A Meta-Analysis of Factors Influencing the Development of Trust in Automation
2016/03/22 by Kristin E. Schaefer, Jessie Y. C. Chen, James L. Szalma +2 · 736 citations
Decision Sciences · Engineering · Mathematics · Medicine · Psychology · #Artificial intelligence #Automation #Cognitive Functions and Memory #Computer science #Engineering #Field (mathematics) #Foundation (evidence) #Human-Automation Interaction and Safety #Knowledge management #Machine learning #Mathematics #Medicine #Meta-analysis #Moderation #Pairwise comparison #Personal Information Management and User Behavior #Political science #Psychology #Work (physics)
paper · open access · doi:10.1177/0018720816634228
published in Human Factors The Journal of the Human Factors and Ergonomics Society 58(3), 377-400 (SAGE Publishing)
openalex publication_date 2016/03/22 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
Abstract
OBJECTIVE: We used meta-analysis to assess research concerning human trust in automation to understand the foundation upon which future autonomous systems can be built. BACKGROUND: Trust is increasingly important in the growing need for synergistic human-machine teaming. Thus, we expand on our previous meta-analytic foundation in the field of human-robot interaction to include all of automation interaction. METHOD: We used meta-analysis to assess trust in automation. Thirty studies provided 164 pairwise effect sizes, and 16 studies provided 63 correlational effect sizes. RESULTS: The overall effect size of all factors on trust development was ḡ = +0.48, and the correlational effect was [Formula: see text] = +0.34, each of which represented medium effects. Moderator effects were observed for the human-related (ḡ = +0.49; [Formula: see text] = +0.16) and automation-related (ḡ = +0.53; [Formula: see text] = +0.41) factors. Moderator effects specific to environmental factors proved insufficient in number to calculate at this time. CONCLUSION: Findings provide a quantitative representation of factors influencing the development of trust in automation as well as identify additional areas of needed empirical research. APPLICATION: This work has important implications to the enhancement of current and future human-automation interaction, especially in high-risk or extreme performance environments.
Citations
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- How and why humans trust: A meta-analysis and elaborated model. [europepmc]
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- Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study. [europepmc]
- Neural Correlates of Trust in Automation: Considerations and Generalizability Between Technology Domains. [europepmc]
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