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Related Experiment Video

Updated: Jan 14, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity

Published on: September 26, 2025

(Some) Benefits in Operator Decisions to Use AI After Experiencing Optimal Outcomes.

Colleen E Patton¹, Benjamin A Clegg², Blake C Davis³

¹North Carolina State University, USA.

|October 18, 2025

Summary

This summary is machine-generated.

Early exposure to optimal human-automation interaction strategies, including high evidence accumulation and automation use, improved operator decision-making. This training approach enhances performance in dynamic tasks.

Keywords:

adaptable automation dynamic decision making evidence accumulation human–automation teaming

Related Experiment Videos

Last Updated: Jan 14, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity

Published on: September 26, 2025

Area of Science:

Human-Computer Interaction
Cognitive Psychology
Decision Science

Background:

Operators often underutilize automation and collect insufficient evidence, leading to suboptimal performance.
Training is needed to improve operator behaviors in dynamic decision-making tasks.

Purpose of the Study:

To investigate how experiencing superior behaviors impacts subsequent evidence accumulation and automation use.
To assess the effectiveness of training in human-automation interaction.

Main Methods:

Participants performed a dynamic decision-making task involving ship movement pattern recognition.
Initial training required high evidence collection and automation use, followed by a choice phase.

Main Results:

Operators chose to collect less evidence and use automation less frequently when given a choice.
Despite reduced engagement, performance improved compared to unaided conditions.

Conclusions:

Experiencing optimal behaviors can enhance subsequent operator decisions and performance.
This training method shows promise for improving human-automation synergy and interaction.