Measuring the Perceived Social Intelligence of Robots

Author:

Barchard Kimberly A.1,Lapping-Carr Leiszle1,Westfall R. Shane1,Fink-Armold Andrea1,Banisetty Santosh Balajee2,Feil-Seifer David2

Affiliation:

1. Department of Psychology, University of Nevada Las Vegas, Las Vegas, NV, USA

2. Department of Computer Science 8 Engineering, University of Nevada Reno, Reno, NV, USA

Abstract

Robotic social intelligence is increasingly important. However, measures of human social intelligence omit basic skills, and robot-specific scales do not focus on social intelligence. We combined human robot interaction concepts of beliefs, desires, and intentions with psychology concepts of behaviors, cognitions, and emotions to create 20 Perceived Social Intelligence (PSI) Scales to comprehensively measure perceptions of robots with a wide range of embodiments and behaviors. Participants rated humanoid and non-humanoid robots interacting with people in five videos. Each scale had one factor and high internal consistency, indicating each measures a coherent construct. Scales capturing perceived social information processing skills (appearing to recognize, adapt to, and predict behaviors, cognitions, and emotions) and scales capturing perceived skills for identifying people (appearing to identify humans, individuals, and groups) correlated strongly with social competence and constituted the Mind and Behavior factors. Social presentation scales (appearing friendly, caring, helpful, trustworthy, and not rude, conceited, or hostile) relate more to Social Response to Robots Scales and Godspeed Indices, form a separate factor, and predict positive feelings about robots and wanting social interaction with them. For a comprehensive measure, researchers can use all PSI 20 scales for free. Alternatively, they can select the most relevant scales for their projects.

Funder

National Institute for Health

Nevada Space Grant Consortium

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

Reference67 articles.

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