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The Effect of Workload and Task Priority on Multitasking Performance and Reliance on Level 1 Explainable AI (XAI)

Jawad Alami¹, Mohamad El Iskandarani¹, Sara Lu Riggs¹

¹University of Virginia, USA.

|March 12, 2025

Summary

This summary is machine-generated.

High workload in critical tasks increases reliance on AI alerts but reduces alert verification. Task priority also impacts AI explanation use, crucial for calibrating AI trust in high-stakes environments.

Keywords:

automation explanation multitasking performance reliance workload

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Area of Science:

Human-Computer Interaction
Cognitive Psychology
Artificial Intelligence

Background:

Operators in critical environments face multitasking challenges impacting performance.
Explainable Artificial Intelligence (XAI) can support decision-making, but its use in multitasking is not well understood.
Level 1 XAI provides basic perceptual information to aid operators.

Purpose of the Study:

To examine how workload and task priority affect multitasking performance.
To investigate operator reliance on Level 1 XAI systems in high-stakes scenarios.
To understand the interplay between workload, task priority, and XAI utilization.

Main Methods:

A within-subjects experiment with 30 participants in a simulated UAV command and control task.
Manipulation of workload (low, medium, high) and AI-assisted task priority (low, high).
Measurement of performance metrics including accuracy, AI reliance, and alert detection.

Main Results:

Increased workload degraded performance on the AI-assisted task and heightened reliance on the AI system, particularly with low task priority.
Task priority significantly influenced the use of AI explanations.
Operators showed increased reliance on AI alerts under high workload but decreased alert verification.

Conclusions:

Workload influences operator reliance on AI, necessitating careful calibration of AI trust in critical systems.
Task priority is a key factor in how operators engage with AI explanations.
Findings inform the design of AI systems for high-stakes environments to ensure appropriate AI reliance.