Attributing Blame in Human-Robot Teams with Robots of Differing Appearance

Abstract

As automation becomes increasingly common in daily life the importance of understanding how we interact with automated systems increases, especially attribution of blame for accidents involving a human-automation team. The current research project looks at how humans attribute blame in an accident involving a human operator and a robot worker and is based on a previous study (Furlough et al., 2019). Participants will read two scenarios detailing an accident while being shown both the operator and robot. The robot’s appearance is manipulated to imply varying levels of automation, ranging from a simple robot to one with a human appearance. Results showed no significant effects, however, this research still has the potential to contribute to the understanding of interactions between humans and automated systems and could inform design in the future to facilitate a positive working environment with robots and humans.