Understanding the Uncanny: Both Atypical Features and Category Ambiguity Provoke Aversion towards Humanlike Robots

Robots intended for social contexts are often designed with explicit humanlike attributes in order to facilitate their reception by (and communication with) people. However, observation of an "uncanny valley" – a phenomenon in which highly humanlike entities provoke aversion in human observers – has lead some to caution against this practice. Both of these contrasting perspectives on the anthropomorphic design of social robots find some support in empirical investigations to date. Yet, owing to outstanding empirical limitations and theoretical disputes, the uncanny valley and its implications for human-robot interaction remains poorly understood. We thus explored the relationship between human similarity and people’s aversion towards humanlike robots via manipulation of the agents’ appearances. To that end, we employed a picture-viewing task (Nagents = 60) to conduct an experimental test (Nparticipants = 72) of the uncanny valley’s existence and the visual features that cause certain humanlike robots to be unnerving. Across the levels of human similarity, we further manipulated agent appearance on two dimensions, typicality (prototypic, atypical, and ambiguous) and agent identity (robot, person), and measured participants’ aversion using both subjective and behavioral indices. Our findings were as follows: (1) Further substantiating its existence, the data show a clear and consistent uncanny valley in the current design space of humanoid robots. (2) Both category ambiguity, and more so, atypicalities provoke aversive responding, thus shedding light on the visual factors that drive people’s discomfort. (3) Use of the Negative Attitudes towards Robots Scale did not reveal any significant relationships between people’s pre-existing attitudes towards humanlike robots and their aversive responding – suggesting positive exposure and/or additional experience with robots is unlikely to affect the occurrence of an uncanny valley effect in humanoid robotics. This work furthers our understanding of both the uncanny valley, as well as the visual factors that contribute to an agent’s uncanniness.