CAT 2025 Slot 3 VARC: Data Colonialism: An Extraction by Another Name

Colonialism, in its classical form, extracted physical resources — cotton, rubber, minerals, labour — from colonised territories and processed them into value elsewhere, typically in the metropole. A growing body of scholarship now argues that a structurally similar extraction is underway with a different resource: personal data. Proponents of the term "data colonialism," notably Nick Couldry and Ulises Mejias, argue that the analogy is not merely rhetorical flourish but points to a genuine continuity in how value is appropriated from human life without commensurate compensation or consent.

The comparison invites an obvious objection: data is not land, and clicking "I agree" on a terms-of-service document is not the same as a colonial administration imposing rule by force. Couldry and Mejias anticipate this objection and refine their claim accordingly: they are not arguing that data collection is literally identical to nineteenth-century colonialism, with its direct territorial control and often extreme violence, but that both processes share a common underlying logic — the appropriation of something previously outside the market (unclaimed land then, the granular data of daily human life now) and its conversion into a resource that generates profit primarily for those who control the means of extraction, while the people who are the actual source of that resource receive little of the resulting value and often cannot meaningfully refuse participation.

The "cannot meaningfully refuse" clause is doing significant work in this argument, and it is worth examining directly. In principle, a person can decline to use a social media platform, a ride-hailing app, or a smart-home device, and thereby avoid supplying it with data. In practice, participation in modern economic and social life increasingly requires these services — a job search conducted without LinkedIn, a delivery conducted without a location-tracking app, a payment made without a card that logs the transaction, are each technically possible but practically marginalising. This asymmetry, the theory holds, is what converts "consent" from a meaningful choice into something closer to a formality: technically present, substantively hollow.

Critics of the framework raise a different concern, one about analytical precision rather than moral force: stretching "colonialism" to cover data extraction risks diluting a term that already refers to a specific, well-documented historical phenomenon involving direct political domination, appropriation of sovereign territory, and often genocidal violence — comparing it to a Silicon Valley company's advertising-targeting algorithm, however exploitative that algorithm may be, is argued by some historians to trivialise the original term's weight rather than illuminate the new phenomenon. Couldry and Mejias respond that the point of the term is not to equate the two in severity, but to insist that data extraction, like classical colonialism before it, establishes new social and economic relations of domination whose full shape becomes visible only in retrospect — colonial societies, after all, took generations to reveal the full extent of the economic dependency they had created, and the authors argue that data relations may be following an analogous, if compressed, trajectory.

Whatever one makes of the historical analogy's precision, the underlying empirical claim — that a small number of firms capture a disproportionate share of the economic value generated from data that billions of people produce, largely without individualised compensation — is harder to dismiss than the label attached to it, and it is this claim, rather than the vocabulary, that has driven a growing number of proposals for data dividends, collective data trusts, and portability rights designed to shift some of that captured value back toward the people who generated it in the first place.