{"id":79,"date":"2024-11-25T09:53:05","date_gmt":"2024-11-25T09:53:05","guid":{"rendered":"https:\/\/planetaryai.net\/staging\/4545\/?page_id=79"},"modified":"2025-02-11T16:46:53","modified_gmt":"2025-02-11T16:46:53","slug":"about","status":"publish","type":"page","link":"https:\/\/planetaryai.net\/staging\/4545\/about\/","title":{"rendered":"About"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"79\" class=\"elementor elementor-79\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9911f76 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"9911f76\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-93b0778 elementor-widget elementor-widget-heading\" data-id=\"93b0778\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Overview<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9639fc2 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"9639fc2\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;shape_divider_bottom&quot;:&quot;book&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-shape elementor-shape-bottom\" aria-hidden=\"true\" data-negative=\"false\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 1000 100\" preserveAspectRatio=\"none\">\n\t<path class=\"elementor-shape-fill\" d=\"M194,99c186.7,0.7,305-78.3,306-97.2c1,18.9,119.3,97.9,306,97.2c114.3-0.3,194,0.3,194,0.3s0-91.7,0-100c0,0,0,0,0-0 L0,0v99.3C0,99.3,79.7,98.7,194,99z\"\/>\n<\/svg>\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d198206 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"d198206\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"800\" height=\"534\" src=\"https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?fit=800%2C534&amp;ssl=1\" class=\"attachment-large size-large wp-image-84\" alt=\"\" srcset=\"https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?w=2560&amp;ssl=1 2560w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?resize=300%2C200&amp;ssl=1 300w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?resize=1024%2C683&amp;ssl=1 1024w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?resize=768%2C512&amp;ssl=1 768w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?resize=1536%2C1024&amp;ssl=1 1536w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?resize=2048%2C1365&amp;ssl=1 2048w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?w=1600&amp;ssl=1 1600w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/sergey-zolkin-_UeY8aTI6d0-unsplash-scaled.jpg?w=2400&amp;ssl=1 2400w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-20fff1b elementor-widget elementor-widget-text-editor\" data-id=\"20fff1b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span class=\"TextRun SCXW49044084 BCX2\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW49044084 BCX2\">Some advocates proclaim AI as \u2018the greatest technology humanity has yet developed\u2019 and claim it will reshape our society. Others say AI will contribute about US$ 15 trillion (<\/span><span class=\"NormalTextRun SCXW49044084 BCX2\">roughly the<\/span><span class=\"NormalTextRun SCXW49044084 BCX2\"> size of the EU economy) to the global economy by 2030. Yet, AI <\/span><span class=\"NormalTextRun SCXW49044084 BCX2\">remains<\/span><span class=\"NormalTextRun SCXW49044084 BCX2\"> an enigma: little is known about where and how AI systems are made, who are the key actors involved, and what are the socio-economic and ecological costs associated with AI.