Assessing the effects of building social intelligence in a robotic interface for the home

Ruyter, Boris de; Privender, Saini; Markopoulos, Panos; Breemen, Albert J. J. M. van

doi:10.1016/j.intcom.2005.03.003

Cited by 123 publications

(107 citation statements)

References 15 publications

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“…Trust The concept of Trust not only emerged from our own findings [29], it is also found in studies concerning robot technology [31,49,50] and human-robot interaction [25,30,51]. To incorporate Trust into the model, two items were developed to measure the trust the user has in the robot and to what extent the user intends to comply to the robot's advice and on the nature of human-robot interaction.…”

Section: Additional Constructsmentioning

confidence: 90%

“…Gender, Age, Experience and Voluntariness of use were found to be the main moderating influences. The model has been applied by De Ruyter et al [30] to investigate the acceptance of a social robot (the iCat). These studies found that participants judged an extravert robot (more expressive in voice and facial expressions) to be more socially intelligent and they were more likely to accept the expressive robot compared with the robot in an introvert condition.…”

Section: Utaut and The Acceptance Of Social Agentsmentioning

confidence: 99%

See 1 more Smart Citation

Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model

Heerink

Kröse

Evers

et al. 2010

Int J of Soc Robotics

858

760

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This paper proposes a model of technology acceptance that is specifically developed to test the acceptance of assistive social agents by elderly users. The research in this paper develops and tests an adaptation and theoretical extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) by explaining intent to use not only in terms of variables related to functional evaluation like perceived usefulness and perceived ease of use, but also variables that relate to social interaction. The new model was tested using controlled experiment and longitudinal data collected regarding three different social agents at elderly care facilities and at the homes of older adults. The model was strongly supported accounting for 59-79% of the variance in usage intentions and 49-59% of the variance in actual use. These findings contribute to our understanding of how elderly users accept assistive social agents.

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Section: Additional Constructsmentioning

confidence: 90%

Section: Utaut and The Acceptance Of Social Agentsmentioning

confidence: 99%

Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model

Heerink

Kröse

Evers

et al. 2010

Int J of Soc Robotics

858

760

View full text Add to dashboard Cite

show abstract

“…In this study, our objective was to evaluate the participant perception, attitude and intention of use a SAR platform in their profession. To this end we adopted the UTAUT model as proposed by Heerink et al [54], which has been widely used for the evaluation of SAR platforms and has been found to be highly reliable in several previous studies (among others: [25,[55][56][57][58]). …”

Section: Technology Acceptance Models and Hypothesesmentioning

confidence: 99%

Robots in Education and Care of Children with Developmental Disabilities: A Study on Acceptance by Experienced and Future Professionals

Conti

Nuovo

Buono

et al. 2016

Int J of Soc Robotics

136

105

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Research in the area of robotics has made available numerous possibilities for further innovation in the education of children, especially in the rehabilitation of those with learning difficulties and/or intellectual disabilities. Despite the scientific evidence, there is still a strong scepticism against the use of robots in the fields of education and care of people. Here we present a study on the acceptance of robots by experienced practitioners (specialized in the treatment of intellectual disabilities) and university students in psychology and education sciences (as future professionals). The aim is to examine the factors, through the Unified Theory of Acceptance and Use of Technology (UTAUT) model, that may influence the decision to use a robot as an instrument in the practice. The overall results confirm the applicability of the model in the context of education and care of children, and suggest a positive attitude towards the use of the robot. The comparison highlights some scepticism among the practitioners, who perceive the robot as an expensive and limited tool, while students show a positive perception and a significantly higher willingness to use the robot. From this experience, we formulate the hypothesis that robots may be accepted if more integrated with standard rehabilitation protocols in a way that benefits can outweigh the costs.

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“…This requires very rich, privacy-sensitive models of users that go beyond simple habits and preferences, and include aspects of their personality, their health status, the social network and context, etc. It requires embedding ambient intelligence in the social context of a person, a notion that extends the definition of ambient intelligence to cover also aspects of social intelligence [18].…”

Section: Customization and Tailoring Adjusts Messages And Content To mentioning

confidence: 99%

The Persuasiveness of Ambient Intelligence

Aarts¹,

Markopoulos

Ruyter³

2007

Security, Privacy, and Trust in Modern Data Management

Self Cite

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Summary. Ambient intelligence (AmI) is a novel concept for embedded computing that builds on the large-scale integration of electronic devices into peoples' surroundings and the ubiquitous availability of digital information to the users of such environments. The concept however is not only concerned with the integration of computing in the background but, as a direct result of the disappearing computer and the corresponding interaction technologies, it calls for novel means of control that support the natural and intelligent use of such smart environments, emphasizing predominantly social aspects. As the familiar box-like devices are replaced by hidden functions embedded in the surroundings, the classical meaning and implication of security and trust needs to be revisited in the context of ambient intelligence. In this chapter, we briefly revisit the foundations of the AmI vision by addressing the role of AmIware, which refers to the basic and enabling AmI technologies, and by presenting some basic definitions of ambient intelligence. Next we discuss the meaning and role of persuasion on the basis of models and theories for motivation originating from cognitive science. Notions such as compliance and ambient journaling are used to develop an understanding of the concept of ambient persuasion. We also address the ethics of ambient intelligence from the point of view of a number of critical factors such as trust and faith, crossing boundaries, and changing realities. The chapter concludes with a summary of findings and some final remarks. IntroductionRecent technological advances have enabled the miniaturization of embedded hardware thus facilitating the large-scale integration of electronic devices into peoples' backgrounds. In addition, novel interaction concepts have been developed that support the natural and intelligent use of such systems, emphasizing the social aspects of the technology embedding. The resulting computing paradigm, which is called ambient intelligence (AmI), provides users with new means to increase their productivity, increase their well-being, or enhance their expressiveness [1].

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Assessing the effects of building social intelligence in a robotic interface for the home

Cited by 123 publications

References 15 publications

Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model

Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model

Robots in Education and Care of Children with Developmental Disabilities: A Study on Acceptance by Experienced and Future Professionals

The Persuasiveness of Ambient Intelligence

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