Explicating AI literacy of employees at digital workplaces

Cetindamar Kozanoglu, D; Kitto, K; Wu, M; Zhang, Y; Abedin, B; Knight, S

Explicating AI literacy of employees at digital workplaces

Cetindamar Kozanoglu, D

Kitto, K Wu, M Zhang, Y Abedin, B Knight, S

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Engineering Management, 2022, pp. 1-28
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Cetindamar Kozanoglu, D https://orcid.org/0000-0002-0457-3258
dc.contributor.author	Kitto, K
dc.contributor.author	Wu, M
dc.contributor.author	Zhang, Y
dc.contributor.author	Abedin, B
dc.contributor.author	Knight, S
dc.date.accessioned	2021-12-23T23:01:35Z
dc.date.available	2021-12-23T23:01:35Z
dc.date.issued	2022-01-01
dc.identifier.citation	IEEE Transactions on Engineering Management, 2022, pp. 1-28
dc.identifier.issn	0018-9391
dc.identifier.uri	http://hdl.handle.net/10453/152505
dc.description.abstract	This paper aims to understand the definition and dimensions of artificial intelligence (AI) literacy. Digital technologies, including AI, trigger organizational affordances in workplaces, yet few studies have investigated employees’ AI literacy. This paper uses a bibliometrics analysis of 270 articles to explore the meaning of AI literacy of employees in the extant literature. Descriptive statistics, keyword co-occurrence analysis, and a hierarchical topic tree are employed to profile the research landscape and identify the core research themes and relevant papers related to AI literacy’s definition, dimensions, challenges, and future directions. Findings highlight four sets of capabilities associated with AI literacy, namely technology-related, work-related, human-machine-related, and learning-related capabilities, pointing also to the importance of operationalizing AI literacy for non AI professionals. This result contributes to the literature associated with technology management studies by offering a novel conceptualization of AI literacy and link it to the employee’s role in digital workplaces. We conclude by inviting researchers to examine the effect of employee-technology interactions on employees’ AI literacy, which might improve the design and use of AI.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Transactions on Engineering Management
dc.relation.isbasedon	10.1109/TEM.2021.3138503
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Business & Management
dc.title	Explicating AI literacy of employees at digital workplaces
dc.type	Journal Article
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	15 Commerce, Management, Tourism and Services
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Professional Practice and Leadership
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
utslib.copyright.embargo	2024-01-13T00:00:00+1000Z
dc.date.updated	2021-12-23T23:01:34Z
pubs.publication-status	Accepted

Abstract:

This paper aims to understand the definition and dimensions of artificial intelligence (AI) literacy. Digital technologies, including AI, trigger organizational affordances in workplaces, yet few studies have investigated employees’ AI literacy. This paper uses a bibliometrics analysis of 270 articles to explore the meaning of AI literacy of employees in the extant literature. Descriptive statistics, keyword co-occurrence analysis, and a hierarchical topic tree are employed to profile the research landscape and identify the core research themes and relevant papers related to AI literacy’s definition, dimensions, challenges, and future directions. Findings highlight four sets of capabilities associated with AI literacy, namely technology-related, work-related, human-machine-related, and learning-related capabilities, pointing also to the importance of operationalizing AI literacy for non AI professionals. This result contributes to the literature associated with technology management studies by offering a novel conceptualization of AI literacy and link it to the employee’s role in digital workplaces. We conclude by inviting researchers to examine the effect of employee-technology interactions on employees’ AI literacy, which might improve the design and use of AI.

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http://hdl.handle.net/10453/152505