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Automation in healthcare
Published in Eduard Fosch-Villaronga, Robots, Healthcare, and the Law, 2019
Hegel et al. (2009) summarized a number of different positions by saying that a robot with a social interface is a social robot. Darling (2016) explained that a social robot is an embodied object with a defined degree of autonomous behaviour that is specifically designed to interact with humans on a social level and respond to mistreatment in a lifelike way. The last part of the definition refers to the workshop that she carried out at Massachusetts Institute of Technology (MIT) with the abuse of the robotic dinosaur Pleo. This might not be applicable generally, because the robot might respond in a lifelike manner in other situations, not only in mistreatment cases. De Graaf, Allouch, & Van Dijk (2015) suggested that what makes a robot social is, in reality, the two-way interaction: social robots express or understand thoughts or feelings, are socially aware, interact unpredictably or spontaneously, and provide a sense of companionship or mutual respect. Still, I agree with the idea that the emotional bonds established between humans and social robots are unidirectional, not reciprocal or bidirectional (Scheutz, 2014).
Robots and Robot Capabilities
Published in Aimee Van Wynsberghe, Healthcare Robots, 2016
Social robots may be used for enjoyment, learning, therapy or for personal growth. Philips ICat, for example, is used to understand human-robot interactions in order to program future robots for greater user acceptability. In therapeutic instances, social robots are used to interact with children with autism. The work of Dautenhahn shows how social robots can be used as a tool for teaching children skills of interaction. Robots with social capabilities are also used as diet assists; individuals wanting to lose weight use the robot to help motivate, encourage and keep track of progress or lack thereof. The goal is to foster a meaningful bond between the human and the robot in order to achieve weight loss goals with greater success.
Quest for the sentient robot
Published in Arkapravo Bhaumik, From AI to Robotics, 2018
Kismet, ROMAN, PR2 and Pepper are state-of-the-art social robots. The down side to this is that the emotion elicited by them is at best sophisticated imitations, developed by observing the human subject. These robots do not feel happiness, remorse, pain, or any other psychological effects — typifying zombies lacking a soul, therefore with no consciousness, free will nor sentience. Developing moral agencies into and also as an extention of such social robots will require more of a deontic approach, developed for a narrow concern such as a carer robot nurse robot, companion/assistant robot, following a set of instructions, while being friendly5 to the human subjects. Other than this lacuna, these models take into consideration first degree effects such as mirroring from the facial expressions and voice of the human subject without any inward processing such as a decision process or associating information. Causality, as shown in Figure 9.8, is much more than first degree and the far reaching effects are often not fully discernible even to us human beings. An artificial being should not only respond to the first degree effects — that is, be self aware — but should be able to analyse and evaluate the far reaching consequences of its actions. To cite an example, consider a mobile robot assisting in medical surgery. Cutting open a patient would seem a harmful act, however the far reaching effects are with the intention of curing the patient. Therefore, such a robot will at least need to possess functional morality and thus a bottom-up approach to develop it or a developmental route, learning from experience and phased in over a long period of time.
Human-robot swarm interaction: coordinated role of human mind mindsets and robot group entitativity
Published in Behaviour & Information Technology, 2023
Social robots are designed to interact autonomously with people. Social interactions between humans and robots are becoming increasingly frequent in different domains, such as education, home care, and healthcare (Jha and Topol 2016; Taddeo and Floridi 2018). Robotic systems are transitioning from individual robots to swarm robots (Floreano and Lipson 2021), and the one-on-one human–robot interaction has expanded to the group level in recent years (Sebo et al. 2020). For instance, in role-play settings, a child or a group of children interacts with a group of robots to develop social emotional abilities (Leite et al. 2015, 2017). Since people are aware of the psychosocial implications of robot groups (Vollmer et al. 2018), the question of how people interact with robot groups has attracted more research attention in the fields of social robotics (Oliveira, Arriaga, and Paiva 2021) and social psychology (Abrams and der Pütten 2020; Smith, Šabanović, and Fraune 2021).
Artificial Intelligence Service Agents: Role of Parasocial Relationship
Published in Journal of Computer Information Systems, 2022
Nurhafihz Noor, Sally Rao Hill, Indrit Troshani
Consumers place primary value on AISA’s hedonic factor when the AISA is primarily designed to provide affective service.37 They are designed with varying purposes and play increasingly important roles such as supporting consumers in changing their behaviors,38 or assisting the elderly in their living environments.39 For instance, social robots such as Pepper are developed to converse with consumers and keep them company in aged care and schools.40 Pepper is also mainly classified as a physical AISA despite having virtual text displays that are used to interact with consumers.40 Physical representation can create relatively higher affective responses from users than virtual AISA.41 Thus, we expect that AISA that are mainly designed to meet the hedonic needs of consumers and that have a more physical representation are likely to evoke high affective responses from consumers, as shown in Figure 1.
Therapeutic use of the humanoid robot, Telenoid, with older adults: A critical interpretive synthesis review
Published in Assistive Technology, 2022
Wendy Moyle, Jenny Murfield, Katarzyna Lion
The world’s population is aging, and with it, we see unprecedented changes in the demographic profile of the global community that will necessitate changes in the provision of aged care (World Health Organization, 2018). An increasing proportion of adults aged 65 years or older will develop conditions associated with aging, including dementia, and more older adults will require some aspect of care, either within the community or a residential aged care facility (RACF). In addition, with families geographically dispersed and aged care workforce shortages anticipated (Sherman et al., 2013), there is an increased risk that older adults will receive care primarily focused on biomedical aspects of their health rather than psychosocial aspects. This may lead to reduced opportunities for meaningful social contact and communication. With loneliness and social isolation already a feature for many older adults living within the community and RACFs (Gardiner et al., 2020; Ong et al., 2016), this is an issue of concern, and research over the last decade has targeted its efforts at exploring the efficacy of various approaches in reducing social isolation and loneliness for older adults receiving care (Gardiner et al., 2018). One avenue of this work gaining traction is the use of social robots, and how these technologies can be used to augment in-person care to help provide meaningful activity, connection, and social wellbeing (Ibarra et al., 2020).