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Chapter 2


                              UNDERSTANDING SOCIAL INTELLIGENCE





                              Per Persson , Jarmo Laaksolahti and Peter L¨ onnqvist

                               Swedish Institute of Computer Science, Kista, Sweden, Department of Computer and Systems
                              Sciences, Stockholm University and Royal Institute of Technology

                              Abstract   Believable social interaction is not only about agents that look right but also do
                                         the right thing. To achieve this we must consider the everyday knowledge and
                                         expectations by which users make sense of real, fictive or artificial social be-
                                         ings. This folk-theoretical understanding of other social beings involves several,
                                         rather independent, levels such as expectations on behaviour, expectations on
                                         primitive psychology, models of folk-psychology, understanding of traits, social
                                         roles and empathy. Implications for Socially Intelligent Agents (SIA) research
                                         are discussed.


                              1.     Introduction
                                Agent technology refers to a set of software approaches that are shifting
                              users’ view of information technology from tools to actors. Tools react only
                              when interacted with, while agents act autonomously and proactively, some-
                              times outside the user’s awareness. With an increasing number of autonomous
                              agents and robots making their way into aspects of our everyday life, users
                              are encouraged to understand them in terms of human behaviour and inten-
                              tionality. Reeves and Nass [5] have shown that people relate to computers -
                              as well as other types of media - as if they were ’real’, e.g., by being polite
                              to computers. However, some systems seem to succeed better than others in
                              encouraging such anthropomorphic attributions, creating a more coherent and
                              transparent experience [20]. What are the reasons for this? What encourages
                              users to understand a system in terms of human intentionality, emotion and cog-
                              nition? What shapes users’ experiences of this kind? Software agent research
                              often focuses on the graphical representation of agents. Synchronisation of lip
                              movements and speech, gestures and torso movements as well as the quality of
                              the graphical output itself are questions that have been investigated [6] [14]. In
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