Is the greatest threat from artificial intelligence (AI) job loss, privacy violations, or algorithmic bias? Or is it a new form of colonialism? AI is revolutionizing everything we do, at the same time, it is quietly introducing a form of digital imperialism. This essay examines the urgent but often overlooked topic of "AI colonialism".
AI colonialism refers to the fact that powerful nations extract wealth from poorer countries, and the benefits of AI mostly belong to the wealthy countries. This pattern of exploitation has been documented in academic research. For example, Mohamed et al. (2020) found that wealthy nations make their AI advancements by exploiting resources and labor from developing nations.
AI hardware requires specific raw materials — silicon for semiconductors, rare earth elements for high-performance magnets, and metals such as gold and silver for electronic components. Crawford (2021) demonstrated in the analysis of AI's material foundations that these resources are predominantly mined in resource-abundant but economically disadvantaged countries. Because there is no insufficient infrastructure to process these materials locally, these nations have to rely on wealthy countries and receive minimal financial or technological advantages from their natural wealth.
One example of this imbalance is cobalt, which is an essential raw material for AI systems batteries. The Democratic Republic of Congo (DRC) supplies about 70 percent of the world’s cobalt. Amnesty International's 2019 report mentioned that workers in Congo receive low wages and work under dangerous conditions. This is similar to historical colonialism when wealth flowed to the wealthy countries, and developing countries relied on raw materials exports. As a result, buyers from wealthy nations dominate both technology development and final AI offerings.
Why developing countries don’t develop their own AI products? Because the AI industry has a high barrier to entry due to high cost. PwC (2022) estimates that AI will boost the global economy by around $15.7 trillion by 2030, but most gains will be concentrated in North America and China. Global inequality is at risk of worsening because of such economic concentration. According to Lee (2021), without proactive international cooperation, AI-driven growth could significantly exacerbate economic divides between regions.
Beyond physical resources, a new form of labor extraction has emerged: AI “ghost workers” (Gray and Suri, 2019). Data-labeling workers in Venezuela and other economically struggling nations receive minimal wages for annotating AI-related data such as self-driving cars. This invisible workforce receives little of the technology's benefits while powering AI's cognitive capabilities. Under Article 23 of the Universal Declaration of Human Rights, everyone has the right to "an existence worthy of human dignity." Creating a digital underclass whose labor is systematically undervalued directly compromises these established rights.
The languages, cultural norms, and social values used to train AI models reflect the value systems of the AI tech powers. Bender et al. (2021) demonstrate how Large Language Models (LLMs) like ChatGPT are trained on information derived predominantly from Western cultures, and marginalized other perspectives. Just as historical colonialism suppressed indigenous languages and cultural practices, AI development risks eroding cultural diversity.
These human rights issues are compounded by the digital divide. The GSMA (Groupe Speciale Mobile Association) 2023 report states that in Africa, only 22 percent of people have cell phones, and of those, only 30-40 percent have access to 4G networks. Sampath (2021) describes this as a type of "digital apartheid," which could result in a human rights crisis in the near future. In the crisis, certain communities are systematically left behind as society advances technologically. This exclusion includes rights to education, economic opportunity, and participation in cultural life as guaranteed by the International Covenant on Economic, Social, and Cultural Rights.
To balance technological innovation with human rights, we must fundamentally transform AI's global development.
Supporting Local Innovation: Local innovation can thrive when properly supported and recognized. DataProphet is a South African AI startup. According to Access Partnership (2022), DataProphet created deep learning models that help optimize manufacturing production. By serving clients globally, DataProphet demonstrates that technological capacity can emerge from regions traditionally excluded from technology leadership. However, such success stories remain exceptions rather than the norm, and they show the importance of structural changes to support similar initiatives.
Rights-centered National AI Strategies: The National AI Strategy of Kenya is a model of how a country can advance its technology investments while protecting citizens’ rights (Gwagwa et al., 2021). It acknowledges the role of local datasets and ethical AI development. It could be a model for how different stakeholders can work together to determine the ways that AI systems affect human rights and cultural contexts.
International Ethical Frameworks: The 2021 UNESCO Recommendation on the Ethics of Artificial Intelligence establishes an international AI development framework that respects human rights. Such frameworks are crucial for bias mitigation and ensuring AI fairness at every stage of its lifecycle. However, the effectiveness of these AI frameworks is highly dependent on their adoption and enforcement.
Democratizing AI Benefits: To distribute AI’s benefits fairly, alternative ownership models like open-source AI initiatives, cooperative structures, and technology-sharing programs should be encouraged (Pasquale, 2020). Significant policy support and corporate engagement are necessary to operationalize these models widely (Zuboff, 2019).
Participatory AI Design: Meaningful community involvement in AI design enhances both innovation and rights protection (McGregor et al., 2019). Embracing participatory approaches can challenge top-down models, ensuring AI technologies are inclusive and equitable (Birhane, 2021).
We do not have to repeat past patterns of exploitation. Technology can serve humanity broadly by prioritizing education, infrastructure, and fair policies. Addressing structural inequalities requires confronting and reshaping current economic models that are driving AI development (Couldry & Mejias, 2019).
While technology transfer and foreign investment might provide short-term benefits, these must not overshadow the longer-term implications of dependency and exploitation. True equity involves building local capacity and ensuring fair distribution of AI’s global gains (Kwet, 2019).
Reclaiming human rights in the age of AI colonialism requires rethinking who develops technology, who owns it, and who benefits. The next decade is crucial: will AI reinforce global inequalities, or expand dignity and opportunity for all?
The answer lies not in algorithms but in human choices. In order to break away from historical cycles of exploitation, we need to center human rights and empower marginalized communities. Let’s shape an AI future that benefits humanity in all its diversity!
References
Access Partnership. (2022). Artificial intelligence for Africa: An opportunity for growth, development, and democratisation. Retrieved from https://www.accesspartnership.com/ai-for-africa/
Amnesty International. (2019). This is what we die for: Human rights abuses in the Democratic Republic of the Congo power the global trade in cobalt. Retrieved from https://www.amnesty.org/en/documents/afr62/3183/2016/en/
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610-623.
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Sampath, P. G. (2021). Regulating digital platforms for the common good: Policy options for developing countries. South Centre Research Paper 129.
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