Human-like behavioral variability blurs the distinction between a human and a machine in a nonverbal Turing test

Abstract

Variability is a property of biological systems, and in animals (including humans), behavioral variability is characterized by certain features, such as the range of variability and the shape of its distribution. Nevertheless, only a few studies have investigated whether and how variability features contribute to the ascription of humanness to robots in a human-robot interaction setting. Here, we tested whether two aspects of behavioral variability, namely, the standard deviation and the shape of distribution of reaction times, affect the ascription of humanness to robots during a joint action scenario. We designed an interactive task in which pairs of participants performed a joint Simon task with an iCub robot placed by their side. Either iCub could perform the task in a preprogrammed manner, or its button presses could be teleoperated by the other member of the pair, seated in the other room. Under the preprogrammed condition, the iCub pressed buttons with reaction times falling within the range of human variability. However, the distribution of the reaction times did not resemble a human-like shape. Participants were sensitive to humanness, because they correctly detected the human agent above chance level. When the iCub was controlled by the computer program, it passed our variation of a nonverbal Turing test. Together, our results suggest that hints of humanness, such as the range of behavioral variability, might be used by observers to ascribe humanness to a humanoid robot.