An in-the-wild study to find type of questions people ask to a social robot providing question-answering service

The role of a human assistant, such as receptionist, is to provide specific information to the public. Questions asked by the public are often context dependent and related to the environment where the assistant is situated. Should similar behaviour and questions be expected when a social robot offers the same assistant service to visitors? Would it be sufficient for the robot to answer only service-specific questions, or is it necessary to design the robot to answer more general questions? This paper aims to answer these research questions by investigating the question-asking behaviour of the public when interacting with a question-answering social robot. We conducted the study at a university event that was open to the public. Results demonstrate that almost no participants asked context-specific questions to the robot. Rather, unrelated questions were common and included queries about the robot's personal preferences, opinions, thoughts and emotional state. This finding contradicts popular belief and common sense expectations from what is otherwise observed during similar human–human interactions. In addition, we found that incorporating non-context-specific questions in a robot's database increases the success rate of its question-answering system.