The Effect of Interaction and Design Participation on Teenagers’ Attitudes towards Social Robots

Björling, Elin A.; Xu, Wendy; Cabrera, María Eugenia; Çakmak, Maya

doi:10.1109/ro-man46459.2019.8956427

Cited by 12 publications

(4 citation statements)

References 33 publications

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“…These included societal implications (environmental impact, over-reliance on technological solutions to mental health problems), commercial considerations (surveillance and data security, harmful advertising), and personal experiences (judgment from others for using a robot, feeling responsible for the robot's feelings, making the robot angry, feeling rejected by the robot). These themes are consistent with those of other user groups, including older adults [14,15,24,41,[48][49][50]. However, children and families also pointed to the unique advantages of a robots as responsive smart objects, particularly as a non-judgmental source of social support and pet-like comfort objects.…”

Section: Ethicssupporting

confidence: 79%

“A Safe Space for Sharing Feelings”: Perspectives of Children with Lived Experiences of Anxiety on Social Robots

Dosso,

Kailley,

Martin

et al. 2023

MTI

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Social robots have the potential to support health and quality of life for children experiencing anxiety. We engaged families with lived experiences of pediatric anxiety in social robot development to explore desired design features, application areas, and emotion functionalities of social robots in anxiety care. We conducted 10 online co-creation workshops with (1) children with anxiety aged 7–13 (n = 24) with their family members (n = 20), and (2) youth with anxiety aged 14–18 (n = 12). Workshop participation included a validated robot expectations scale, anonymous polls, and discussion. Transcripts and text responses were subjected to content analysis. A lived experience expert group provided feedback throughout the research. Participants desired a pet-like robot with a soft texture, expressive eyes, and emotion detection to support activities of daily living. Specific anxiety-related applications included breathing exercises, managing distressing thoughts, and encouragement. Emotional alignment, the design of a robot’s emotional display, and the emotional impacts of an interaction were discussed. Privacy and the replacement of human interaction were concerns. We identify pediatric anxiety-specific design features, applications, and affective considerations for existing and future social robots. Our findings highlight the need for customizability and robust emotional functionality in social robot technologies intended to support the health and care of children living with anxiety.

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Section: Ethicssupporting

confidence: 79%

“A Safe Space for Sharing Feelings”: Perspectives of Children with Lived Experiences of Anxiety on Social Robots

Dosso,

Kailley,

Martin

et al. 2023

MTI

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“…We explored need-finding through interviews with experts in HRI to collect untapped opportunities for social robots [58,59]. Need-finding is a methodological tool for both grounding and inspiring research and allows us to quickly enter a user's world, casting the user as an expert who can teach us the meaning of a given task, objects, or technology.…”

Section: Methods and Proceduresmentioning

confidence: 99%

“…The EMAR V4 with flexible software for customized teenager-robot interactions, does not have a fully customizable body but rather a hard shell that does not enable individual personalization [60]. OPSORO is an inexpensive and customizable robot but lacks robustness to be used across different use cases [58], [59].Additionally, many robot kits developed for education are made with arts and crafts materials not allowing a robust robot that can be deployed in real contexts of use. There is an almost unlimited design space for robots to have different colors, heights, materials, shapes, and forms.…”

Section: Customizable Technologiesmentioning

confidence: 99%

FLEXI: A Robust and Flexible Social Robot Embodiment Kit

Alves‐Oliveira

Bavier

Malandkar

et al. 2022

Designing Interactive Systems Conference

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The social robotics market is appealing yet challenging. Though social robots are built few remain on the market for long. Many reasons account for their short lifespan with costs and contextspecificity ranking high amount them. In this work, we designed, fabricated, and developed FLEXI, a social robot embodiment kit that enabled unlimited customization, making it applicable for a broad range of use cases. The hardware and software of FLEXI were entirely developed by this research team from scratch. FLEXI includes a rich set of materials and attachment pieces to allow for a diverse range of hardware customizations that ensure the embodiment is appropriate for specific customer/researcher projects. It also includes an open-source end-user programming interface to lower the barrier of robotics access to interdisciplinary teams that populate the field of Human-Robot Interaction. We present an iterative development of this cost-effective kit through the lenses of case studies, conceptual research, and soft deployment of FLEXI in three application scenarios: community-support, mental health, and education. Additionally, we provide in openaccess the full list of materials and a tutorial to fabricate FLEXI, making it accessible to any maker space, research lab, or workshop space interested in working with or learning about social robots.

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“…The negative attitude towards robot scale (NARS) and robot anxiety scale (RAS) [10] have been used to quantify human workers' cognitive strain, whereas facial expressions have also been monitored, using cameras, as behavioural stress indicators [1]. Another 10-item questionnaire, the perceived stress scale (PSS-10), was employed by Björling et al (2019) to evaluate the perceived stress of a teen during robot interaction [11]. Rossato et al (2021) assessed the subjective experience of senior and younger workers in HRC using the technology acceptance model (TAM) and NASA-TLX for measuring a user's acceptance of technology and cognitive task load, respectively [12].…”

Section: Introductionmentioning

confidence: 99%

Multimodal Assessment of Cognitive Workload Using Neural, Subjective and Behavioural Measures in Smart Factory Settings

Zakeri,

Arif,

Omurtag

et al. 2023

Sensors

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Collaborative robots (cobots) have largely replaced conventional industrial robots in today’s workplaces, particularly in manufacturing setups, due to their improved performance and intelligent design. In the framework of Industry 5.0, humans are working alongside cobots to accomplish the required level of automation. However, human–robot interaction has brought up concerns regarding human factors (HF) and ergonomics. A human worker may experience cognitive stress as a result of cobots’ irresponsive nature in unpredictably occurring situations, which adversely affects productivity. Therefore, there is a necessity to measure stress to enhance a human worker’s performance in a human–robot collaborative environment. In this study, factory workers’ mental workload was assessed using physiological, behavioural, and subjective measures. Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals were collected to acquire brain signals and track hemodynamic activity, respectively. The effect of task complexity, cobot movement speed, and cobot payload capacity on the mental stress of a human worker were observed for a task designed in the context of a smart factory. Task complexity and cobot speed proved to be more impactful. As physiological measures are unbiased and more authentic means to estimate stress, eventually they may replace the other conventional measures if they prove to correlate with the results of traditional ones. Here, regression and artificial neural networks (ANN) were utilised to determine the correlation between physiological data and subjective and behavioural measures. Regression performed better for most of the targets and the best correlation (rsq-adj = 0.654146) was achieved for predicting missed beeps, a behavioural measure, using a combination of multiple EEG and fNIRS predictors. The k-nearest neighbours (KNN) algorithm was used to evaluate the accuracy of correlation between traditional measures and physiological variables, with the highest accuracy of 77.8% achieved for missed beeps as the target. Results show that physiological measures can be more insightful and have the tendency to replace other biased parameters.

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The Effect of Interaction and Design Participation on Teenagers’ Attitudes towards Social Robots

Cited by 12 publications

References 33 publications

“A Safe Space for Sharing Feelings”: Perspectives of Children with Lived Experiences of Anxiety on Social Robots

“A Safe Space for Sharing Feelings”: Perspectives of Children with Lived Experiences of Anxiety on Social Robots

FLEXI: A Robust and Flexible Social Robot Embodiment Kit

Multimodal Assessment of Cognitive Workload Using Neural, Subjective and Behavioural Measures in Smart Factory Settings

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