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Attitudes Towards Robots Measure (ARM): A New Measurement Tool Aggregating Previous Scales Assessing Attitudes Toward Robots

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Abstract

In the forthcoming decade, interactions between humans and robots are expected to increase gradually. The attitudes that individuals hold towards robots will play a pivotal role in predicting their behavior towards these novel artificial agents, as well as their acceptance across multiple societal pillars. Despite the significant impact of attitudes on the success of human-robot interactions, no existing measure of attitudes towards humanoid robots currently meets the rigorous psychometric standards, particularly in terms of the percentage of variance explained. In this study, we introduce a new measure of attitudes towards robots (ARM), building upon previous scales on the topic, and provide evidence for the scale’s internal and external validity. Through three experiments, we selected the most reliable items pertaining to attitudes towards robots (derived from previous attitudes towards robots’ questionnaires), identified common factors, and tested the internal and external validity of the newly developed measure. Our findings reveal 15 items, underlying attitudes towards robots, divided into three primary factors: prior anxiety, prior acceptability, and prior anthropomorphism. We report the development and validation of the scale, and discuss the identified dimensions in relation to the literature on human-robot interactions and the psychology of robot perception.

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Data Availability

Data can be accessed at https://osf.io/4aduw/.

Notes

  1. Using orthogonal rotation (e.g. VARIMAX), we preserve the independence of the factors. With oblique rotation (e.g. OBLIMIN, PROMAX), we break it and factors are allowed to correlate.

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Spatola, N., Wudarczyk, O.A., Nomura, T. et al. Attitudes Towards Robots Measure (ARM): A New Measurement Tool Aggregating Previous Scales Assessing Attitudes Toward Robots. Int J of Soc Robotics 15, 1683–1701 (2023). https://doi.org/10.1007/s12369-023-01056-3

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