AI Project and Deployment Risk: Articulation and Legitimization

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dc.contributor.authorLahiri, Sucheta
dc.contributor.authorSaltz, Jeffrey
dc.date.accessioned2023-12-26T18:48:02Z
dc.date.available2023-12-26T18:48:02Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.703
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other861f6395-32c3-445f-ae44-d1b437adb512
dc.identifier.urihttps://hdl.handle.net/10125/107088
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAI, Organizing, and Management
dc.subjectai
dc.subjectartifiicial intelligence
dc.subjectbourdieu
dc.subjectcultural capital
dc.subjectdata science
dc.subjectproject management
dc.subjectrisk
dc.subjectsocial capital
dc.titleAI Project and Deployment Risk: Articulation and Legitimization
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractThis study explores how practitioners identify and manage AI project-related risks to reduce AI project failures. Specifically, through a qualitative research study involving 16 data science practitioners, this study presents insights into how practitioners articulate and mitigate the risk of AI project failure. A thematic analysis of this study identified six key themes (Ethical risk, BlackBox Models, Data Privacy, Data Storage, Financial Risks, and Success criteria). Further analysis explored drivers for identifying and mitigating these risks. Specifically, it was found that agency (consumer and institutional-driven) and social/cultural capital (such as management hierarchy and domain knowledge) legitimized specific AI project risks and were key drivers in ensuring risks were identified and mitigated. Results from this research suggest that future research should explore different social and cultural perspectives since these perspectives can impact the articulation of risk and how these risks can be ultimately managed within an AI project context.
dcterms.extent10 pages
prism.startingpage5836

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