The Continuity Thesis: From Brute Force to Invisible Infrastructure

The concept of algorithmic colonialism was given its most precise and widely cited formulation by Abeba Birhane, an Ethiopian-born cognitive scientist, in her 2020 essay 'Algorithmic Colonization of Africa,' published in SCRIPTed. The core argument, she argues, is that Western tech monopolies 'with their desire to dominate, control, and influence social, political, and cultural discourse, share common characteristics with traditional colonialism.'

Birhane identifies the structural parallel precisely. Traditional colonialism was driven by political and government forces and used brute force domination. Algorithmic colonialism is driven by corporate profits and operates through what she calls 'invisible and nuanced mechanisms, for example, control of digital ecosystems and infrastructure.' The Oxford Academic chapter from Imagining AI (2023) elaborates: 'Political, economic, and ideological domination in the age of AI takes the form of 'technological innovation,' 'state-of-the-art algorithms,' and 'AI solutions' to social problems.'

What makes this a colonial dynamic rather than simply an unequal economic relationship is the combination of three features that track the classical colonial pattern. First, extraction: as Birhane's work suggests, the approach 'assumes that the human soul, behaviour, and action is raw material free for the taking.' Human activity in the Global South generates data that is collected, processed, and monetized by companies headquartered in the Global North, with little or no return to the communities that produced it. Second, infrastructure control: currently, as they document, 'much of Africa's digital infrastructure and ecosystem is controlled and managed by Western monopoly powers such as Facebook, Google, Uber, and Netflix.' Third, epistemic imposition: Western-developed algorithms encode Western values, categories of knowledge, and framings of social problems, and then apply them to African contexts where they may be actively harmful or simply inappropriate.

The framing connects to a longer tradition of thought about digital colonialism and data colonialism. Couldry and Mejias define data colonialism as a 'distinctively 21st-century manifestation of colonialism that normalises the exploitation of human beings through data, just as historic colonialism appropriated territory and resources and ruled subjects for profit.' Michael Kwet extends this to argue that 'colonialism does not arrive with soldiers, missionaries or trade monopolies, but with cloud services, proprietary software and algorithmic governance, each serving to deepen the country's dependence on Western technological infrastructures.'

Structural analysis adds a further dimension: a 'handful of corporations, predominantly from the United States and, increasingly, China, control the infrastructures of the digital economy,' producing 'a new form of asymmetrical dependency that echoes the colonial past.' This is not merely about individual algorithms being biased: it is about the architecture of the global digital order and who controls its foundational infrastructure, standards, and governance.

Birhane's thesis makes a further point that is often missed in technology policy discussions: the colonial parallel is not merely analogical but causal. The same actors, the same interests, and often the same institutional networks that organized historical colonial extraction are present in the digital economy. The tech monopolies that 'present such exploitations as efforts to liberate the bottom billion, helping the 'unbanked' bank, or connecting the 'unconnected,'' as they note, are reproducing 'the same colonial tale now told under the guise of technology.'