For millions in developing nations, tech giants from the Global North are increasingly controlling digital infrastructure, collecting data, and profiting from the labor in ways that mirror historic colonial exploitation. This practice, known as data colonialism, raises various questions about fairness, sovereignty, and the future of digital development.
Defining Data Colonialism
“Data colonialism” represents a newer age of resource extraction, where major technology companies from the Global North exploit the Global South’s labor, data, and resources without providing equal compensation, exerting control over the digital infrastructure and personal data of developing countries, mirroring notable historical exploitation (ICT-Works). In historical colonialism, resources were extracted from colonized territories to benefit the colonizers, often forced with arbitrary control. In the digital age, data has become a vital resource for nations, and its control and exploitation is incredibly important.
The Global South has been regarded with concerns over data exploitation and unequal exchanges, exacerbating existing regional inequalities (UNESCO). Corporations and governments in the Global North typically control the infrastructure, and data processing capabilities, while the Global South handles the data production, with limited control on how their data is used. The uneven distribution of digital power also increases dependency and reliance on the Global North, hindering digital development for the Global South. Many UN observers state that the digital dependencies caused by data colonialism deepens inequality, noting that Africa has less than 1% of global data centre capacity and holds less than 1,000 GPUs, the processors that AI depend on (Financial Times).
The Exploitation
Mimicking historic colonial practices, the extractive relationships that developing nations are locked into, offer lucrative services while their citizens’ data is harvested without fair compensation. In 2016, Facebook’s Free Basics program in Africa and India aimed to offer free or low-cost services, however, it only funneled users into gated ecosystems where their data was monetized unfairly (The Guardian). A more recent example is WhatsApp’s 2021 privacy update where users, particularly those in markets like India or Brazil, were forced to accept intrusive data-sharing terms with Meta, or risk losing app functionality. Users surrendered metadata, contact lists, device info, usage patterns, and other private data. This example shows how monopolistic market position creates unfair data extraction with no accountability, leaving people helpless (Boston Review).
Another example of data colonialism lies in the discussion on AI labor exploitation across the Global South. In Kenya and Venezuela, local workers earn as little as $1.50 per hour to perform psychologically taxing tasks like content moderation and data annotation for large tech companies based in the Global North, deploying AI systems trained on their labor but redirecting profits elsewhere. Additionally, since human data specialists are needed to manually label content types, many companies use “ghost work” to accomplish this. Ghost work involves exploiting cheap labor from Venezuela to manually label graphic content types (Daily AI).
In Africa, data colonialism and exploitation can also be seen. Kenyan workers that moderate ChatGPT content were exposed to graphic and traumatic material without adequate support, resembling a “content moderation” sweatshop (ICT-Works). Additionally, academic research also confirms that these labor arrangements in the production of AI reinforce historical inequalities where resource-rich regions, now data-rich regions, are left undercompensated while others reap the rewards.
The Development Dilemma
For developing nations, building digital infrastructure is incredibly critical. However, investments in homegrown digital systems, free of exploitation, require a large amount of financial capital and advanced technical expertise which most countries in the Global South lack. Regulatory frameworks can also often lag because many developing countries don’t have the institutional capacity to keep pace with other western countries. Eager developing countries could consider partnering with international partners, however, these partners typically offer technology under terms that model long-term dependencies, retaining structural inequality.
Regardless of these issues, resistance to data colonialism is growing. Many nations and organizations have expressed interest in pushing back against data colonialism. The Prime Minister of India, Narendra Modi, encouraged Indian youth to build social media platforms akin to Western platforms to safeguard digital sovereignty (The Times of India). The African Union launched the Data Governance and Innovation Forum, aiming to accelerate the implementation of the African Union’s Data Policy Framework (African Union). Europe's GDPR has set a new baseline for privacy standards worldwide, influencing international norms and encouraging companies to adopt its tenets. China has begun exporting its digital governance model through its Digital Silk Road Initiative.
Together, these movements show that data sovereignty is a growing force that is working to reshape global power structures rooted in structural imbalances and exploitation.