by Beatrice Bonami<\/p>\n\n\n\n
What comes to mind when we think about Artificial Intelligence (AI)? Shiny robots, super computers? Cutting edge laboratories in Asia and North America? What if we tell you that AI is far closer to us than we might realize? It’s present in the spam folder in our emails, in how we navigate social media, self-checkouts, driverless cars, and even when we hear from Call Centers “click 1 if you want to talk to an <\/em>operator, we will transfer you.<\/em>” Yes, AI is everywhere, and its structures are far from shiny or cutting edge, depending on the exploitation of data, labor, and natural resources. The real image of AI is closer to super infrastructures of data centers in the Brazilian desert. Artisanal mining sites in the Copper Belt. Crowded rooms with data workers in Kampala and Bangalore. Debatable server cluster locations in Colombian indigenous protected lands, which consume water and electric power that would be enough to sustain a town for months. <\/p>\n\n\n\n These are the real outlooks when we think of AI: an industry that is far from being green and equitable, exploiting earth and humans as so many other industries do. Specifically, data centers are the backbone of AI, and their expansion in the Global South is creating serious socio-ecological injustices. These facilities consume large volumes of clean water for cooling, often competing with local public supply, strain electrical grids that must prioritize corporate demand over household access, and require vast tracts of land. While governments frame data centers as symbols of modernization and economic growth and couch them in digital sovereignty narratives, the benefits rarely materialize locally, leaving surrounding communities with the ecological cost of powering AI systems built elsewhere. <\/p>\n\n\n\n Much of what we know about data centers concerns their quantifiable environmental impacts: water depletion, energy overuse, heat and e-waste, land conversion, and growing carbon footprints. What is still poorly understood is how these infrastructures affect the social, cultural, and ontological<\/em> fabric of the places where they are built- how they reshape people\u2019s relationships to land, water, and belonging in ways that cannot be reduced to numbers alone. To study these less-visible effects, a multidisciplinary approach is essential, bringing together political ecology, actor-network theory, material semiotics, and assemblage theory to trace how AI infrastructures reorder human and more-than-human ecosystems. <\/p>\n\n\n\n At Planetary AI, we are examining these dynamics through ethnographic fieldwork in multiple countries, e.g. Brazil, Chile, Colombia, Kenya, South Africa and India, documenting how communities experience and respond to data center developments.\u00a0Our approach begins with the premise that the environmental harms caused by data centres – such as water extraction, land enclosure, heat waste, and energy overuse – cannot be separated from their social, cultural, and political consequences. Environmental and climate justice issues are relevant here not simply because our natural ecosystems are being harmed, but because access to water, land, and energy is inseparable from histories of dispossession, claims to belonging, and the right of communities to define how they live and envision their future. In this sense, the expansion of AI\u2019s infrastructures is not just a technical or environmental issue, but a justice issue – one that determines whose worlds are protected, who are put at risk, and who gets to decide what AI and its futures look like.\u00a0<\/p>\n\n\n\n If you are working on similar issues in the Global South or have information about emerging resistance or planning processes involving data centers and land or water rights, please get in touch – we are actively building a network of local collaborators and observers. <\/p>\n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" by Beatrice Bonami What comes to mind when we think about Artificial Intelligence (AI)? Shiny robots, super computers? Cutting edge laboratories in Asia and North America? What if we tell you that AI is far closer to us than we might realize? It’s present in the spam folder in our emails, in how we navigate social media, self-checkouts, driverless cars, and even when we hear from Call Centers “click 1 if you want to talk to an operator, we will transfer you.” Yes, AI is everywhere, and its structures are far from shiny or cutting edge, depending on the exploitation of data, labor, and natural resources. The real image of AI is closer to super infrastructures of data centers in the Brazilian desert. Artisanal mining sites in the Copper Belt. Crowded rooms with data workers in Kampala and Bangalore. Debatable server cluster locations in Colombian indigenous protected lands, which consume water and electric power that would be enough to sustain a town for months. These are the real outlooks when we think of AI: an industry that is far from being green and equitable, exploiting earth and humans as so many other industries do. Specifically, data centers are the backbone of AI, and their expansion in the Global South is creating serious socio-ecological injustices. These facilities consume large volumes of clean water for cooling, often competing with local public supply, strain electrical grids that must prioritize corporate demand over household access, and require vast tracts of land. While governments frame data centers as symbols of modernization and economic growth and couch them in digital sovereignty narratives, the benefits rarely materialize locally, leaving surrounding communities with the ecological cost of powering AI systems built elsewhere. Much of what we know about data centers concerns their quantifiable environmental impacts: water depletion, energy overuse, heat and e-waste, land conversion, and growing carbon footprints. What is still poorly understood is how these infrastructures affect the social, cultural, and ontological fabric of the places where they are built- how they reshape people\u2019s relationships to land, water, and belonging in ways that cannot be reduced to numbers alone. To study these less-visible effects, a multidisciplinary approach is essential, bringing together political ecology, actor-network theory, material semiotics, and assemblage theory to trace how AI infrastructures reorder human and more-than-human ecosystems. At Planetary AI, we are examining these dynamics through ethnographic fieldwork in multiple countries, e.g. Brazil, Chile, Colombia, Kenya, South Africa and India, documenting how communities experience and respond to data center developments.\u00a0Our approach begins with the premise that the environmental harms caused by data centres – such as water extraction, land enclosure, heat waste, and energy overuse – cannot be separated from their social, cultural, and political consequences. Environmental and climate justice issues are relevant here not simply because our natural ecosystems are being harmed, but because access to water, land, and energy is inseparable from histories of dispossession, claims to belonging, and the right of communities to define how they live and envision their future. In this sense, the expansion of AI\u2019s infrastructures is not just a technical or environmental issue, but a justice issue – one that determines whose worlds are protected, who are put at risk, and who gets to decide what AI and its futures look like.\u00a0 If you are working on similar issues in the Global South or have information about emerging resistance or planning processes involving data centers and land or water rights, please get in touch – we are actively building a network of local collaborators and observers. <\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[26],"tags":[],"class_list":["post-434","post","type-post","status-publish","format-standard","hentry","category-reflection"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/posts\/434","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/comments?post=434"}],"version-history":[{"count":2,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/posts\/434\/revisions"}],"predecessor-version":[{"id":436,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/posts\/434\/revisions\/436"}],"wp:attachment":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/media?parent=434"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/categories?post=434"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/tags?post=434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}