Differential biases in human-human versus human-robot interactions. (January 2023)

• Record Type: Journal Article
• Authors: Alarcon, Gene M.; Capiola, August; Hamdan, Izz Aldin; Lee, Michael A.; Jessup, Sarah A.
• Is Part Of: Applied ergonomics. Volume 106(2023)
• Publication Date: 2023-01
• Subjects: Human engineering -- Periodicals; 620.82
• DOI: 10.1016/j.apergo.2022.103858
• Languages: English
• ISSNs: 0003-6870

Abstract

Abstract: The research on human-robot interactions indicates possible differences toward robot trust that do not exist in human-human interactions. Research on these differences has traditionally focused on performance degradations. The current study sought to explore differences in human-robot and human-human trust interactions with performance, consideration, and morality trustworthiness manipulations, which are based on ability/performance, benevolence/purpose, and integrity/process manipulations, respectively, from previous research. We used a mixed factorial hierarchical linear model design to explore the effects of trustworthiness manipulations on trustworthiness perceptions, trust intentions, and trust behaviors in a trust game. We found partner (human versus robot) differences across all three trustworthiness perceptions, indicating biases towards robots may be more expansive than previously thought. Additionally, there were marginal effects of partner differences on trust intentions. Interestingly, there were no differences between partners on trust behaviors. Results indicate human biases toward robots may be more complex than considered in the literature. Highlights: Comparison of computers as social agents and unique agent paradigms. Explored the differences in human-human and human-robot interactions across the trust process. Differences between partner types were found across different trustworthiness manipulations. Findings support both the Computers as Social Actors model and the Unique Agent Hypothesis.