Towards a socio-specific artificial intelligence adoption framework

dc.contributor.authorSmit, Danie
dc.contributor.authorEybers, Sunet
dc.contributor.emailsunet.eybers@up.ac.zaen_US
dc.date.accessioned2023-06-14T10:25:49Z
dc.date.available2023-06-14T10:25:49Z
dc.date.issued2022
dc.description.abstractOrganisations need to be able to adopt AI successfully, but also responsibly. This requirement is not trivial, as AI can deliver real value to adopters. However, can also result in serious impacts on humans. AI’s technical capabilities make AI powerful, still the implementation of AI in organisations is not limited to the technical elements and requires a more holistic approach. An AI implementation within an organisation is a socio-technical system, with the interplay between social and technical components. When AI makes decisions that impact people, the socio considerations in AI adoption frameworks are paramount. Although technical adoption challenges are well researched and can overlap with aspects associated with traditional IT implementations, artificial intelligence adoption often faces additional social implication. This study focuses on these social challenges, which is a problem frequently experienced by many organisations. The study investigates how an organisation can increase adoption of AI as part of its quest to become more data-driven. This study was conducted at an automotive manufacturer’s analytics competence centre, located in South Africa. This paper describes the first iteration of a larger research effort that follows the design science research methodology. A socio-specific artificial intelligence adoption framework was created and can be used by organisations to help them succeed with their AI adoption initiatives in a responsible manner.en_US
dc.description.departmentInformaticsen_US
dc.description.librarianam2023en_US
dc.description.urihttp://www.easychair.org/publications/EPiC/Computingen_US
dc.identifier.citationSmit, D. & Eybers, S. 2022, 'Towards a socio-specific artificial intelligence adoption framework', EPiC Series in Computing, vol. 85, pp. 270-282 doi : 10.29007/pc8j.en_US
dc.identifier.issn2398-7340
dc.identifier.other10.29007/pc8j
dc.identifier.urihttp://hdl.handle.net/2263/91123
dc.language.isoenen_US
dc.publisherEasyChairen_US
dc.rightsAll EPiC volumes are open access.en_US
dc.subjectOrganisationsen_US
dc.subjectAdoptersen_US
dc.subjectHumansen_US
dc.subjectArtificial intelligence (AI)en_US
dc.titleTowards a socio-specific artificial intelligence adoption frameworken_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Smit_Towards_2022.pdf
Size:
1.43 MB
Format:
Adobe Portable Document Format
Description:
Article

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: