Journal article
Investigating Trust in Interaction with Inconsistent Embodied Virtual Agents
International journal of social robotics, v 13(8), pp 2103-2118
01 Dec 2021
Abstract
Embodied Virtual Agents (EVAs) are used today as interfaces for social robots, educational tutors, game counterparts, medical assistants, as well as companions for the elderly and individuals with psychological or behavioral conditions. Forming a reliable and trustworthy interaction is critical to the success and acceptability of this new form of interaction. In this paper, we report on a study investigating how trust is influenced by the cooperativeness of an EVA as well as an individuals prior experience with other agents. Participants answered two sets of multiple choice questions, working with a different agent in each set. Two types of agent behaviors were possible: Cooperative and Uncooperative. In addition to participants achieving significantly higher performance and having higher trust for the cooperative agent, we found that participants' trust for the cooperative agent was significantly higher if they interacted with an uncooperative agent in one of the sets, compared to working with cooperative agents in both sets. Furthermore, we found that participants may still decide to choose agent's suggested answer (which can be incorrect) over theirs, even if they are fairly certain their own answer is the correct one. The results suggest that trust for an EVA is relative and it is dependent on user's history of interaction with different agents in addition to current agent's behavior. The findings provide insight into important considerations for creating trustworthy EVAs.
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Details
- Title
- Investigating Trust in Interaction with Inconsistent Embodied Virtual Agents
- Creators
- Reza Moradinezhad - Drexel UniversityErin T. Solovey - Worcester Polytechnic Institute
- Publication Details
- International journal of social robotics, v 13(8), pp 2103-2118
- Publisher
- Springer Nature
- Number of pages
- 16
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000632298500001
- Scopus ID
- 2-s2.0-85103194169
- Other Identifier
- 991019167800204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Robotics