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.

机器人正变得越来越可用于工作场所协作，但是仍然存在许多问题。人们是否真的愿意将协作任务分配给机器人？如果是这样，他们究竟将哪些任务分配给哪种类型的机器人？在这里，我们利用关于人的工作适应性和心理感知的心理学理论来研究人机协作工作中的任务分配。我们建议人们根据他们的“感知头脑”将机器人分配给工作，并且人们将在协作决策中表现出可预测的社会偏见。在这项研究中，参与者单独执行一项算术（即计算差异）和社交（即判断情绪状态）任务，或者与以下两个机器人之一进行协作：有情感能力的机器人或无情感能力的机器人。合作决定（即，在所有试验中，分配机器人来生成答案的比率都很高，尤其是对于参与者发现具有挑战性的任务（即算术任务）。通过感知到的机器人与任务的配合来预测协作，从而将情感机器人分配给社交任务。有趣的是，算术任务更多地分配给了情感尽管具备情感能力的机器人同样具有计算能力，但他们却没有能力。这与在心智感知和个人工作适应性方面的社会偏见（例如性别偏见）是一致的。这项工作对HRI的理论和实践意义正在讨论中。