Driven by state-of-the-art AI technologies, human-AI collaboration has become an important area in computer-supported teamwork research. While human-AI collaboration has been investigated in various domains, more research is needed to explore human perceptions and expectations of AI teammates in human-AI teaming. To achieve an in-depth understanding of how people perceive AI teammates and what they expect from AI teammates in human-AI teaming, we conducted a survey with 213 participants and a follow-up interview with 20 participants. Considering the context-dependency of teamwork, we chose to study human-AI teaming in the context of multiplayer online games as a case study. This study shows that people have mixed feelings toward AI teammates but hold a positive attitude toward future collaboration with AI teammates in general. Our findings highlight people's expectations for AI teammates in a rapidly changing collaborative environment (e.g., instrumental skills for in-game tasks, shared understanding between humans and AI, communication capabilities, human-like behaviors and performance), as well as factors that impact people's willingness to team up with AI teammates (e.g., pre-existing attitudes toward AI, previous collaboration experience with humans). We contribute to CSCW by shedding light on how AI should be structured in human-AI teaming to support highly complex collaborative activities in CSCW environments.
A large body of research has underscored the importance of the cognitive process of team cognition and its relation to team performance. However, little research has focused on applying such an important teamwork process to computer-mediated collaboration within a fast-paced virtual environment. In this paper, we use esports as a research platform to address this limitation due to its fast-paced nature and its heavy reliance on teamwork. We report the experience and perceptions of 20 players with regard to their descriptions of team cognition within esports. We found that esports players relied on their game experience and understanding of role interdependencies in order to develop team cognition with strangers. We also found that experienced teams utilized a mutual understanding of teammate skills and personalities in order to predict responses and limit the verbal communication required to make quick team decisions. We contribute to CSCW by extending the cognitive understanding of computer-mediated collaboration and by advancing research on team cognition and how it can occur within a fast-paced virtual environment.
Awareness, and specifically, spatial awareness, has long played a pivotal role in Computer-Supported Cooperative Work research in both theory and design. This significant background gives awareness the ability to answer challenges facing human-agent teams in communication and shared understanding. As such, the current study investigates the effects of spatial information level (low, high) on the development of team cognition and its outcomes in varying compositions of human-agent teams (human-human-agent, human-agent-agent) versus human-only (human-human-human) teams. The mixed-methods study had teams complete several rounds of the NeoCITIES emergency response management simulation and complete various team cognition and perception measures, followed by qualitative free-response questions. The study found that human-only teams did not perform at the same level as human-agent teams, with multi-agent human-agent teams having the best performance. A significant interaction, though with inconclusive simple main effects, displayed the trend that human-agent teams had better team mental model similarity when spatial awareness was high rather than low, while human-only teams experienced the reverse trend. Qualitative findings identified that high spatial awareness jump-started team cognition development, fostered more accurate shared mental models, enhanced the explainability of the agent, and helped the iterative development of team cognition over time.
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