We evaluated the seal-like robot PARO in the context of multi-sensory behavioral therapy in a local nursing home. Participants were 10 elderly nursing home residents with varying levels of dementia. We report three principle findings from our observations of interactions between the residents, PARO, and a therapist during seven weekly therapy sessions. Firstly, we show PARO provides indirect benefits for users by increasing their activity in particular modalities of social interaction, including visual, verbal, and physical interaction, which vary between primary and non-primary interactors. Secondly, PARO's positive effects on older adults' activity levels show steady growth over the duration of our study, suggesting they are not due to short-term "novelty effects." Finally, we show a variety of ways in which individual participants interacted with PARO and relate this to the "interpretive flexibility" of its design.
This paper analyzes scientists' discourses on the social impacts and acceptability of robotics, based on data collected through participant observation and interviews with robotics researchers in the US and Japan. It shows that a linear, technologically determinist, view of the interaction between robots and society is dominant in the field; in this narrative the social impact of robotic technologies derives mostly from their technological capabilities and the aim is for society to accept and adapt to technological innovations. The framework of mutual shaping and co-production, which explores the dynamic interaction between robotics and society, is proposed as an alternative perspective on the dynamics between society and technology and a framework for envisioning and evaluating social robots. This approach focuses on analyzing how social and cultural factors influence the way technologies are designed, used, and evaluated as well as how technologies affect our construction of social values and meanings. Finally, the paper describes a range of methodologies of contextually grounded and participatory design that fit the mutual shaping framework and support a socially robust understanding of technological development that enables the participation of multiple stakeholders and disciplines.
What is covered in this chapter:• The role of nonverbal communication in interactions between people-how communication is enhanced by facial expressions, hand gestures, body posture, and sounds; • The importance of interpreting, using, and responding to nonverbal cues in the appropriate way, both to successful humanrobot interactions and to generate a positive perception of robots; • Nonverbal communication channels that are unique to robots, as well as channels that replicate those commonly used by humans; • How robotic sounds, lights, and colors or physical gestures with arms, legs, tails, ears, and other body parts can be effective for communicating with people. 81
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