Do the Eyes Have It? A Review of Using Eye Tracking for Automation Trust Measurement

Area of Science:

• Human-Computer Interaction
• Cognitive Science
• Automation Systems

Background:

• Researchers seek reliable measures for trust in automation.
• Eye tracking is explored as a nonintrusive, objective tool.
• Existing studies often assume decreased visual attention with increased trust.

Purpose of the Study:

• To systematically review and assess the validity of eye tracking metrics for representing trust in automation.
• To determine the reliability of the assumed inverse relationship between trust and visual attention.

Main Methods:

• A systematic literature review was conducted.
• Included studies tested the relationship between eye tracking metrics and trust in automation.
• Analyzed findings across 22 relevant articles.

Main Results:

• Only about half of the reviewed studies found a significant negative relationship between eye tracking metrics and trust.
• The other half of the studies found no significant relationship.
• The observed relationship varied significantly across different metrics and study designs.

Conclusions:

• The relationship between automation trust and eye tracking metrics is inconsistent and unreliable.
• Current eye tracking metrics are not sufficiently robust for accurately measuring automation trust.
• Further research is needed to establish valid and reliable eye tracking measures for automation trust.