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Trust plays a critical role in the success of human-robot teams (HRTs). While typically studied as a perceptual attitude, trust also encompasses individual dispositions and interactive behaviors like compliance. Anthropomorphism, the attribution of human-like qualities to robots, is a related phenomenon that designers often leverage to positively influence trust. However, the relationship of anthropomorphism to perceptual, dispositional, and behavioral trust is not fully understood. This study explores how anthropomorphism moderates these relationships in a virtual urban search and rescue HRT scenario. Our findings indicate that the moderating effects of anthropomorphism depend on how a robot’s recommendations and its confidence in them are communicated through text and graphical information. These results highlight the complexity of the relationships between anthropomorphism, trust, and the social conveyance of information in designing for safe and effective human-robot teaming. 

Objective We review the current state-of-the-art in team cognition research, but more importantly describe the limitations of existing theories, laboratory paradigms, and measures considering the increasing complexities of modern teams and the study of team cognition. Background Research on, and applications of, team cognition has led to theories, data, and measures over the last several decades. Method This article is based on research questions generated in a spring 2022 seminar on team cognition at Arizona State University led by the first author. Results Future research directions are proposed for extending the conceptualization of teams and team cognition by examining dimensions of teamness; extending laboratory paradigms to attain more realistic teaming, including nonhuman teammates; and advancing measures of team cognition in a direction such that data can be collected unobtrusively, in real time, and automatically. Conclusion The future of team cognition is one of the new discoveries, new research paradigms, and new measures. Application Extending the concepts of teams and team cognition can also extend the potential applications of these concepts. 

This study investigated in 22 teams, individual and team trust measures reported by two human participants, recruited from a university populace, as they interacted with each other, robotic combat vehicles (RCVs), a human superior, and their team during a simulated Next Generation Combat Vehicle (NGCV) mission conducted within Minecraft. Trust was measured via survey questions based on established metrics and was found to be high toward the human peer, the human superior, and the overall team throughout the mission. In contrast, overall trust in the RCV was significantly lower in phases of the mission when breakdown in RCV functionality caused a hindrance in mission completion. Trust in the RCV was shown to recover as the mission progressed in phases without RCV maintenance issues. The findings reinforce that trust is distinguishable at the individual level and not necessarily perceived the same at the team level. 

Navigation is critical for everyday tasks but is especially important for urban search and rescue (USAR) contexts. Aside from successful navigation, individuals must also be able to effectively communicate spatial information. This study investigates how differences in spatial ability affected overall performance in a USAR task in a simulated Minecraft environment and the effectiveness of an individual’s ability to communicate their location verbally. Randomly selected participants were asked to rescue as many victims as possible in three 10-minute missions. Results showed that sense of direction may not predict the ability to communicate spatial information, and that the skill of processing spatial information may be distinct from the ability to communicate spatial information to others. We discuss the implications of these findings for teaming contexts that involve both processes. 

Abstract Artificial social intelligence (ASI) agents have great potential to aid the success of individuals, human–human teams, and human–artificial intelligence teams. To develop helpful ASI agents, we created an urban search and rescue task environment in Minecraft to evaluate ASI agents’ ability to infer participants’ knowledge training conditions and predict participants’ next victim type to be rescued. We evaluated ASI agents’ capabilities in three ways: (a) comparison to ground truth—the actual knowledge training condition and participant actions; (b) comparison among different ASI agents; and (c) comparison to a human observer criterion, whose accuracy served as a reference point. The human observers and the ASI agents used video data and timestamped event messages from the testbed, respectively, to make inferences about the same participants and topic (knowledge training condition) and the same instances of participant actions (rescue of victims). Overall, ASI agents performed better than human observers in inferring knowledge training conditions and predicting actions. Refining the human criterion can guide the design and evaluation of ASI agents for complex task environments and team composition. 

Trust in autonomous teammates has been shown to be a key factor in human-autonomy team (HAT) performance, and anthropomorphism is a closely related construct that is underexplored in HAT literature. This study investigates whether perceived anthropomorphism can be measured from team communication behaviors in a simulated remotely piloted aircraft system task environment, in which two humans in unique roles were asked to team with a synthetic (i.e., autonomous) pilot agent. We compared verbal and self-reported measures of anthropomorphism with team error handling performance and trust in the synthetic pilot. Results for this study show that trends in verbal anthropomorphism follow the same patterns expected from self-reported measures of anthropomorphism, with respect to fluctuations in trust resulting from autonomy failures.