Personal Influences on Dynamic Trust Formation in Human-Agent Interaction

Abstract

The development of automated technologies in our daily life has transformed the role of human operators from a controller to a teammate who shares control with automated agents. However, this 'teammate' relationship between humans and automation raises an important but challenging research question regarding the formation of human-agent trust. Considering that the formation of human-agent trust is a dynamic and sophisticated process involving human factors, this study conducted a two-phase online experiment to examine personal influences on users' trust propensity and their trust formation in human-agent interactions. Our findings revealed distinctive personal influences on dispositional trust and the formation of human-agent trust at different stages. We found that users who exhibit higher trust propensities in humans also develop higher trust toward automated agents in initial stages. This study, as the first of its kind, not only fills the gap of knowledge about personal influences on human-agent trust, but also offers opportunities to enhance the future design of automated agent systems.

Evaluating Effective Connectivity of Trust in Human–Automation Interaction: A Dynamic Causal Modeling (DCM) Study

“…Trust, as a result of multiple cognitive pro- Huang & Bashir, 2017;Kun et al, 2018;Lee & See, 2000;Noah & Walker, 2017;Pop et al, 2015;Thropp et al, 2018;Visser et al, 2014;Yeh & Wickens, 2001). Among them, reliability and credibility are two of the most researched factors in human-automation interaction (Balfe et al, 2018;Lee & See, 2004;Madhavan & Wiegmann, 2007).…”

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“…Automation refers to technology that allows for data to be collected, selected, computed, and analyzed (Lee & See, 2004). Automation helps users control processes in a systematic way, make decisions, decrease cognitive workload, and reduce human error (Hoff & Bashir, 2015;Huang & Bashir, 2017;Miller, 2018). For example, medical professionals rely on robots for precision, dexterity, and endurance.…”

How to Evaluate Trust in AI-Assisted Decision Making? A Survey of Empirical Methodologies

“…All the numbers reported are as of beginning of January 2021 4. We found several keywords including automated decision aid (e.g.,[91]), AI-based decision support system (e.g.,[24]), intelligent assistant (e.g.,[2]), intelligent agent (e.g.,[214]), classifier (e.g.,[237]), etc 5. Henceforth, all reported percentages are rounded up to the nearest tenth.Proc.…”