{"id":16195,"date":"2024-04-12T15:50:03","date_gmt":"2024-04-12T12:50:03","guid":{"rendered":"https:\/\/africasustainabilitymatters.com\/?p=16195"},"modified":"2026-01-11T05:31:38","modified_gmt":"2026-01-11T05:31:38","slug":"how-chatgpt-and-generative-ai-are-disrupting-sustainability","status":"publish","type":"post","link":"https:\/\/rayscohosting.best\/ASM\/2024\/04\/12\/how-chatgpt-and-generative-ai-are-disrupting-sustainability\/","title":{"rendered":"How ChatGPT and generative AI are disrupting sustainability"},"content":{"rendered":"

The burgeoning field of generative Artificial Intelligence (AI), while remarkable in its advancements, is drawing significant scrutiny over its environmental impact, particularly regarding water and energy consumption. An alarming examination reveals the extent to which tools like ChatGPT are contributing to this concern, as highlighted by Forbes, a University of California research study, and National Geographic.<\/span>\u00a0<\/span><\/p>\n

ChatGPT, developed by OpenAI, exemplifies this issue, consuming an astonishing over half a million kilowatts of electricity daily to handle around two hundred million requests. This level of energy consumption is nearly equivalent to the daily usage of 180,000 U.S. households. Furthermore, a single interaction with ChatGPT demands about fifty centiliters of water, akin to the volume of one plastic water bottle.<\/span>\u00a0<\/span><\/p>\n

Such figures are particularly troubling considering the rapid expansion of generative AI (genAI) product innovations, not only from OpenAI but also from tech giants and new players like Amazon, Anthropic, Cohere, Microsoft, and Nvidia. The overall electricity consumption of the AI industry is on track to soar, with estimates suggesting it could reach between 85-134 terawatt-hours (TWh) annually by 2027.<\/span>\u00a0<\/span><\/p>\n

Read also: Advancing AI for sustainable development<\/a><\/strong><\/p>\n

A policy report from the Organisation for Economic Co-operation and Development (OECD) sheds light on the varying water footprints of AI, which differ substantially based on the geographic location of its training and hosting. In Microsoft\u2019s global data centers, for instance, AI’s water usage ranges from 1.8 to 12 liters per kilowatt-hour of energy consumed. This variance underscores the pressing need for more water-efficient genAI infrastructures and the development of energy-efficient technological innovations.<\/span>\u00a0<\/span><\/p>\n

Water, humanity\u2019s most critical and scarce resource, accounts for merely 2.5% of the planet’s total volume, with over half of that being frozen. Given that agriculture consumes 70% of our accessible freshwater, the looming water scarcity by 2050\u2014expected to affect two-thirds of the global population\u2014highlights the urgent need for sustainable practices. This scenario paints a stark picture of the challenges lying ahead in balancing technological innovation with environmental stewardship.<\/span>\u00a0<\/span><\/p>\n

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The discourse calls for immediate action from government leaders, board directors, and CEOs to pressure technology companies towards more sustainable and ethical practices. As the OECD newsletter emphasizes, the involvement of the public in AI policy matters is crucial to fostering a responsible approach to the development and deployment of AI technologies, ensuring that the march towards innovation does not come at the expense of our planet\u2019s most vital resources.<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

The burgeoning field of generative Artificial Intelligence (AI), while remarkable in its advancements, is drawing significant scrutiny over its environmental impact, particularly regarding water and energy consumption. An alarming examination…<\/p>\n","protected":false},"author":12,"featured_media":16196,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","pagelayer_contact_templates":[],"_pagelayer_content":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[118],"tags":[1327],"class_list":["post-16195","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-sustainability-of-ai"],"_links":{"self":[{"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/posts\/16195","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/comments?post=16195"}],"version-history":[{"count":0,"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/posts\/16195\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/media\/16196"}],"wp:attachment":[{"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/media?parent=16195"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/categories?post=16195"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rayscohosting.best\/ASM\/wp-json\/wp\/v2\/tags?post=16195"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}