The environmental sustainability of data-driven health research: A scoping review
The environmental sustainability of data-driven health research: A scoping review
Data-Driven and Artificial Intelligence technologies are rapidly changing the way that health research is conducted, including offering new opportunities. This will inevitably have adverse environmental impacts. These include carbon dioxide emissions linked to the energy required to generate and process large amounts of data; the impact on the material environment (in the form of data centres); the unsustainable extraction of minerals for technological components; and e-waste (discarded electronic appliances) disposal. The growth of Data-Driven and Artificial Intelligence technologies means there is now a compelling need to consider these environmental impacts and develop means to mitigate them. Here, we offer a scoping review of how the environmental impacts of data storage and processing during Data-Driven and Artificial Intelligence health-related research are being discussed in the academic literature. Using the UK as a case study, we also offer a review of policies and initiatives that consider the environmental impacts of data storage and processing during Data-Driven and Artificial Intelligence health-related research in the UK. Our findings suggest little engagement with these issues to date. We discuss the implications of this and suggest ways that the Data-Driven and Artificial Intelligence health research sector needs to move to become more environmentally sustainable.
Environmental sustainability, digital technologies, environmental impacts, sustainability
Samuel, Gabrielle
66af6213-08de-4c0e-92c1-12083ec456e3
Lucassen, A M
2eb85efc-c6e8-4c3f-b963-0290f6c038a5
19 July 2022
Samuel, Gabrielle
66af6213-08de-4c0e-92c1-12083ec456e3
Lucassen, A M
2eb85efc-c6e8-4c3f-b963-0290f6c038a5
Samuel, Gabrielle and Lucassen, A M
(2022)
The environmental sustainability of data-driven health research: A scoping review.
Digital Health, 8.
(doi:10.1177/20552076221111297).
Abstract
Data-Driven and Artificial Intelligence technologies are rapidly changing the way that health research is conducted, including offering new opportunities. This will inevitably have adverse environmental impacts. These include carbon dioxide emissions linked to the energy required to generate and process large amounts of data; the impact on the material environment (in the form of data centres); the unsustainable extraction of minerals for technological components; and e-waste (discarded electronic appliances) disposal. The growth of Data-Driven and Artificial Intelligence technologies means there is now a compelling need to consider these environmental impacts and develop means to mitigate them. Here, we offer a scoping review of how the environmental impacts of data storage and processing during Data-Driven and Artificial Intelligence health-related research are being discussed in the academic literature. Using the UK as a case study, we also offer a review of policies and initiatives that consider the environmental impacts of data storage and processing during Data-Driven and Artificial Intelligence health-related research in the UK. Our findings suggest little engagement with these issues to date. We discuss the implications of this and suggest ways that the Data-Driven and Artificial Intelligence health research sector needs to move to become more environmentally sustainable.
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20552076221111297
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Published date: 19 July 2022
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Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Wellcome (grant number 222180/Z/20/Z).
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© The Author(s) 2022.
Keywords:
Environmental sustainability, digital technologies, environmental impacts, sustainability
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Local EPrints ID: 469073
URI: http://eprints.soton.ac.uk/id/eprint/469073
ISSN: 2055-2076
PURE UUID: b5bfc150-ec69-45da-a7c8-4a3b0b7bc9db
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Date deposited: 06 Sep 2022 18:08
Last modified: 17 Mar 2024 02:54
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