“THIS ISN’T ME!”: The Role of Age-Related Self- and User Images for Robot Acceptance by Elders

Abstract

Although companion-type robots are already commercially available, little interest has been taken in identifying reasons for inter-individual differences in their acceptance. Elders’ age-related perceptions of both their own self (self-image) and of the general older robot user (user image) could play a relevant role in this context. Since little is known to date about elders’ companion-type robot user image, it is one aim of this study to investigate its age-related facets, concentrating on possibly stigmatizing perceptions of elder robot users. The study also addresses the association between elders’ age-related self-image and robot acceptance: Is the association independent of the user image or not? To investigate these research questions, N = 28 adults aged 63 years and older were introduced to the companion-type robot Pleo. Afterwards, several markers of robot acceptance were assessed. Actual and ideal self- and subjective robot user image were assessed by a study-specific semantic differential on the stereotype dimensions of warmth and competence. Results show that participants tended to stigmatize elder robot users. The self-images were not directly related to robot acceptance, but affected it in the context of the user image. A higher fit between self- and user image was associated with higher perceived usefulness, social acceptance, and intention to use the robot. To conclude, elders’ subjective interpretations of new technologies play a relevant role for their acceptance. Together with elders’ individual self-images, they need to be considered in both robot development and implementation. Future research should consider that associations between user characteristics and robot acceptance by elders can be complex and easily overlooked.

Technology Acceptance in Socially Assistive Robots: Scoping Review of Models, Measurement, and Influencing Factors

“…Most of the included articles involved quantitative data collection methods using various constructs and questionnaires. e acceptance of SARs was primarily assessed by constructing technology acceptance models to compile questionnaires [12,14,18,22,23,25,26,29,31,37,40,42,45,47]. Furthermore, self-developed questionnaires were also used [19,20,27,41,43,46].…”

“…In the study by Kodate et al, about 178 (77%) of respondents reported that they were open to the use of home-care robots [40]. e three other studies reported that older adults had negative attitudes towards the idea of SARs in aged care [15,29,47]. Furthermore, they showed low intentions to use the robot.…”

Better than Us: The Role of Implicit Self-Theories in Determining Perceived Threat Responses in HRI

“…Participation was contingent on (a) having completed >50 surveys with a minimal HIT approval rate of 98% or greater, (b) being located in either the USA, UK, Canada, Ireland, Australia, or New Zealand, and (c) having no experience with robotics and/or any expertise in AI (e.g., data science and machine learning). It should be noted here, that both technical expertise and experience with robotics, have been found consistently to predict favorable responses toward, and acceptance of, social robots [e.g., 23,65,26,63,107,62,96]. Thus, it seemed reasonable to exclude such individuals as they may have obscured our findings.…”

Effect of customer's perception on service robot acceptance

“…As shown in Appendix Table A1, we collected 20 papers published from 2017 to 2020 about user acceptance of service robots. These studies used theories including TAM (Hwa et al., 2018; Saadatzi et al., 2020), UTAUT (Guggemos et al., 2020; Kencebay, 2019), DIT (Khaksar et al., 2019), Attribution Theory (Belanche et al., 2020), Self‐Congruity Theory (Dudek et al., 2020), and Uncanny Valley Theory (Appel et al., 2020). Based on TAM/UTAUT, relevant studies have also created new models, such as RAM (Turja et al., 2019), HRCAM (Bröhl et al., 2019), an AIDUT (Lin et al., 2019).…”