\u00a0<\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-3d1ad73 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"3d1ad73\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;shape_divider_bottom&quot;:&quot;book&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-shape elementor-shape-bottom\" aria-hidden=\"true\" data-negative=\"false\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 1000 100\" preserveAspectRatio=\"none\">\n\t<path class=\"elementor-shape-fill\" d=\"M194,99c186.7,0.7,305-78.3,306-97.2c1,18.9,119.3,97.9,306,97.2c114.3-0.3,194,0.3,194,0.3s0-91.7,0-100c0,0,0,0,0-0 L0,0v99.3C0,99.3,79.7,98.7,194,99z\"\/>\n<\/svg>\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d539751 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"d539751\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"550\" src=\"https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?fit=800%2C550&amp;ssl=1\" class=\"attachment-large size-large wp-image-82\" alt=\"\" srcset=\"https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?w=2560&amp;ssl=1 2560w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?resize=300%2C206&amp;ssl=1 300w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?resize=1024%2C704&amp;ssl=1 1024w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?resize=768%2C528&amp;ssl=1 768w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?resize=1536%2C1056&amp;ssl=1 1536w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?resize=2048%2C1408&amp;ssl=1 2048w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?w=1600&amp;ssl=1 1600w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2024\/11\/immo-wegmann-raLWowGMCWw-unsplash-scaled.jpg?w=2400&amp;ssl=1 2400w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32b9100 elementor-widget elementor-widget-text-editor\" data-id=\"32b9100\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span class=\"TextRun SCXW49044084 BCX2\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW49044084 BCX2\">AI systems often thought to be automated are <span class=\"NormalTextRun AdvancedProofingIssueV2Themed SCXW49044084 BCX2\">actually dependent<\/span> on human workers labelling and cleaning data to train algorithms when they give incorrect answers. ChatGPT and driverless cars would not exist without this behind-the-scenes human labour for AI. Large Silicon Valley firms rely on the outsourcing of data enrichment tasks (commonly known as \u2018data work\u2019) to different parts of the planet via a host of suppliers and labour platforms. Thus data work value chains (different stages of production, and distribution of goods) can go anywhere across the planet both to Global North countries (i.e., high-income) such as the United States and the United Kingdom and Global South (i.e., low and middle-income) such as India, Colombia and Kenya, among host of others. The project will map these data work value chains to show how the planetary AI systems are made.<br \/><\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-38f9bba e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"38f9bba\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-19c5cf5 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"19c5cf5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"530\" src=\"https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?fit=800%2C530&amp;ssl=1\" class=\"attachment-large size-large wp-image-365\" alt=\"\" srcset=\"https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?w=2560&amp;ssl=1 2560w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?resize=300%2C199&amp;ssl=1 300w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?resize=1024%2C678&amp;ssl=1 1024w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?resize=768%2C509&amp;ssl=1 768w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?resize=1536%2C1017&amp;ssl=1 1536w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?resize=2048%2C1356&amp;ssl=1 2048w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?w=1600&amp;ssl=1 1600w, https:\/\/i0.wp.com\/planetaryai.net\/staging\/4545\/wp-content\/uploads\/2025\/02\/immo-wegmann-7wrmNM0f2FI-unsplash-scaled.jpeg?w=2400&amp;ssl=1 2400w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b7089b2 elementor-widget elementor-widget-text-editor\" data-id=\"b7089b2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI systems are also deeply material in nature. Not only they depend on planetary networks of resource extraction from DRC to Chile to Indonesia, they require large physical infrastructures such as data centres that are rapidly emerging. These data centres are implicated in diverting million of gallons of water and tremendous amount of electricity away from communities affecting lives and livelihoods of people living nearby. This project studies the environmental costs associated with data centres and resistance to them in the Global South.