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Chapter 4 - Big Data, Little Understanding

from Part I - Philosophical, Epistemological and Theoretical Considerations

Published online by Cambridge University Press:  08 June 2023

By
Rudy A. Hirschheim  and
David Whitchurch
Edited by
Boyka Simeonova  and
Robert D. Galliers
Boyka Simeonova
Affiliation:
University of Leicester
Robert D. Galliers
Affiliation:
Bentley University, Massachusetts and Warwick Business School
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Summary

Big data has been proclaimed as revolutionary and transformative, and will alter businesses and society in fundamental ways. Such dramatic claims sound suspiciously like prior technological waves which were also promoted as metamorphic. Most of these past ‘revolutionary’ technologies have proved to be more evolutionary than revolutionary, but is the same likely to be true with big data? This chapter examines a number of the underlying assumptions associated with the supposed big data revolution. It highlights some of the fallacies and misconceptions that lie behind big data, and how these assumptions can lead to unintended and dysfunctional consequences. In particular, it explores how these dysfunctions might manifest themselves when it comes to organizational knowledge and practice. The analysis in the chapter leads to the conclusion that while big data offers promise, the hype surrounding it has obscured the potential dangers in its use. The chapter explains that it is important to take a more nuanced view of this new technology, putting safeguards in place to ensure that big data use (including big data analytics, machine learning, artificial intelligence and the algorithms they develop) does not lead to dysfunction.

Keywords

big databig data analyticsmachine learningknowledgeunderstandingimpacts
Type
Chapter
Information
Cambridge Handbook of Qualitative Digital Research , pp. 43 - 59
Publisher: Cambridge University Press
Print publication year: 2023

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