Do You Trust Me, Blindly? Factors Influencing Trust Towards a Robot Recommender System
- Publication Type:
- Conference Proceeding
- RO-MAN 2018 - 27th IEEE International Symposium on Robot and Human Interactive Communication, 2018, pp. 7 - 14
- Issue Date:
Copyright Clearance Process
- Recently Added
- In Progress
- Open Access
This item is currently unavailable due to the publisher's embargo.
The embargo period expires on 30 Nov 2020
© 2018 IEEE. When robots and human users collaborate, trust is essential for user acceptance and engagement. In this paper, we investigated two factors thought to influence user trust towards a robot: preference elicitation (a combination of user involvement and explanation) and embodiment. We set our experiment in the application domain of a restaurant recommender system, assessing trust via user decision making and perceived source credibility. Previous research in this area uses simulated environments and recommender systems that present the user with the best choice from a pool of options. This experiment builds on past work in two ways: first, we strengthened the ecological validity of our experimental paradigm by incorporating perceived risk during decision making; and second, we used a system that recommends a nonoptimal choice to the user. While no effect of embodiment is found for trust, the inclusion of preference elicitation features significantly increases user trust towards the robot recommender system. These findings have implications for marketing and health promotion in relation to Human-Robot Interaction and call for further investigation into the development and maintenance of trust between robot and user.
Please use this identifier to cite or link to this item: