The Benefits and Costs of Low and High Degree of Automation. (September 2020)

• Record Type: Journal Article
• Authors: Tatasciore, Monica; Bowden, Vanessa K.; Visser, Troy A. W.; Michailovs, Steph I. C.; Loft, Shayne
• Is Part Of: Human factors. Volume 62:Number 6(2020)
• Page Start: 874
• Page End: 896
• Publication Date: 2020-09
• Subjects: automation -- submarine track management -- situation awareness -- workload -- complacency; Human engineering -- Periodicals; 620.82
• DOI: 10.1177/0018720819867181
• Languages: English
• ISSNs: 0018-7208

Abstract

Objective: The objective of this study is to examine the effects of low and high degree of automation (DOA) on performance, subjective workload, situation awareness (SA), and return-to-manual control in simulated submarine track management. Background: Theory and meta-analytic evidence suggest that as DOA increases, operator performance improves and workload decreases, but SA and return-to-manual control declines. Research also suggests that operators have particular difficulty regaining manual control if automation provides incorrect advice. Method: Undergraduate student participants completed a submarine track management task that required them to track the position and behavior of contacts. Low DOA supported information acquisition and analysis, whereas high DOA recommended decisions. At a late stage in the task, automation was either unexpectedly removed or provided incorrect advice. Results: Relative to no automation, low DOA moderately benefited performance but impaired SA and non-automated task performance. Relative to no automation and low DOA, high DOA benefited performance and lowered workload. High DOA did impair non-automated task performance compared with no automation, but this was equivalent to low DOA. Participants were able to return-to-manual control when they knew low or high DOA was disengaged, or when high DOA provided incorrect advice. Conclusion: High DOA improved performance and lowered workload, at no additional cost to SA or return-to-manual performance when compared with low DOA. Application: Designers should consider the likely level of uncertainty in the environment and the consequences of return-to-manual deficits before implementing low or high DOA.