Anthropomorphism is a common phenomenon when people attribute human characteristics to non-human objects. It plays an important role in acceptance of robots in natural human environments. Various studies in the field of Human-Robot Interaction (HRI) show that there are various factors that can affect the extent to which a robot is anthropomorphized. However, our knowledge of this phenomenon is segmented, as there is a lack of a coherent model of anthropomorphism that could consistently explain these findings. A robot should be able to adjust its level of anthropomorphism to a level that can optimize its task performance. In order to do that, robotic system designers must know which characteristics affect the perception of robots' anthropomorphism. Currently, existing models of anthropomorphism emphasize the importance of the context and perceiver in this phenomenon, but provide little guidelines regarding the factors of a perceived object that are affecting it.

The proposed reverse process to anthropomorphization is known as dehumanization. In the recent years research in social psychology has found which characteristics are deprived from people who are perceived as subhumans or are objectified. Furthermore, the process of dehumanization is two dimensional rather than unidimensional. This thesis discusses a model of anthropomorphism that uses characteristics from both dimensions of dehumanization and those relating to robots' physical appearance to affect the anthropomorphism of a robot. Furthermore, involvement of implicit and explicit processes in anthropomorphization are discussed.

In this thesis I present five empirical studies that were conducted to explore anthropomorphism in HRI. Chapter 3 discusses development and validation of a cognitive measurement of humanlikeness using the magnitude of the inversion effect. Although robot stimuli were processed more similarly to human stimuli rather than objects and induced the inversion effect, the results suggest that this measure has limited potential for measuring humanlikeness due to the low variance that it can explain. The second experiment, presented in Chapter 4 explored the involvement of Type I and Type II processing in anthropomorphism. The main findings of this study suggest that anthropomorphism is not a result of a dual-process and self-reports have a potential to be suitable measurement tools of anthropomorphism.

Chapter 5 presents the first empirical work on the dimensionality of anthropomorphism. Only perceived emotionality of a robot, but not its perceived intelligence, affects its anthropomorphization. This finding is further supported by a follow up experiment, presented in Chapter 6, that shows that Human Uniqueness dimension is less relevant for a robot's anthropomorphiazability than Human Nature (HN) dimension. Intentionality of a robot did not result in its higher anthropomorphizability. Furthermore, this experiment showed that humanlike appearance of a robot is not linearly related with its anthropomorphism during HRI. The lack of linear relationship between humanlike appearance and attribution of HN traits to a robot during HRI is further supported by the study described in Chapter 7. This last experiment shows also that another factor of HN, sociability, affects the extent to which a robot is anthropomorphized and therefore the relevance of HN dimension in the process of anthropomorphization.

This thesis elaborates on the process of anthropomorphism as an important factor affecting HRI. Without fully understanding the process itself and what factors make robots to be anthropomorphized it is hard to measure the impact of anthropomorphism on HRI. It is hoped that understanding anthropomorphism in HRI will make it possible to design interactions in a way that optimizes the benefits of that phenomenon for an interaction.