An attempt to reduce negative attitude towards robots and upgrade trust through explanations

Abstract

When humans interact with robots in daily life, each human has a different attitude towards robots that may directly affect human-robot trustworthy relationships. By attitude, we mean any mental disposition matured through experience. A negative attitude is the psychological factors that prevent a human from interacting with robots in daily life and also creates a hurdle for a human to build trust in a robot. In this paper, we hypothesise that explanations from a robot that contain “Decision-Transparency” and “Error-Justification and Correction” policy can help in reducing humans’ negative attitude towards robots and facilitate smooth interaction. Explanations, specifically communicated in human-understandable terms can create a significant difference. To analyse the profound impact of explanations from a robot, we conducted an Experimental Study with 34 human participants by performing a decision-making task in collaboration with a real robot. Objective assessment, i.e. facial expressions and eye contact with the robot signalled a decrease in the negative attitude of human participants towards the robot. We also found that human participants trusted and conformed more with the robot’s decisions (communicated in terms of explanations), as compared to their own decisions. Meanwhile, subjective measures (Negative Attitude toward Robots Scale (NARS), Human-Robot Trust Scale (HRT) questionnaires) also reported that, after having interaction with the robot, humans’ trust in the robot increased and negative attitude significantly reduced. Our findings suggest new implications for the establishment of smooth human-robot trustworthy relationships.