Not Seeing the Data for the Trees: How Ecological Metaphors Matter in Academic Discourse on Platforms and AI
Publication date
2026
Editors
Mollen, Anne
Jansen, Fieke
Kannengießer, Sigrid
Velkova, Julia
Advisors
Supervisors
Document Type
Part of book
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cc_by
Abstract
Discourses on computation, data, platforms and AI are filled with biological and botanical metaphors. Not only do tech companies use such language to appeal to environmentally conscious consumers, but, significantly, much critical work by media scholars also employs ecological metaphors to highlight particular aspects of data systems, platforms, and industries. Apart from functioning as explanatory frameworks, what are the implication of academic metaphors for how AI and platforms are studied? In this chapter, we will take a critical look at biological and botanical metaphors employed in a few key publications in the field of platform studies. Methodologically, we are inspired by Christy Wampoles, “ecocritical metaphorology” as a way to focus on the ideological work done by figurative speech that involves words related to nature, plants, flowers, and trees, to “help us understand the extent to which metaphorical thinking facilitates or hinders our efforts to ‘save the planet’” (Wampole, 2021, p. 53). We will argue that using botanical and ecological metaphors to explain AI and platformization processes runs the risk of obscuring and naturalizing human-made decisions, infrastructures, and politics. At the end of this chapter, we speculate about potential alternative metaphors to better describe environmental implications of AI and digital platforms.
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Citation
van Schie, G & Gloerich, I 2026, Not Seeing the Data for the Trees: How Ecological Metaphors Matter in Academic Discourse on Platforms and AI. in A Mollen, F Jansen, S Kannengießer & J Velkova (eds), AI Infrastructures and Sustainability : Expanding Perspectives on Automation, Communication and Media. Palgrave Studies in European Communication Research and Education, Palgrave Macmillan, United Kingdom, pp. 261-277. https://doi.org/10.1007/978-3-032-09748-4_12