines humanoid robots in these professional settings, even though the human-robot interaction (HRI) is particularly critical in such contexts. On the basis of a literature review and experience from several experimental studies, this article offers some guidance for designing HRI experiments with humanoid robots. In addition to detailing major challenges associated with designing HRI studies, this article suggests important next steps for experimental research with humanoid robots, as well as implications for further study

It Depends on the Timing: The Ripple Effect of AI on Team Decision-Making

Whereas artificial intelligence (AI) is increasingly used to facilitate team decision-making, little is known about how the timing of AI assistance may impact team performance. The study investigates this question with an online experiment in which teams completed a new product development task with assistance from a chatbot. Information needed for making the decision was distributed among the team members. The chatbot shared information critical to the decision in either the first half or second half of team interaction. The results suggest that teams assisted by the chatbot in the first half of the decision-making task made better decisions than those assisted by the chatbot in the second half. Analysis of team member perceptions and interaction processes suggests that having a chatbot at the beginning of team interaction may have generated a ripple effect in the team that promoted information sharing among team members

The Effect of Ingroup Identification on Conformity Behavior in Group Decision-Making: The Flipping Direction Matters

Various social influences affect group decision-making processes. For instance, individuals may adapt their behavior to fit in with the group's majority opinion. Furthermore, ingroup favoritism may lead individuals to favor the ideas of ingroup members rather than the outgroup. So far, little is explored on how these phenomena of social conformity and ingroup favoritism manifest in group decision-making processes when a group has to decide in favor or against an item. We address such a scenario where the `flipping direction' of conformity (in favor or against an item) matters. Specifically, we explore whether and how the ingroup favoritism manifests differently in terms of conformity behavior depending on the `flipping direction'. The results show that group inclusiveness does not play a role in the general tendency to conform. However, when it comes to a negative flipping direction, a higher feeling of group inclusiveness seems to play a role; yet, for individualist cultures only

A Design Space Exploration of Creative Concepts for Care Robots: Questioning the Differentiation of Social and Physical Assistance

In an interdisciplinary project, creative concepts for care robotics were developed. To explore the design space that these open up, we discussed them along the common differentiation of physical (effective) and social-emotional assistance. Trying to rate concepts on these dimensions frequently raised questions regarding the relation between the social-emotional and the physical, and highlighted gaps and a lack of conceptual clarity. We here present our design concepts, report on our discussion, and summarize our insights; in particular we suggest that the social and the physical dimension of care technologies should always be thought of and designed as interrelated

SIG on Telepresence Robots

In this document we explain the need and plans for a SIG Meeting at CHI on telepresence robots. We describe the organization of this SIG, our expected attendees, procedure and schedule of topics to be discussed, as well as our recruitment plan. Our goal is to provide a forum to discuss key issues surrounding the uses and usefulness of telepresence robots, including challenges and best practices

Conversational Agents and their Influence on the Well-being of Clinicians

An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors

Chatbot Catalysts: Improving Team Decision-Making Through Cognitive Diversity and Information Elaboration

As the integration of artificial intelligence (AI) into team decision-making continues to expand, it is both theoretically and practically pressing for researchers to understand the impact of the technology on team dynamics and performance. To investigate this relationship, we conducted an online experiment in which teams made decisions supported by chatbots and employed computational methods to analyze team interaction processes. Our results indicated that compared to those assisted by chatbots in later phases, teams receiving chatbot assistance during the initial phase of their decision-making process exhibited increased cognitive diversity (i.e., diversity in shared information) and information elaboration (i.e., exchange and integration of information). Ultimately, teams assisted by chatbots early on performed better. These results imply that introducing AI at the beginning of the process can enhance team decision-making by promoting effective information sharing among team members

Slow but Likeable? Inefficient Robots as Caring Team Members

This position paper discusses the notion of efficiency as a criterion for designing and evaluating the contributions that robots might make to human work teams. Participation in teams requires the coordination and prosecution of task-centric work activity but also requires the investment of caring social behavior as a distinctive kind of positive contribution to group interaction. Team spirit, emotional support, trust and reputation are all the outcome of such investments; they reinforce the capabilities of a team for particular joint activities, and contribute to its resilience over time. The requisite social behavior for these qualities of a team might be treated as a given in design considerations for human work teams. But the picture must change for human-robot teams: socially supportive behavior can only exist if it is explicitly designed in, and the consequent “task inefficiencies” are treated as a core part of the design equation. We draw on our own research on relational effort in social communication to offer some initial considerations about how task-inefficient action might be required for robots to engage in caring interactions with human collaborators