Artificial intelligence (AI) is often announced as a force of progress, stimulating innovation, economic growth and unprecedented efficiency. Technology giants boast of the potential of AI to revolutionize industries, stimulate productivity and even resolve urgent global challenges such as climate change. But under this utopian account is a darker reality – that where the economic rewards of the AI are concentrated in the northern worldwide, while its exploitation of work and its environmental destruction are outsourced in the world. From workers exploited behind the sets of AI training data to the environmental costs of massive data centers, the expansion of AI strengthens the historical models of inequality. Rather than creating a democratized technological future, AI deepens the world divide – what I call AI colonialism – where the advantages accumulate a few while the charges are outsourced to the most vulnerable.
Despite the perception that the AI operates independently, technology is strongly based on human work, in particular, low -wage workers in the world South who make data labeling, moderation of content and Other tedious digital tasks. In countries like Kenya, India and the Philippines, millions of workers return through large amounts of data to form AI models, gaining as little as $ 1.50 an hour under precarious conditions of concerts. The nature of their work can be exhausting. Kenyan content moderators used by subcontractors for platforms like Facebook and Tiktok spend hours examining violent and disturbing materials, often suffering from psychological trauma with little or no mental health support. In India, the trainers of IA Annot images, transcribe text and report inappropriate content – all essential for refining automatic learning algorithms – but they are treated as disposable, rejected stable contracts, fair wages and protections legal.
While the leaders of the Silicon Valley collect enormous benefits, the work which fuels the development of the AI remains invisible. The AI is not simply a neutral technological tool – it is anchored in a global operating system which reflects past colonial work structures, extracted the value of the world South while keeping its marginalized workers.
The AI is not only built on a cheap workforce – it is also built on narcotic environmental costs, worn disproportionate by developing countries. The formation of large -scale AI models requires massive calculation power, leading to high energy consumption and carbon emissions. A single model of AI like the GPT-3 of Openai can emit as many CO2 as five cars over their lives. This energy demand stimulates the rapid expansion of data centers, especially in regions where electricity and land are cheap, often in the world. Countries like South Africa, Indonesia and Brazil have become hubs for AI infrastructure, but at a devastating cost. These data centers require large amounts of water for cooling, exacerbating water shortage problems, while their massive electricity consumption often depends on fossil fuels, the increase in carbon footprints.
Meanwhile, the extraction of rare minerals for AI equipment – such as cobalt, nickel and lithium – plus the anchored environment. In the Democratic Republic of Congo, where more than 70% of the world cobalt is exploited, workers endure inhuman conditions in dangerous and unregulated mines, often with children among the workforce. Minor operations similar to the Philippines and Latin America have led to deforestation, water contamination and forced trips to Aboriginal communities. These environmental consequences are not also carried. The Northern worldwide benefits from the Halls and economic growth of the AI while the climate burden falls disproportionately on the world South, which communities are already confronted with serious climatic vulnerabilities. It is the brand of Necroexportation brand – a system where technological prosperity in a part of the world is maintained by the systematic damage of another.
However, some efforts to AI governance are already underway. As a first full regulatory framework on artificial intelligence, the European Union AI Act aims to manage the risk of AI, guarantee transparency and regulate high -risk AI applications. Its jurisdiction, however, is limited to Europe, leaving aside the vast majority of AI workers, suppliers of resources and communities affected by the environmental degradation led by AI. Likewise, the voluntary principles of OECD AI and UNESCO emphasize ethical AI but lack application mechanisms, allowing large technological companies to continue their operating practices without consequences (Principles of OECD AI).
Therefore, a really fair AI system must go beyond regional regulations. Global governance efforts must seek to orchestrate all relevant stakeholders to the following four objectives: First, apply global work protections: AI must not be built on working conditions similar to a Misery workshop in Kenya , in India or Venezuela. The International Labor Organization (ILO) must establish global labor standards of binding AI, guarantee equitable wages, labor safety protections and collective negotiation rights for workers of the Ia.
Second, the mandate of the ethical supply of AI material: cobalt, nickel and lithium – critical components of the infrastructure of AI – must be ethically coming, with strict human rights laws to warn child labor, dangerous working conditions and conflicts of violent resources.
Third, regulating the carbon footprint of AI: the environmental impact of AI is worse than most industries admit it. Data centers are now consuming more electricity than whole countries, and their emissions are 662% higher than those reported by Big Tech. AI regulations must include carbon ceilings, compulsory transparency on emissions and investments in carbon neutral training techniques.
