Key points are not available for this paper at this time.
In response to the growing demand for enhanced integration of implicit measurements in Human-Robot Interaction (HRI) research, the need for studies involving physically present robots, and the calls for a transition from lab experiments to more naturalistic investigations, we introduce the Real-World Implicit Association Task (RW-IAT). This report outlines the versatile methodology of the RW-IAT; emphasizing its allowance to present real-life stimuli and capture behavioral data, including response times and mouse tracking metrics in a controlled manner. Sample analyses focusing on communicative and noncommunicative actions between a human actor and the Pepper robot reveal significant effects on the Agency and Experience dimensions of the mind perception. We believe the methodology we proposed will contribute to conducting ecologically valid research in the field of HRI in real-world contexts.
Pekçetin et al. (Mon,) studied this question.