Age Difference in Perceived Ease of Use, Curiosity, and Implicit Negative Attitude toward Robots

Robot occupations affect the categorization border between human and robot faces

The Uncanny Valley hypothesis implies that people perceive a subjective border between human and robot faces. The robot-human border refers to the level of human-like features that distinguishes humans from robots. However, whether people's perceived anthropomorphism and robot-human borders are consistent across different robot occupations remains to be explored. This study examined the robot-human border by analyzing the human photo proportion represented by the point of subjective equality in three image classification tasks. Stimulus images were generated by morphing a robot face photo and one each of four human photos in systematically changed proportions. Participants classified these morphed images in three different robot occupational conditions to explore the effect of changing robot jobs on the robot-human border. The results indicated that robot occupation and participant age and gender influenced people's perceived anthropomorphism of robots. These can be explained by the implicit link between robot job and appearance, especially in a stereotyped context. The study suggests that giving an expected appearance to a robot may reproduce and strengthen a stereotype that associates a certain appearance with a certain job.

The Effects of Social Presence and Familiarity on Children-Robot Interactions

In children-robot interactions, an impression of a robot's "social presence" (i.e., an interactive agent that feels like a person) links positively to an improved relationship with the robot. However, building relationships takes many exposures, and there is an intellectual gap in how social presence and familiarity collaborate in modulating children-robot relationships. We investigated whether social presence altered over time, how repeated exposure and social presence affected rapport, and how social presence would modulate children's attitudes toward the robot. Fourteen children (four female, age = 10.79 ± 1.12) interacted with a companion robot for four days in spontaneous interactions. The findings revealed that children who perceived the robot as having a higher social presence developed a stronger rapport than those who perceived a lower social presence. However, repeated encounters did not change the children's perceptions of the robot's social presence. Children rated higher rapport after repeated interactions regardless of social presence levels. This suggests that while a higher social presence initially elevated the positive relationship between children and the robot, it was the repeated interactions that continued solidifying the rapport. Additionally, children who perceived a higher social presence from the robot felt less relational uneasiness about their relationship with robots. These findings highlight the importance of robots' social presence and familiarity in promoting positive relationships in children-robot interaction.

A Cross-Cultural Comparison on Implicit and Explicit Attitudes Towards Artificial Agents

Historically, there has been a great deal of confusion in the literature regarding cross-cultural differences in attitudes towards artificial agents and preferences for their physical appearance. Previous studies have almost exclusively assessed attitudes using self-report measures (i.e., questionnaires). In the present study, we sought to expand our knowledge on the influence of cultural background on explicit and implicit attitudes towards robots and avatars. Using the Negative Attitudes Towards Robots Scale and the Implicit Association Test in a Japanese and Dutch sample, we investigated the effect of culture and robots' body types on explicit and implicit attitudes across two experiments (total n = 669). Partly overlapping with our hypothesis, we found that Japanese individuals had a more positive explicit attitude towards robots compared to Dutch individuals, but no evidence of such a difference was found at the implicit level. As predicted, the implicit preference towards humans was moderate in both cultural groups, but in contrast to what we expected, neither culture nor robot embodiment influenced this preference. These results suggest that only at the explicit but not implicit level, cultural differences appear in attitudes towards robots.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12369-022-00917-7.

Correlation Between Learning Motivation and Satisfaction in Synchronous On-the-Job Online Training in the Public Sector

Non-governmental organizations often regard expanding revenue and reducing costs as standard procedures to achieve corporate sustainability, while at the same time considering human resources as important assets. Government agencies have greater flexibility in staffing, and their human resource strategies for employee education and training often use organizational learning to develop operational performance. Training is regarded as a panacea for corporate sustainability and channels have been established to support employees' learning. Curriculum development of synchronous online learning is an approach that requires further investigation. We distributed 360 questionnaires to supervisors and employees of the Taipei City Government, Taiwan. A total of 268 valid copies were retrieved, giving a response rate of 74%. The study results are expected to help public sector employers enhance employee cohesiveness and generate more operational team spirit.

Should my robot know what's best for me? Human–robot interaction between user experience and ethical design

To integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles.

Are Preferences Useful for Better Assistance?

