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Managerial Controversies in Artificial Intelligence and Big Data Analytics

Managerial Controversies in Artificial Intelligence and Big Data Analytics

Kenneth David Strang, Zhaohao Sun
Copyright: © 2022 |Pages: 20
ISBN13: 9781668436622|ISBN10: 1668436620|EISBN13: 9781668436639
DOI: 10.4018/978-1-6684-3662-2.ch085
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MLA

Strang, Kenneth David, and Zhaohao Sun. "Managerial Controversies in Artificial Intelligence and Big Data Analytics." Research Anthology on Big Data Analytics, Architectures, and Applications, edited by Information Resources Management Association, IGI Global, 2022, pp. 1745-1764. https://doi.org/10.4018/978-1-6684-3662-2.ch085

APA

Strang, K. D. & Sun, Z. (2022). Managerial Controversies in Artificial Intelligence and Big Data Analytics. In I. Management Association (Ed.), Research Anthology on Big Data Analytics, Architectures, and Applications (pp. 1745-1764). IGI Global. https://doi.org/10.4018/978-1-6684-3662-2.ch085

Chicago

Strang, Kenneth David, and Zhaohao Sun. "Managerial Controversies in Artificial Intelligence and Big Data Analytics." In Research Anthology on Big Data Analytics, Architectures, and Applications, edited by Information Resources Management Association, 1745-1764. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-3662-2.ch085

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Abstract

This chapter discusses several fundamental and managerial controversies associated with artificial intelligence and big data analytics which will be of interest to quantitative professionals and practitioners in the fields of computing, e-commerce, e-business services, and e-government. The authors utilized the systems thinking technique within an action research framework. They used this approach because their ideology was pragmatic, the problem at hand, was complex and institutional (healthcare discipline), and they needed to understand the problems from both a practitioner and a nonhuman technology process viewpoint. They used the literature review along with practitioner interviews collected at a big data conference. Although they found many problems, they considered these to be already encompassed into the big data five V's (volume, velocity, variety, value, veracity). Interestingly, they uncovered three new insights about the hidden healthcare artificial intelligence and big data analytics risks; then they proposed solutions for each of these problems.

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