Critic, compatriot, or chump?

Abstract

As their abilities improve, robots will be placed in roles of greater responsibility and specialization. In these contexts, robots may attribute blame to humans in order to identify problems and help humans make sense of complex information. In a between-participants experiment with a single factor (blame target) and three levels (human blame vs. team blame vs. self blame) participants interacted with a robot in a learning context, teaching it their personal preferences. The robot performed poorly, then attributed blame to either the human, the team, or itself. Participants demonstrated a powerful and consistent negative response to the human-blaming robot. Participants preferred the self-blaming robot over both the human and team blame robots. Implications for theory and design are discussed.