A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Understanding Autonomy in Future Systems

Author: Schaefer, K.E.; Chen, J.Y.C.; Szalma, J.L.; Hancock, P.A.

Description: 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 g = +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 (g = +0.49; [Formula: see text] = +0.16) and automation-related (g = +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.

Subject headings: Automation; Humans; Man-Machine Systems; Trust; human-automation interaction; human-robot interaction; meta-analysis; trust

Subject headings:

Publication year: 2016

Journal or book title: Human Factors

Volume: 58

Issue: 3

Pages: 377-400

Find the full text : https://journals.sagepub.com/doi/abs/10.1177/0018720816634228

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Type: Journal Article

Serial number: 2316