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Exploring Consumers' Discernment Ability of Autogenerated Advertisements
University of Borås, Faculty of Librarianship, Information, Education and IT. School of Informatics, University of Skövde.ORCID iD: 0000-0002-3553-5983
University of Borås, Faculty of Librarianship, Information, Education and IT.ORCID iD: 0000-0003-4308-434X
University of Borås, Faculty of Librarianship, Information, Education and IT. (InnovationLab)ORCID iD: 0000-0002-9685-7775
University of Borås, Faculty of Textiles, Engineering and Business. School of Informatics, University of Skövde.ORCID iD: 0000-0002-5814-9604
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2023 (English)In: Machine Learning, Multi Agent and Cyber Physical Systems: Proceedings of the 15th International FLINS Conference (FLINS 2022) / [ed] Qinglin Sun; Jie Lu; Xianyi Zeng; Etienne E. Kerre; Tianrui Li, World Scientific, 2023, p. 322-329Conference paper, Published paper (Refereed)
Sustainable development
According to the author(s), the content of this publication falls within the area of sustainable development.
Abstract [en]

Autogenerated Advertisements (AGAs) can be a concern for consumers if they suspect that Artificial Intelligence (AI) was involved. Consumers may have an opposing stance against AI, leading companies to miss profit opportunities and reputation loss. Hence, companies need ways of managing consumers’ con-cerns. As a part of designing such advices we explore consumers’ discernment ability (DA) of AGAs. A quantitative survey was used to explore consumers’ DA of AGAs. In order to do this, we administered questionnaires to 233 re-spondents. A statistical analysis including Z-tests, of these responses suggests that consumers can hardly pick out AGAs. This indicates that consumers may be guessing and thus do not possess any significant DA of our AGAs.

Place, publisher, year, edition, pages
World Scientific, 2023. p. 322-329
Series
World Scientific Proceedings Series on Computer Engineering and Information ScienceAdvanced Knowledge International, ISSN 1793-7868, E-ISSN 2972-4465 ; 13
Keywords [en]
Autogenerated ads, Discernment ability, Marketing
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hb:diva-29252DOI: 10.1142/9789811269264_0038ISBN: 978-981-126-925-7 (print)ISBN: 978-981-126-927-1 OAI: oai:DiVA.org:hb-29252DiVA, id: diva2:1725573
Conference
Conference on Machine learning, Multi Agent and Cyber Physical Systems (FLINS 2022), Tianjin, China, 26 – 28 August 2022
Note

Partly funded by The Knowledge Foundation, grants nr. 20160035, 20170215

Available from: 2023-01-11 Created: 2023-01-11 Last updated: 2023-11-27

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Sahlin, JohannesSundell, HåkanMbiydzenyuy, GideonAlm, Håkan

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