Robots are a source of evaluative conflict and thus elicit ambivalence. In fact, psychological research has shown across domains that people simultaneously report strong positive and strong negative evaluations about one and the same attitude object. This is defined as ambivalence. In the current research, we extended existing ambivalence research by measuring ambivalence towards various robot-related stimuli using explicit (i.e., self-report) and implicit measures. Concretely, we used a mouse tracking approach to gain insights into the experience and resolution of evaluative conflict elicited by robots. We conducted an extended replication across four experiments with N = 411 overall. This featured a mixed-methods approach and included a single paper meta-analysis. Thereby, we showed that the amount of reported conflicting thoughts and feelings (i.e., objective ambivalence) and self-reported experienced conflict (i.e., subjective ambivalence) were consistently higher towards robot-related stimuli compared to stimuli evoking univalent responses. Further, implicit measures of ambivalence revealed that response times were higher when evaluating robot-related stimuli compared to univalent stimuli, however results concerning behavioral indicators of ambivalence in mouse trajectories were inconsistent. This might indicate that behavioral indicators of ambivalence apparently depend on the respective robot-related stimulus. We could not obtain evidence of systematic information processing as a cognitive indicator of ambivalence, however, qualitative data suggested that participants might focus on especially strong arguments to compensate their experienced conflict. Furthermore, interindividual differences did not seem to substantially influence ambivalence towards robots. Taken together, the current work successfully applied the implicit and explicit measurement of ambivalent attitudes to the domain of social robotics, while at the same time identifying potential boundaries for its application.

机器人是评价性冲突的根源，因此会引发矛盾心理。事实上，跨领域的心理学研究表明，人们同时对同一个态度对象做出强烈的积极评价和强烈的消极评价。这被定义为矛盾心理。在当前的研究中，我们通过使用显式（即自我报告）和隐式测量来测量对各种机器人相关刺激的矛盾心理，从而扩展了现有的矛盾心理研究。具体来说，我们使用鼠标跟踪方法来深入了解机器人引发的评估性冲突的体验和解决方案。我们在四个实验中进行了扩展重复，总共N = 411。该方法采用混合方法，并包括一篇论文荟萃分析。因此，我们发现，与引起单价反应的刺激相比，与机器人相关的刺激所报告的冲突想法和感受（即客观矛盾心理）和自我报告的经历冲突（即主观矛盾心理）的数量始终较高。此外，矛盾心理的隐式测量表明，与单价刺激相比，评估机器人相关刺激时的反应时间更长，但有关小鼠轨迹中矛盾心理行为指标的结果却不一致。这可能表明矛盾心理的行为指标显然取决于相应的机器人相关刺激。我们无法获得系统信息处理作为矛盾心理认知指标的证据，然而，定性数据表明参与者可能会关注特别有力的论据来补偿他们经历过的冲突。此外，个体之间的差异似乎并没有显着影响人们对机器人的矛盾心理。总而言之，当前的工作成功地将矛盾态度的隐式和显式测量应用于社交机器人领域，同时确定了其应用的潜在边界。