How Are Robots Appraised in Relation to Social Expectations? Eliciting Explanations through Social Stories

This work focuses on the importance of exploring how people explain and assess the behavior of artificial agents in social contexts. It introduces a formalization of agent behavior through a cognitive architecture based on Social Practice Theory. Using narrative scenarios enacted by the humanoid robot Pepper, two distinct behaviors are compared: one that is socially evocative and another that aligns with social expectations, driven by the interaction of the components within the architecture. A preliminary analysis combining thematic coding of semi-structured interviews and a Likert-scale questionnaire reveals that when a robot’s behavior aligns with social expectations, it influences both the language used to explain the agent’s actions and the participants’ assessments of its social competence.