Cleaning work is a labor-intensive job that frequently exposes workers to substantial occupational hazards. Unfortunately, the outbreak of coronavirus disease 2019 (COVID-19) has increased the pressure on janitors and cleaners to meet the rising need for a safe and hygienic environment, particularly in grocery stores, where the majority of people get their daily necessities. To reduce the occupational hazards and fulfill the new challenges of COVID-19, autonomous cleaning robots, have been designed to complement human workers. However, a lack of understanding of the new generation of cleaning tools’ acceptance may raise safety concerns when they’re deployed. Therefore, a video-based survey was developed and distributed to 32 participants, aiming to assess human acceptance of the cleaning robot in grocery environments during the COVID-19 pandemic. Moreover, the effects of four factors (gender, work experience, knowledge, and pet) that may influence human acceptance of the cleaning robot were also examined. In general, our findings revealed a non-negative human acceptance of the cleaning robot, which is a positive sign of deploying cleaning robots in grocery stores to reduce the workload of employees and decrease COIVID-related anxiety and safety concerns of customers. Furthermore, prior knowledge of robotics was observed to have a significant effect on participants’ acceptance of the cleaning robot ( p = 0.039).
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Why Should We Gender?: The Effect of Robot Gendering and Occupational Stereotypes on Human Trust and Perceived Competency
The attribution of human-like characteristics onto humanoid robots has become a common practice in Human-Robot Interaction by designers and users alike. Robot gendering, the attribution of gender onto a robotic platform via voice, name, physique, or other features is a prevalent technique used to increase aspects of user acceptance of robots. One important factor relating to acceptance is user trust. As robots continue to integrate themselves into common societal roles, it will be critical to evaluate user trust in the robot's ability to perform its job. This paper examines the relationship among occupational gender-roles, user trust and gendered design features of humanoid robots. Results from the study indicate that there was no significant difference in the perception of trust in the robot's competency when considering the gender of the robot. This expands the findings found in prior efforts that suggest performance-based factors have larger influences on user trust than the robot's gender characteristics. In fact, our study suggests that perceived occupational competency is a better predictor for human trust than robot gender or participant gender. As such, gendering in robot design should be considered critically in the context of the application by designers. Such precautions would reduce the potential for robotic technologies to perpetuate societal gender stereotypes.
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- Award ID(s):
- 1849101
- PAR ID:
- 10139610
- Date Published:
- Journal Name:
- HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
- Page Range / eLocation ID:
- 13 to 21
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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