This research paper identifies the disciplinary differences of stakeholders and its effects on working cross-functional in the context of machine learning. This study specifically focused on 1) how stakeholders with disciplinary differences interpret a search system, and 2) how the multi-disciplines should be managed in an organization. This was studied through 12 interviews with stakeholders from design disciplines, product management, data science and machine learning engineering, followed by a focus group with a participant from each of the different disciplines. The findings were analyzed through a thematic analysis and institutional logics and concluded that the different logics had a high impact on the stakeholders’ understanding of the search system. The research also concluded that bridging the gap between the multi-disciplinary stakeholders are of high importance in context of machine learning.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-480072 |
Date | January 2022 |
Creators | Eliasson, Nina |
Publisher | Uppsala universitet, Institutionen för informatik och media |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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