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Morphological Box for AI Solutions: Evaluation and Refinement with a Taxonomy Development Method
Institute of Computer Science, University of Rostock, Albert-Einstein-Str. 22, Rostock, 18057, Germany.
Jönköping University, Tekniska Högskolan, JTH, Avdelningen för datateknik och informatik. Institute of Computer Science, University of Rostock, Albert-Einstein-Str. 22, Rostock, 18057, Germany.ORCID-id: 0000-0002-7431-8412
2023 (Engelska)Ingår i: Perspectives in Business Informatics Research: 22nd International Conference on Business Informatics Research, BIR 2023, Ascoli Piceno, Italy, September 13–15, 2023, Proceedings / [ed] K. Hinkelmann, F. J. López-Pellicer, A. Polini, Springer, 2023, Vol. 493, s. 145-157Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Investigations into the organisational uptake of artificial intelligence (AI) solutions confirm that there is a growing interest in enterprises and public authorities to use AI. In this context, the lack of understanding of AI concepts in organisations is a significant challenge. As a contribution to addressing this issue, we previously developed and evaluated a morphological box for AI solutions. To further refine this morphological box, the paper follows a well-established scientific method for this purpose: This paper presents the application of a taxonomy development method to our morphological box. We use this method to determine a meta-characteristic, identify the target audience, project the use of the morphological box, and define both subjective and objective ending conditions. We describe several iterations of the development and evaluation loops and present our final results. Our analysis demonstrates the effectiveness of the taxonomy development method in refining and enhancing the morphological box for AI solutions. We further present the application of the morphological box for classifying AI projects with four initial case studies, discuss the results as well as further development directions and potentials of the box. 

Ort, förlag, år, upplaga, sidor
Springer, 2023. Vol. 493, s. 145-157
Serie
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 493
Nyckelord [en]
AI Context, Artificial Intelligence, Morphological Box, Organisational AI Solutions, Taxonomy Development, Artificial intelligence context, Condition, Development method, Organisational, Organizational artificial intelligence solution, Public authorities, Scientific method, Target audience, Taxonomies
Nationell ämneskategori
Människa-datorinteraktion (interaktionsdesign)
Identifikatorer
URN: urn:nbn:se:hj:diva-62634DOI: 10.1007/978-3-031-43126-5_11Scopus ID: 2-s2.0-85172136110ISBN: 978-3-031-43125-8 (tryckt)ISBN: 978-3-031-43126-5 (digital)OAI: oai:DiVA.org:hj-62634DiVA, id: diva2:1803724
Konferens
Proceedings of the 22nd International Conference on Business Informatics Research, BIR 2023 Ascoli Piceno 13 September 2023 through 15 September 2023
Tillgänglig från: 2023-10-10 Skapad: 2023-10-10 Senast uppdaterad: 2023-10-27Bibliografiskt granskad

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Sandkuhl, Kurt

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