Assistive Robots have an inherent need of adapting to the user they are assisting. This is crucial for the correct development of the task, user safety, and comfort. However, adaptation can be performed in several manners. We believe user preferences are key to this adaptation. In this article, we evaluate the use of preferences for Physically Assistive Robotics tasks in a Human-Robot Interaction user evaluation. Three assistive tasks have been implemented consisting of assisted feeding, shoe-fitting, and jacket dressing, where the robot performs each task in a different manner based on user preferences. We assess the ability of the users to determine which execution of the task used their chosen preferences (if any). The obtained results show that most of the users were able to successfully guess the cases where their preferences were used even when they had not seen the task before. We also observe that their satisfaction with the task increases when the chosen preferences are employed. Finally, we also analyze the user’s opinions regarding assistive tasks and preferences, showing promising expectations as to the benefits of adapting the robot behavior to the user through preferences.

Identifying Mild Cognitive Impairment by Using Human-Robot Interactions

BACKGROUND

Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults.

OBJECTIVE

To overcome methodological drawbacks of previous studies (e.g., use of potentially imprecise screening tools that fail to include patients with MCI), this study investigated the feasibility of assessing multiple cognitive functions in older adults with and without MCI by using a social robot.

METHODS

This study included 33 older adults with or without MCI and 33 healthy young adults. We examined the utility of five robotic cognitive tests focused on language, episodic memory, prospective memory, and aspects of executive function to classify age-associated cognitive changes versus MCI. Standardized neuropsychological tests were collected to validate robotic test performance.

RESULTS

The assessment was well received by all participants. Robotic tests assessing delayed episodic memory, prospective memory, and aspects of executive function were optimal for differentiating between older adults with and without MCI, whereas the global cognitive test (i.e., Mini-Mental State Examination) failed to capture such subtle cognitive differences among older adults. Furthermore, robot-administered tests demonstrated sound ability to predict the results of standardized cognitive tests, even after adjustment for demographic variables and global cognitive status.

CONCLUSION

Overall, our results suggest the human-robot interaction approach is feasible for MCI identification. Incorporating additional cognitive test measures might improve the stability and reliability of such robot-assisted MCI diagnoses.

Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19

The evolution of Artificial Intelligence (AI) has revolutionized many aspects of human life, including healthcare. Amidst the Covid-19 pandemic, AI-enabled smartwatches are being used to help users to self-monitor and self-manage their health. Using a framework based on Stimulus-Organism-Response (S-O-R) theory, this present study aimed to explore the use of AI-enabled smartwatches for health purposes, in particular the effects of product quality, service quality, perceived convenience, and perceived ease of use on user experience, trust and user satisfaction. Based on a purposive survey sample of 486 smartphone users in Bangladesh, data collected was analyzed using SPSS software for elementary analyses and PLS-SEM for hypotheses testing. The findings showed that the predictors, namely product quality, service quality, perceived convenience, and perceived ease of use, significantly affected user experience and trust. Similarly, user experience and trust were influential on user satisfaction and played partial mediating roles between predictors and user satisfaction. Besides, gender and age moderate the relationships of experience and trust with customer satisfaction. These findings support the S-O-R theoretical framework and have practical implications for brand and marketing managers of smartwatches in developing product features and understanding users' attitudes and behaviours.

Social Robots for Evaluating Attention State in Older Adults

Sustained attention is essential for older adults to maintain an active lifestyle, and the deficiency of this function is often associated with health-related risks such as falling and frailty. The present study examined whether the well-established age-effect on reducing mind-wandering, the drift to internal thoughts that are seen to be detrimental to attentional control, could be replicated by using a robotic experimenter for older adults who are not as familiar with online technologies. A total of 28 younger and 22 older adults performed a Sustained Attention to Response Task (SART) by answering thought probes regarding their attention states and providing confidence ratings for their own task performances. The indices from the modified SART suggested a well-documented conservative response strategy endorsed by older adults, which were represented by slower responses and increased omission errors. Moreover, the slower responses and increased omissions were found to be associated with less self-reported mind-wandering, thus showing consistency with their higher subjective ratings of attentional control. Overall, this study demonstrates the potential of constructing age-related cognitive profiles with attention evaluation instruction based on a social companion robot for older adults at home.

