Ascribing mental states to non-human agents has been shown to increase their likeability and lead to better joint-task performance in human-robot interaction (HRI). However, it is currently unclear what physical features non-human agents need to possess in order to trigger mind attribution and whether different aspects of having a mind (e.g., feeling pain, being able to move) need different levels of human-likeness before they are readily ascribed to non-human agents. The current study addresses this issue by modeling how increasing the degree of human-like appearance (on a spectrum from mechanistic to humanoid to human) changes the likelihood by which mind is attributed towards non-human agents. We also test whether different internal states (e.g., being hungry, being alive) need different degrees of humanness before they are ascribed to non-human agents. The results suggest that the relationship between physical appearance and the degree to which mind is attributed to non-human agents is best described as a two-linear model with no change in mind attribution on the spectrum from mechanistic to humanoid robot, but a significant increase in mind attribution as soon as human features are included in the image. There seems to be a qualitative difference in the perception of mindful versus mindless agents given that increasing human-like appearance alone does not increase mind attribution until a certain threshold is reached, that is: agents need to be classified as having a mind first before the addition of more human-like features significantly increases the degree to which mind is attributed to that agent.

No abstract

Social robotics strives to create robots that enable social interactions similar to those experienced between two humans with the goal to increase performance in human-robot interaction (HRI). This is often achieved by designing robots that create an illusion of intentionality either through biologically inspired design or functional design in which the agent mirrors the cognitive or physical aspects of a human. The current study focused on functionally inspired design with the intent to learn what minimal features need to be included in the physical design of a social robot in order for it to appear as an intentional agent. Two groups of three and four participants respectively were lead through a design thinking workshop in which they brainstormed and ranked the physical features and expected interactions of social and non-social robots.They were asked to sketch ideal and minimum versions of each type of robot which were then evaluated on the degree to which different mental states were attributed to the robot (as only an intentional agent can have a mind and therefore mental states). Results showed that the minimum features required for participants to attribute mental states to a robot include an emotive head with eyes and a mouth. This minimal feature set can be utilized by social roboticists to aid in future designs in order to save both time and monetary resources.

No abstract

No abstract