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The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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Automation trust and attention allocation in multitasking workspace.

Nicole D Karpinsky1, Eric T Chancey2, Dakota B Palmer1

  • 1Old Dominion University, VA, USA.

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High workload reduces operator trust and monitoring of automation. When complex tasks demand more attention, operators visually disengage from automation systems, impacting overall performance and trust.

Keywords:
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Area of Science:

  • Human-Computer Interaction
  • Cognitive Psychology
  • Automation Systems Engineering

Background:

  • Operator distrust and poor monitoring of automation are linked to high workload.
  • Previous inferences were primarily based on automation dependence behaviors.

Purpose of the Study:

  • To directly measure automation monitoring by assessing visual attention allocation, workload, and trust.
  • To investigate these factors in a dynamic multitasking environment with imperfect automation.

Main Methods:

  • Participants performed concurrent manual tracking and system monitoring tasks.
  • An unreliable signaling system assisted the monitoring task.
  • Eye movement data, workload, and trust ratings were collected.

Main Results:

  • Increased tracking task difficulty led to reduced visual attention allocated to automation monitoring.
  • Higher visual attention demands correlated with decreased trust in the automation.
  • Trust mediated the task load-attention relationship in Experiment 1, but not Experiment 2.

Conclusions:

  • Multitasking involves a complex interplay between task load, visual attention, and automation trust.
  • Automation designers must account for operator task load to prevent monitoring deficits and distrust.
  • Findings highlight the need for adaptive automation design in complex operational environments.