How Sustainable Is Big Data?
Open accessAbstract
The rapid growth of “big data” provides tremendous opportunities for making better decisions, where “better” can be defined using any combination of economic, environmental, or social metrics. This essay provides a few examples of how the use of big data can precipitate more sustainable decision‐making. However, as with any technology, the use of big data on a large scale will have some undesirable consequences. Some of these are foreseeable, while others are entirely unpredictable. This essay highlights some of the sustainability‐related challenges posed by the use of big data. It does not intend to suggest that the advent of big data is an undesirable development. However, it is not too early to start asking what the unwanted repercussions of the big data revolution might be.
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In a world prone to climate crisis, the environmental impact of AI might well constrain its deployment, at least if sustainability becomes a serious parameter in economic activity.
“Similarly, in a world prone to climate crisis, the environmental impact of AI (Corbett 2018;Dhar 2020;Lucivero 2020;Strubell et al. 2020; van Wynsberghe 2021) might well constrain its deployment, at least if sustainability becomes a serious parameter in economic activity (Nishant et al. 2020 for a contrary optimistic view).”
From Artificial intelligence and work: a critical review of recent research from the social sciences (2024) · cites this paper as Corbett 2018
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“Similarly, in a world prone to climate crisis, the environmental impact of AI (Corbett 2018; Dhar 2020; Lucivero 2020; Strubell et al. 2020; van Wynsberghe 2021) might well constrain its deployment, at least if sustainability becomes a serious parameter in economic activity (Nishant et al. 2020 for…”
- Authors
- Corbett, C. J.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Corbett, Charles J.
- ORCID
- Corbett, Charles J.
- Venue
- Production and Operations Management
- Publisher
- SAGE Publications
- Published
- 2018-09
- Volume
- 27
- Issue
- 9
- Pages
- 1685-1695
- ISSN
- 1059-1478 (ISSN-L)
- 1937-5956
- OpenAlex
- W2778203760
- Cited by
- 128
- References
- 48
- Citations by year
- 2026: 12 · 2025: 12 · 2024: 28 · 2023: 25 · 2022: 21 · 2021: 13 · 2020: 11 · 2019: 3 · 2018: 2 · 2017: 1
- FWCI
- 7.47
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Production and Operations Management (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Keywords
- big data, sustainability, sustainable decision-making, unintended consequences of technology
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