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-87aef6a e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"87aef6a\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-89d32e0 elementor-align-start elementor-widget__width-initial elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"89d32e0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-search\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M505 442.7L405.3 343c-4.5-4.5-10.6-7-17-7H372c27.6-35.3 44-79.7 44-128C416 93.1 322.9 0 208 0S0 93.1 0 208s93.1 208 208 208c48.3 0 92.7-16.4 128-44v16.3c0 6.4 2.5 12.5 7 17l99.7 99.7c9.4 9.4 24.6 9.4 33.9 0l28.3-28.3c9.4-9.4 9.4-24.6.1-34zM208 336c-70.7 0-128-57.2-128-128 0-70.7 57.2-128 128-128 70.7 0 128 57.2 128 128 0 70.7-57.2 128-128 128z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">i.    In the context of an emerging AI and development agenda, the overall objective of the project is to develop grounded theoretical and analytical insights into the production networks of AI by placing data work and data centres at the centre of its enquiry. <\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-people-arrows\" viewBox=\"0 0 576 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M96,128A64,64,0,1,0,32,64,64,64,0,0,0,96,128Zm0,176.08a44.11,44.11,0,0,1,13.64-32L181.77,204c1.65-1.55,3.77-2.31,5.61-3.57A63.91,63.91,0,0,0,128,160H64A64,64,0,0,0,0,224v96a32,32,0,0,0,32,32V480a32,32,0,0,0,32,32h64a32,32,0,0,0,32-32V383.61l-50.36-47.53A44.08,44.08,0,0,1,96,304.08ZM480,128a64,64,0,1,0-64-64A64,64,0,0,0,480,128Zm32,32H448a63.91,63.91,0,0,0-59.38,40.42c1.84,1.27,4,2,5.62,3.59l72.12,68.06a44.37,44.37,0,0,1,0,64L416,383.62V480a32,32,0,0,0,32,32h64a32,32,0,0,0,32-32V352a32,32,0,0,0,32-32V224A64,64,0,0,0,512,160ZM444.4,295.34l-72.12-68.06A12,12,0,0,0,352,236v36H224V236a12,12,0,0,0-20.28-8.73L131.6,295.34a12.4,12.4,0,0,0,0,17.47l72.12,68.07A12,12,0,0,0,224,372.14V336H352v36.14a12,12,0,0,0,20.28,8.74l72.12-68.07A12.4,12.4,0,0,0,444.4,295.34Z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">ii.  To develop and apply innovative methodological tools combining multidisciplinary approaches from geography, anthropology, political ecology, computational data science, etc to investigate value chains of AI.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-user-cog\" viewBox=\"0 0 640 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M610.5 373.3c2.6-14.1 2.6-28.5 0-42.6l25.8-14.9c3-1.7 4.3-5.2 3.3-8.5-6.7-21.6-18.2-41.2-33.2-57.4-2.3-2.5-6-3.1-9-1.4l-25.8 14.9c-10.9-9.3-23.4-16.5-36.9-21.3v-29.8c0-3.4-2.4-6.4-5.7-7.1-22.3-5-45-4.8-66.2 0-3.3.7-5.7 3.7-5.7 7.1v29.8c-13.5 4.8-26 12-36.9 21.3l-25.8-14.9c-2.9-1.7-6.7-1.1-9 1.4-15 16.2-26.5 35.8-33.2 57.4-1 3.3.4 6.8 3.3 8.5l25.8 14.9c-2.6 14.1-2.6 28.5 0 42.6l-25.8 14.9c-3 1.7-4.3 5.2-3.3 8.5 6.7 21.6 18.2 41.1 33.2 57.4 2.3 2.5 6 3.1 9 1.4l25.8-14.9c10.9 9.3 23.4 16.5 36.9 21.3v29.8c0 3.4 2.4 6.4 5.7 7.1 22.3 5 45 4.8 66.2 0 3.3-.7 5.7-3.7 5.7-7.1v-29.8c13.5-4.8 26-12 36.9-21.3l25.8 14.9c2.9 1.7 6.7 1.1 9-1.4 15-16.2 26.5-35.8 33.2-57.4 1-3.3-.4-6.8-3.3-8.5l-25.8-14.9zM496 400.5c-26.8 0-48.5-21.8-48.5-48.5s21.8-48.5 48.5-48.5 48.5 21.8 48.5 48.5-21.7 48.5-48.5 48.5zM224 256c70.7 0 128-57.3 128-128S294.7 0 224 0 96 57.3 96 128s57.3 128 128 128zm201.2 226.5c-2.3-1.2-4.6-2.6-6.8-3.9l-7.9 4.6c-6 3.4-12.8 5.3-19.6 5.3-10.9 0-21.4-4.6-28.9-12.6-18.3-19.8-32.3-43.9-40.2-69.6-5.5-17.7 1.9-36.4 17.9-45.7l7.9-4.6c-.1-2.6-.1-5.2 0-7.8l-7.9-4.6c-16-9.2-23.4-28-17.9-45.7.9-2.9 2.2-5.8 3.2-8.7-3.8-.3-7.5-1.2-11.4-1.2h-16.7c-22.2 10.2-46.9 16-72.9 16s-50.6-5.8-72.9-16h-16.7C60.2 288 0 348.2 0 422.4V464c0 26.5 21.5 48 48 48h352c10.1 0 19.5-3.2 27.2-8.5-1.2-3.8-2-7.7-2-11.8v-9.2z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">iii.   