Remote HRI: a Methodology for Maintaining COVID-19 Physical Distancing and Human Interaction Requirements in HRI Studies

Observing how humans and robots interact is an integral part of understanding how they can effectively coexist. This ability to undertake these observations was taken for granted before the COVID-19 pandemic restricted the possibilities of performing HRI study-based interactions. We explore the problem of how HRI research can occur in a setting where physical separation is the most reliable way of preventing disease transmission. We present the results of an exploratory experiment that suggests Remote-HRI (R-HRI) studies may be a viable alternative to traditional face-to-face HRI studies. An R-HRI study minimizes or eliminates in-person interaction between the experimenter and the participant and implements a new protocol for interacting with the robot to minimize physical contact. Our results showed that participants interacting with the robot remotely experienced a higher cognitive workload, which may be due to minor cultural and technical factors. Importantly, however, we also found that whether participants interacted with the robot in-person (but socially distanced) or remotely over a network, their experience, perception of, and attitude towards the robot were unaffected.

Age Differences in State Curiosity: Examining the Role of Personal Relevance

OBJECTIVES

Curiosity, or the desire for novel information and/or experience, is associated with improved well-being and more informed decisions, which has implications on older adults' (OAs') adoption of novel technologies. There have been suggestions that curiosity tends to decline with age. However, it was rarely studied under specific contexts, and there were relatively limited attempts to enhance OAs' curiosity. Under the theoretical framework of selective engagement theory, we examined age differences of curiosity in the context of learning a novel technology and investigated the moderating role of personal relevance.

METHOD

This study utilized a pretest-posttest experimental design with a total of 50 younger adults (YAs) and 50 OAs from Hong Kong to measure their trait curiosity, perceived personal relevance, and state curiosity toward robots after interacting with a robot.

RESULTS

OAs showed significantly lower trait curiosity than YAs, but OAs showed a higher level of state curiosity toward a robot than YAs when they perceived an increase in personal relevance after interacting with the robot.

CONCLUSION

Findings replicated previous findings that trait curiosity declined with age, but they also illustrated the distinctions between trait and state curiosity in the context of aging and highlighted the potential role of personal relevance in enhancing curiosity of OAs.

Asynchronously Embedding Psychological Test Questions into Human–Robot Conversations for User Profiling

Psychological variables of a person (e.g., cognitive abilities, personality traits, emotional states, and preferences) are valuable information that can be utilized by social robots to offer personalized human–robot interaction. These variables are often latent and inferred indirectly from a third-person perspective based on an individual’s behavioral manifestations (e.g., facial emotion expressions), and hence the true values of inferred psychological variables remain unknown to a robot observer. Although earlier studies have employed robot-administered psychological tests to infer psychological variables based on an individual’s first-person responses, these tests were formally presented and could be tedious to some users. To leverage the validity and reliability of well-established psychological tests for user profiling with ease, the present study examined the possibility of asynchronously embedding psychological test questions into casual human–robot conversations. In our experiment using a big-five personality inventory, the verbal responses from users to these asynchronous test questions were then compared with the written responses to the same personality test. The personality measures estimated from the two approaches correlated strongly in a young adult population but only moderately in an older population. These findings demonstrate the validity of the proposed asynchronous method for psychological testing in human–agent interactions and suggest some caveats when this testing method is applied to older adults or other special populations.

Age-Related Differences in the Uncanny Valley Effect

BACKGROUND

Due to declining birthrates and an increasing aging population, shortage of the caregiving labor force has become a global issue. Among various efforts toward the solution, introducing robotic products for assistance could provide an effective way to help older adults in their daily lives. As previous studies have indicated that older adults' acceptance of robots is lower than that of younger adults, enhancing older adults' acceptance of robots is imperative. Because older adults' first impressions based on a robot's appearance might affect their acceptance of the robot, we investigated the uncanny valley effect (UVE) here. The UVE refers to the phenomenon that people rate robots more positively as robots become more humanlike, but only up to a certain point; as robots approach a near-perfect similarity to human appearance, likeability drops and forms the uncanny valley. Nevertheless, evidence for the UVE came mainly from younger adults.

OBJECTIVE

The present study aimed to examine whether the UVE varies across different age groups and whether a robot's appearance would affect participants' acceptance of the robot's service or companionship.

METHODS

An online questionnaire study was conducted with 255 participants, including younger (n = 77, age 18-39 years), middle-aged (n = 87, age 40-59 years), and older (n = 91, age 60-87 years) adults. Participants were asked to view each picture in a set selected from a total of 83 robot pictures and evaluate their impressions of each robot and the intention of use regarding robot function as a service provider or a companion.

RESULTS

The UVE was found in younger and middle-aged adults; however, older adults did not show the UVE. Older adults preferred humanlike over non-humanlike robots, regardless of robot function.

CONCLUSION

The design of assistive robots should take the UVE into consideration by customizing robot appearance based on the age group of the intended user.