We take a fresh look at emotion recognition in autistic children, by testing their recognition of three different emotions (happy, sad, and surprise). The interest in selecting these is that whereas the first two are typical “simple” emotions (caused by situations), the third is typically a “cognitive” emotion (caused by beliefs). Because subjects with autism have clear difficulties in understanding beliefs, we predicted they would show more difficulty in recognising surprise. In contrast, as they have no difficulty in understanding situations (...) as causes of emotion, we predicted they would not show deficits in recognising happy and sad. These predictions were borne out, in a comparison with a group of normal children and in a group of subjects with mental handicap. This result shows the importance of fine-grain analysis in emotion-recognition tasks, and is discussed in relation to affective and theory of mind models of autism. (shrink)

In this paper, we move toward offering psychological benchmarks to measure success in building increasingly humanlike robots. By psychological benchmarks we mean categories of interaction that capture conceptually fundamental aspects of human life, specified abstractly enough to resist their identity as a mere psychological instrument, but capable of being translated into testable empirical propositions. Nine possible benchmarks are considered: autonomy, imitation, intrinsic moral value, moral accountability, privacy, reciprocity, conventionality, creativity, and authenticity of relation. Finally, we discuss how getting the right (...) group of benchmarks in human–robot interaction will, in future years, help inform on the foundational question of what constitutes essential features of being human. (shrink)

Anthropomorphism is a phenomenon that describes the human tendency to see human-like shapes in the environment. It has considerable consequences for people’s choices and beliefs. With the increased presence of robots, it is important to investigate the optimal design for this tech- nology. In this paper we discuss the potential benefits and challenges of building anthropomorphic robots, from both a philosophical perspective and from the viewpoint of empir- ical research in the fields of human–robot interaction and social psychology. We believe (...) that this broad investigation of anthropomorphism will not only help us to understand the phenomenon better, but can also indicate solutions for facil- itating the integration of human-like machines in the real world. (shrink)

Darwin discusses why different muscles are brought into action under different emotions and how particular animals have adapted for association with man.

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to inter-act with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots (...) were able to adequately demonstrate this, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye tracking, electroencephalography (EEG), or functional near-infrared spectroscopy (fNIRS) embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive mechanisms involved in human-human interactions, and high-light the importance of perceiving others as intentional agents to activate these brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles. (shrink)