Seeing Eye to Eye with Robots: An Experimental Study Predicting Trust in Social Robots for Domestic Use

The use of social robots in service tasks is spreading, showcasing advantages for both consumers and service providers. However, their widespread adoption is hindered by a notable lack of trust. Our study aims to uncover insights into the factors influencing the adoption of social robots in home settings, exploring the factors that lead users to trust and eventually adopt robots. We designed two experimental conditions, presenting the Amazon Astro robot from different perspectives (high-angle and eye-level) and demonstrating its different abilities to 198 people recruited from MTurk. We employed both quantitative (trust, first impressions of warmth and competence as well as usability, familiarity, and attitudes) questionnaires and qualitative (word analysis) assessments, and results showed that participants had higher trust scores when seeing the robot from an eye-level perspective. In addition, usability, familiarity and competence were shown to explain a significant amount of variance in trust. While existing negative attitudes towards robots and the participants’ age were shown to be the strongest predictors for participants’ willingness to purchase a robot, trust was able to significantly affect use intention. We contribute to the broader understanding of the challenges and opportunities in integrating social robots into daily life, shedding light on the dynamics between technological innovation and consumer adoption.