Abstract
Robots are becoming more available for workplace collaboration, but many questions remain. Are people actually willing to assign collaborative tasks to robots? And if so, exactly which tasks will they assign to what kinds of robots? Here we leverage psychological theories on person-job fit and mind perception to investigate task assignment in human–robot collaborative work. We propose that people will assign robots to jobs based on their “perceived mind,” and also that people will show predictable social biases in their collaboration decisions. In this study, participants performed an arithmetic (i.e., calculating differences) and a social (i.e., judging emotional states) task, either alone or by collaborating with one of two robots: an emotionally capable robot or an emotionally incapable robot. Decisions to collaborate (i.e., to assign the robots to generate the answer) rates were high across all trials, especially for tasks that participants found challenging (i.e., the arithmetic task). Collaboration was predicted by perceived robot-task fit, such that the emotional robot was assigned the social task. Interestingly, the arithmetic task was assigned more to the emotionally incapable robot, despite the emotionally capable robot being equally capable of computation. This is consistent with social biases (e.g., gender bias) in mind perception and person-job fit. The theoretical and practical implications of this work for HRI are being discussed.
Highlights
Collaboration is a driving force of success and innovation [16]
The results show that agent preferences were driven by robot-task fit, such that the emotional robot was chosen more often to respond to the social task and the emotionless robot was chosen more often to respond to the arithmetic task
While the preference for the emotional over the emotionless robot for the social task was reflected in higher proficiency ratings for the emotional robot for the social task, the preference for the emotionless over the emotional robot for the arithmetic task was not reflected in higher proficiency ratings for the emotionless robot for the arithmetic task
Summary
Collaboration (i.e., offloading parts of one’s own task to others) is a driving force of success and innovation [16]. It is because they are able to effectively. Albert‐Einstein‐Allee 47, 89069 Ulm, Germany 3 University of North Carolina, Chapel Hill, NC, USA manage the unique skills of team members [2]. The importance of optimizing collaborations has given rise to an entire literature of psychological research that documents how people make decisions about joint tasks [9]. As robots become more and more common as work partners, we need to reveal how people choose to rely upon mechanical agents in shared activities [12]. This work is crucial as robots and the tasks they are designed for continue to diversify
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