Effects of Task Difficulty and Display Format on Automation Usage Strategy: A Workload Capacity Analysis

Abstract

Objective An experiment used workload capacity analysis to quantify automation usage strategy across different task difficulty and display format types in a speeded task. Background Workload capacity measures the efficiency of concurrent information processing and can serve as a gauge of automation usage strategy in speeded decision tasks. The present study used workload capacity analysis to investigate automation usage strategy while information display format and task difficulty were manipulated. Method Subjects performed a speeded judgment task assisted by an automated aid that issued decision cues at varying onset times. Response time distributions were converted to measures of workload capacity. Results Two variants of a workload capacity measure, C_zOR and C_zAND, gave evidence that operators moderated their own decision times both in anticipation of and following the arrival of the aid's diagnosis under difficult task conditions regardless of display format. Conclusion Assistance from an automated decision aid may cause operators to delay their own responses in a speeded decision task, producing joint response time distributions that are slower than optimal. Application Even when it renders its own judgments quickly and with high accuracy, an automated decision aid may slow responses from a user. Automation designers should consider the relative costs and benefits of response accuracy and time when choosing whether and how to implement an automated decision aid.

Keywords: human-automation system; task difficulty; visual interface; workload capacity.