Fourth, ensuring the transfer of technology in the world South: the power over the AI industry is concentrated in the hands of a few rich companies in the Northern worldwide, while strengthening technological dependence in developing countries. Instead of extracting resources and work while keeping an expertise in AI confined to Silicon Valley, the world South must be authorized by technology transfer agreements, financing for IA research and development of ‘Inclusive AI infrastructure.
For too long, AI was presented as an engine of economic prosperity and progress, with little recognition of human suffering and the ecological destruction it perpetuates. However, technology does not exist in a vacuum; Rather, it reflects the political, economic and ethical choices of those who develop and control it. AI does not have to function as a tool of digital colonialism, but unless its structural inequalities are treated, this is exactly what it will remain.
The future of AI should not be built on the back of exploited workers, poisoned environments and in -depth global inequalities. Instead, it must be designed as a really fair and lasting technology, where its advantages are fairly shared, its costs are quite distributed and its governance prioritizes human dignity and planetary survival. It is not a technological challenge – it is moral and political. The dismantling of colonialism of AI requires a fundamental redress of who serves AI, who takes advantage of it and who pays the price of its expansion. It is time for governments, institutions and civil society to demand responsibility – to reject an economy of extractive AI and to build one which serves humanity, not only the elites. A future where AI is really ethical, sustainable and is simply possible – only if we demand it.
References
Cho, R. (2023). Crush carbon footprint of AI. Columbia Climate School. Extract from https://news.climate.columbia.edu/2023/06/09/ais-growing-carbon-footprint/
European Commission. (2024). The AI Act: the very first legal framework on AI. Extract from https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence
Fairwork Project. (2023). Fairwork Cloudwork Ratings 2023: working on the planetary labor market. Extract from https://fair.work/wp-content/uploads/sites/17/2023/07/fairork-cloudwork-ratings-2023-red.pdf
HAO, K. (2019). The formation of a single model of AI can emit as much carbon as five cars during their lifetime. MIT review review. Extract from https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their- lifetime /
Haskins, C. (2024). Humans little paid behind the intelligence of AI ask Biden to release them from “modern slavery”. Cable. Extract from https://www.wired.com/story/low-paid-humans-ai-biden-modern-ay-slavery/
International Labor Organization (ILO). (2023). AI and generative jobs: a global analysis of potential effects on quantity and quality of work. Extract from https://www.ilo.org/global/publications/working-ppers/wcms_895344/lang-en/index.htm
Jones, E. and EasterDay, B. (2022). Environmental costs and promises of artificial intelligence. Council of foreign relations. Extract from https://www.cfr.org/blog/artificial-intelligence-environment-costs-and
Abell, A. (2019). Necropolitical. Duke University Press.
Muldoon, J., Cant, C., Graham, M. and Utek Spilda, F. (2023). Ethical AI poverty: impact supply and IA supply chains. Ai and society. Extract from https://doi.org/10.1007/s00146-023-01824-9
Oxford Insights. (2023). AI preparation index of the 2023 government. Extract from https://oxfordinsights.com/wp-content/uploads/2023/12/2023-government-ai-regniss-index-2.pdf
OPENAI. (2019). Energy and political considerations for in -depth learning in AI. Extract from https://arxiv.org/abs/1906.02243
Pogrebna, G. (2024). AI has supported by the development of a worker of global technology “slavery”. Asia Times. Extract from https://asiatimes.com/2024/10/ai—ndernderpinned-by-developing-world-techworker-slavery/
Regilme, SSF (2024). Colonialism of artificial intelligence: environmental damage, labor exploitation and human rights crises in the world South. International Affairs SAI review 44(2), 75-92. https://dx.doi.org/10.1353/sais.2024.a950958.
Rowe, N. (2023). Minor workers form AI. Cable. Extract from https://www.wired.com/story/artificial-intelligence-data-nabeling-children/
The goalkeeper. (2024). Ex-Facebook content moderator in Kenya continues Meta on poor working conditions. Africa News. Extract from https://www.africanews.com/2022/05/10/ex-facebook-content-moderator-in-kenya-sues-meta-poor-Working-conditions/
The United Nations. (2024). The General Assembly adopts the historical resolution of the Directorate of Artificial Intelligence to World Good. Extract from https://press.un.org/en/2024/ga12588.doc.htm
Zuboff, S. (2019). The age of surveillance capitalism: the struggle for a human future at the new border of power. PUBLICAFFAIRES.
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