To produce original empirical evidence showcasing (a) different types of data work, actors, and its implications on local labour markets and workers and (b) various socio-environmental costs associated with data centres in the Global South.  <\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-map-pin\" viewBox=\"0 0 288 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M112 316.94v156.69l22.02 33.02c4.75 7.12 15.22 7.12 19.97 0L176 473.63V316.94c-10.39 1.92-21.06 3.06-32 3.06s-21.61-1.14-32-3.06zM144 0C64.47 0 0 64.47 0 144s64.47 144 144 144 144-64.47 144-144S223.53 0 144 0zm0 76c-37.5 0-68 30.5-68 68 0 6.62-5.38 12-12 12s-12-5.38-12-12c0-50.73 41.28-92 92-92 6.62 0 12 5.38 12 12s-5.38 12-12 12z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">iv.    To study production networks of AI in India, Colombia, Kenya and Uganda. <\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-globe-africa\" viewBox=\"0 0 496 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M248 8C111.03 8 0 119.03 0 256s111.03 248 248 248 248-111.03 248-248S384.97 8 248 8zm160 215.5v6.93c0 5.87-3.32 11.24-8.57 13.86l-15.39 7.7a15.485 15.485 0 0 1-15.53-.97l-18.21-12.14a15.52 15.52 0 0 0-13.5-1.81l-2.65.88c-9.7 3.23-13.66 14.79-7.99 23.3l13.24 19.86c2.87 4.31 7.71 6.9 12.89 6.9h8.21c8.56 0 15.5 6.94 15.5 15.5v11.34c0 3.35-1.09 6.62-3.1 9.3l-18.74 24.98c-1.42 1.9-2.39 4.1-2.83 6.43l-4.3 22.83c-.62 3.29-2.29 6.29-4.76 8.56a159.608 159.608 0 0 0-25 29.16l-13.03 19.55a27.756 27.756 0 0 1-23.09 12.36c-10.51 0-20.12-5.94-24.82-15.34a78.902 78.902 0 0 1-8.33-35.29V367.5c0-8.56-6.94-15.5-15.5-15.5h-25.88c-14.49 0-28.38-5.76-38.63-16a54.659 54.659 0 0 1-16-38.63v-14.06c0-17.19 8.1-33.38 21.85-43.7l27.58-20.69a54.663 54.663 0 0 1 32.78-10.93h.89c8.48 0 16.85 1.97 24.43 5.77l14.72 7.36c3.68 1.84 7.93 2.14 11.83.84l47.31-15.77c6.33-2.11 10.6-8.03 10.6-14.7 0-8.56-6.94-15.5-15.5-15.5h-10.09c-4.11 0-8.05-1.63-10.96-4.54l-6.92-6.92a15.493 15.493 0 0 0-10.96-4.54H199.5c-8.56 0-15.5-6.94-15.5-15.5v-4.4c0-7.11 4.84-13.31 11.74-15.04l14.45-3.61c3.74-.94 7-3.23 9.14-6.44l8.08-12.11c2.87-4.31 7.71-6.9 12.89-6.9h24.21c8.56 0 15.5-6.94 15.5-15.5v-21.7C359.23 71.63 422.86 131.02 441.93 208H423.5c-8.56 0-15.5 6.94-15.5 15.5z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">v.     To co-produce findings from the Global South and adopt a diverse range of dissemination strategies across multiple audiences and platforms. <\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-user-graduate\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M319.4 320.6L224 416l-95.4-95.4C57.1 323.7 0 382.2 0 454.4v9.6c0 26.5 21.5 48 48 48h352c26.5 0 48-21.5 48-48v-9.6c0-72.2-57.1-130.7-128.6-133.8zM13.6 79.8l6.4 1.5v58.4c-7 4.2-12 11.5-12 20.3 0 8.4 4.6 15.4 11.1 19.7L3.5 242c-1.7 6.9 2.1 14 7.6 14h41.8c5.5 0 9.3-7.1 7.6-14l-15.6-62.3C51.4 175.4 56 168.4 56 160c0-8.8-5-16.1-12-20.3V87.1l66 15.9c-8.6 17.2-14 36.4-14 57 0 70.7 57.3 128 128 128s128-57.3 128-128c0-20.6-5.3-39.8-14-57l96.3-23.2c18.2-4.4 18.2-27.1 0-31.5l-190.4-46c-13-3.1-26.7-3.1-39.7 0L13.6 48.2c-18.1 4.4-18.1 27.2 0 31.6z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">vi.     Build capacity among early career researchers across the Global South. <\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-58d30b3 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"58d30b3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Aims and Objectives<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-a9d97a0 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"a9d97a0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f3f21f5 elementor-widget elementor-widget-heading\" data-id=\"f3f21f5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Want to learn more?