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Transparency of Automated Combat Classification
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-6245-5850
Saab Aeronautics, Sweden.ORCID iD: 0000-0002-0552-8619
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-8884-2154
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2900-9335
2014 (English)In: Engineering Psychology and Cognitive Ergonomics: 11th International Conference, EPCE 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings / [ed] Don Harris, Springer International Publishing Switzerland , 2014, p. 22-33Conference paper, Published paper (Refereed)
Abstract [en]

We present an empirical study where the effects of three levels of system transparency of an automated target classification aid on fighter pilots’ performance and initial trust in the system were evaluated. The levels of transparency consisted of (1) only presenting text–based information regarding the specific object (without any automated support), (2) accompanying the text-based information with an automatically generated object class suggestion and (3) adding the incorporated sensor values with associated (uncertain) historic values in graphical form. The results show that the pilots needed more time to make a classification decision when being provided with display condition 2 and 3 than display condition 1. However, the number of correct classifications and the operators’ trust ratings were the highest when using display condition 3. No difference in the pilots’ decision confidence was found, yet slightly higher workload was reported when using display condition 3. The questionnaire results report on the pilots’ general opinion that an automatic classification aid would help them make better and more confident decisions faster, having trained with the system for a longer period.

Place, publisher, year, edition, pages
Springer International Publishing Switzerland , 2014. p. 22-33
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 8532
Keywords [en]
Classification support, automation transparency, uncertainty visualization, fighter pilots
National Category
Computer Sciences
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-10163DOI: 10.1007/978-3-319-07515-0_3ISI: 000342845800003Scopus ID: 2-s2.0-84903643576ISBN: 978-3-319-07514-3 (print)ISBN: 978-3-319-07515-0 (electronic)OAI: oai:DiVA.org:his-10163DiVA, id: diva2:760454
Conference
11th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2014, Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014, Heraklion, Crete, Greece, 22 June 2014 through 27 June 2014
Funder
Vinnova, NFFP5-2009-01315
Note

Springer Cham

This research has been supported by VINNOVA (Swedish Governmental Agency for Innovation Systems) through the National Aviation Engineering Research Program (NFFP5-2009-01315), Saab AB, the University of Skövde. We would like to thank the study participants, Johan Holmberg, JensAlfredson and Marike Brunberg for their valuable feedback and support.

Available from: 2014-11-04 Created: 2014-11-04 Last updated: 2023-03-24Bibliographically approved

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Helldin, ToveOhlander, UlrikaFalkman, GöranRiveiro, Maria

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CiteExportLink to record
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Citation style
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