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Should We Just Let the Machines Do It? The Benefit and Cost of Action Recommendation and Action Implementation Automation
Human Factors: The Journal of the Human Factors and Ergonomics Society ( IF 3.3 ) Pub Date : 2021-02-08 , DOI: 10.1177/0018720821989148
Monica Tatasciore 1 , Vanessa K Bowden 1 , Troy A W Visser 1 , Shayne Loft 1
Affiliation  

Objective

To examine the effects of action recommendation and action implementation automation on performance, workload, situation awareness (SA), detection of automation failure, and return-to-manual performance in a submarine track management task.

Background

Theory and meta-analytic evidence suggest that with increasing degrees of automation (DOA), operator performance improves and workload decreases, but SA and return-to-manual performance declines.

Method

Participants monitored the location and heading of contacts in order to classify them, mark their closest point of approach (CPA), and dive when necessary. Participants were assigned either no automation, action recommendation automation, or action implementation automation. An automation failure occurred late in the task, whereby the automation provided incorrect classification advice or implemented incorrect classification actions.

Results

Compared to no automation, action recommendation automation benefited automated task performance and lowered workload, but cost nonautomated task performance. Action implementation automation resulted in perfect automated task performance (by default) and lowered workload, with no costs to nonautomated task performance, SA, or return-to-manual performance compared to no automation. However, participants provided action implementation automation were less likely to detect the automation failure compared to those provided action recommendations, and made less accurate classifications immediately after the automation failure, compared to those provided no automation.

Conclusion

Action implementation automation produced the anticipated benefits but also caused poorer automation failure detection.

Application

While action implementation automation may be effective for some task contexts, system designers should be aware that operators may be less likely to detect automation failures and that performance may suffer until such failures are detected.



中文翻译:

我们应该让机器来做吗?行动建议和行动实施自动化的收益和成本

客观的

检查行动建议和行动实施自动化对潜艇轨道管理任务中的性能、工作量、态势感知 (SA)、自动化故障检测和返回手动性能的影响。

背景

理论和元分析证据表明,随着自动化程度 (DOA) 的提高,操作员绩效会提高并且工作量会减少,但 SA 和返回人工的绩效会下降。

方法

参与者监测接触者的位置和航向,以便对其进行分类,标记他们最近的接近点 (CPA),并在必要时潜水。参与者被分配了没有自动化、行动推荐自动化或行动实施自动化。任务后期发生自动化故障,由此自动化提供了错误的分类建议或实施了错误的分类操作。

结果

与没有自动化相比,行动推荐自动化有利于自动化任务性能并降低工作量,但会降低非自动化任务性能。行动实施自动化导致完美的自动化任务性能(默认情况下)和降低的工作量,与没有自动化相比,非自动化任务性能、SA 或返回到手动性能没有成本。然而,与那些提供行动建议的参与者相比,提供行动实施自动化的参与者不太可能检测到自动化失败,并且与那些没有提供自动化的参与者相比,在自动化失败后立即做出不太准确的分类。

结论

行动实施自动化产生了预期的好处,但也导致较差的自动化故障检测。

应用

虽然操作实施自动化可能对某些任务上下文有效,但系统设计人员应该意识到操作员可能不太可能检测到自动化故障,并且在检测到此类故障之前性能可能会受到影响。

更新日期:2021-02-08
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