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Transparency of Automated Combat Classification
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))
Saab Aeronautics, Sweden.
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0001-8884-2154
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0003-2900-9335
2014 (Engelska)Ingår i: 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, 2014, s. 22-33Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
Springer, 2014. s. 22-33
Serie
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8532
Nyckelord [en]
Classification support, automation transparency, uncertainty visualization, fighter pilots
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Teknik; Skövde Artificial Intelligence Lab (SAIL)
Identifikatorer
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 (tryckt)ISBN: 978-3-319-07515-0 (tryckt)OAI: oai:DiVA.org:his-10163DiVA, id: diva2:760454
Konferens
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
Forskningsfinansiär
VINNOVATillgänglig från: 2014-11-04 Skapad: 2014-11-04 Senast uppdaterad: 2018-03-28Bibliografiskt granskad

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Helldin, ToveOhlander, UlrikaFalkman, GöranRiveiro, Maria

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Helldin, ToveOhlander, UlrikaFalkman, GöranRiveiro, Maria
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