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-db4f3b4 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"db4f3b4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"\/about\/team\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Meet the Team<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Overview Some advocates proclaim AI as \u2018the greatest technology humanity has yet developed\u2019 and claim it will reshape our society. Others say AI will contribute about US$ 15 trillion (roughly the size of the EU economy) to the global economy by 2030. Yet, AI remains an enigma: little is known about where and how AI systems are made, who are the key actors involved, and what are the socio-economic and ecological costs associated with AI.\u00a0 AI systems often thought to be automated are actually dependent on human workers labelling and cleaning data to train algorithms when they give incorrect answers. ChatGPT and driverless cars would not exist without this behind-the-scenes human labour for AI. Large Silicon Valley firms rely on the outsourcing of data enrichment tasks (commonly known as \u2018data work\u2019) to different parts of the planet via a host of suppliers and labour platforms. Thus data work value chains (different stages of production, and distribution of goods) can go anywhere across the planet both to Global North countries (i.e., high-income) such as the United States and the United Kingdom and Global South (i.e., low and middle-income) such as India, Colombia and Kenya, among host of others. The project will map these data work value chains to show how the planetary AI systems are made. AI systems are also deeply material in nature. Not only they depend on planetary networks of resource extraction from DRC to Chile to Indonesia, they require large physical infrastructures such as data centres that are rapidly emerging. These data centres are implicated in diverting million of gallons of water and tremendous amount of electricity away from communities affecting lives and livelihoods of people living nearby. This project studies the environmental costs associated with data centres and resistance to them in the Global South.\u00a0 i. In the context of an emerging AI and development agenda, the overall objective of the project is to develop grounded theoretical and analytical insights into the production networks of AI by placing data work and data centres at the centre of its enquiry. ii. To develop and apply innovative methodological tools combining multidisciplinary approaches from geography, anthropology, political ecology, computational data science, etc to investigate value chains of AI. iii. To produce original empirical evidence showcasing (a) different types of data work, actors, and its implications on local labour markets and workers and (b) various socio-environmental costs associated with data centres in the Global South. iv. To study production networks of AI in India, Colombia, Kenya and Uganda. v. To co-produce findings from the Global South and adopt a diverse range of dissemination strategies across multiple audiences and platforms. vi. Build capacity among early career researchers across the Global South. Aims and Objectives Want to learn more? Meet the Team<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"nf_dc_page":"","footnotes":""},"class_list":["post-79","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/pages\/79","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/comments?post=79"}],"version-history":[{"count":20,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/pages\/79\/revisions"}],"predecessor-version":[{"id":368,"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/pages\/79\/revisions\/368"}],"wp:attachment":[{"href":"https:\/\/planetaryai.net\/staging\/4545\/wp-json\/wp\/v2\/media?parent=79"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}