Can increased automation transparency mitigate the effects of time pressure on automation use?

Automation transparency Decision support systems Time pressure Uninhabited vehicle control

Journal

Applied ergonomics
ISSN: 1872-9126
Titre abrégé: Appl Ergon
Pays: England
ID NLM: 0261412

Informations de publication

Date de publication:
Jan 2024
Historique:
received: 15 06 2023
revised: 12 09 2023
accepted: 16 09 2023
medline: 13 11 2023
pubmed: 28 9 2023
entrez: 27 9 2023
Statut: ppublish

Résumé

A factor that can potentially negatively impact the accuracy of automated decision aid use, and increase perceived workload, is time pressure. Increased automation transparency can increase the accuracy of automation use. We examined the extent to which increased transparency can mitigate the negative effects of time pressure on the accuracy of automation use and perceived workload. Participants completed an uninhabited vehicle (UV) management task where they assigned the best UV to complete missions by either accepting or rejecting automated advice. Participants made a decision after either 25s (low time pressure) or 12s (high time pressure). The accuracy of automation use decreased, and perceived workload increased, when under higher time pressure. Higher transparency benefited the accuracy of automation use and increased perceived trust and usability. However, high transparency did not mitigate the negative impacts of high time pressure, indicating that increased time pressure can influence the processing of highly transparent information.

Identifiants

pubmed: 37757606
pii: S0003-6870(23)00180-1
doi: 10.1016/j.apergo.2023.104142
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104142

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Monica Tatasciore (M)

The University of Western Australia, Australia. Electronic address: monica.tatasciore@uwa.edu.au.

Shayne Loft (S)

The University of Western Australia, Australia.

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Classifications MeSH