Robots that embody humanlike features might someday provide social and informational services such as storytelling, educational assistance, companionship using complex, adaptive real-world interactions. For these systems to offer such benefits, designers need to have a better understanding of people’s expectations of these systems and how these expectations might be met by carefully designing appropriate social behaviors that support humanlike features. In the first half of this talk, I will present results from an ethnographic study of a hospital delivery robot—particularly on people’s expectations of and responses to the robot and how they adapted the robot into their workflow. In the second half of the talk, I will draw on some of the findings from this study and present an integrated, interdisciplinary approach for designing social behavior for humanlike robots. I will present a series of empirical studies that demonstrate how this approach might be used to design social gaze behaviors for humanlike robots and how participants show social and cognitive improvements—particularly, better recall of information, more conversational participation, and stronger rapport and attribution of intentionality—led by theoretically based manipulations in the designed gaze behavior.
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|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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