The subjects and regions of uneven datafication

Azedeh Akbari's “Uneven Datafication” makes a signal intervention in the study of contemporary capitalism, defined as it is by the commodification of data, a deceptively simple idea that contains, as do all commodities, the social hieroglyphic of economic relations. Akbari points out that while most commentators on data capitalism recognize the unequal power relations inaugurated by data capitalism, fewer locate the origin of that capacity in the continued story of expropriation, extraction, and epistemic violence of colonialism. These processes began during the age of colonial expansion and continued under the guise of both national elites and successive rounds of globalization. In Akbari's account, the term “uneven datafication” is meant to harken back to earlier analyses of world systems and their inequalities, as in the literature on uneven development from which Akbari draws. The article makes good use, for instance, of Samir Amin's (1974, 2010) analyses of the accumulation of capital from the peripheries to the core and the unequal exchange that accompanies that accumulation.

Particularly important to Akbari's analysis is the treatment of data as a peculiar commodity. As she points out, data is difficult to standardize, and its ability to be used by multiple parties means that the extraction of value and the question of ownership are difficult to resolve. This makes data difficult to conceptualize. Data is not a regular commodity where rules of ownership are exclusive, yet it is doubtless a driver of economic value production. As a side note, Akbari mentions that data is not often accurately tracked as a value-producing commodity across borders, so the balance of trade appears skewed. If the value of the data collected by American companies was included in these calculations, for instance, the United States would come out far ahead in the uneven trade that exists between it and other countries. Such a note, which could be developed in future work, makes it clear that balance of trade should more often be viewed from the perspective of data as a commodity. This perspective would provide a measure of the unevenness of data development towards which Akbari's analysis points.

Given Akbari's analysis, two points warrant further consideration. First, there is the issue of from whence potential for undoing this unevenness of data might come? Second, there is the issue of how native elites or comprador classes are enrolled in the creation of unevenness—in other words, is there unevenness within uneven development at the level of nation-states? These questions were foundational for the critique and extension of world-systems theory, so it is not surprising to find them reemerging here. A deepening of the theory of uneven data that Akbari proposes might engage with how scholars complicated world-systems theory by addressing these two questions.

Akbari mentions in passing that Amin's focus on national elites in the periphery, who framed anti-imperialism as part of their identity, is less important (or more worthy of challenge) than other parts of his theorization. Instead, Akbari highlights Amin's focus on complicating class solidarity by understanding the coexistence of various classes in interdependence within capitalism. As Akbari writes, a “universalist theorization” of information pushes “a worker/hacker, a coder in Silicon Valley, a software developer in India, a cyber intelligence officer of the Israeli army, and a female content moderator in Morocco puts different subjects within the same frame” whereas, interdependence allows theorists to grasp how “the capacity for political mobilization and solidarity is often hindered by the very tools that are supposed to connect people, such as social media platforms.” Complicating too-easy pictures of solidarity is of course an extremely important task. Nevertheless, it is difficult to see within uneven development analyses where radical potential might be located. The interconnectedness of global economies also suggests that collective subjects might emerge that cut against the extractivism of current data economies, including such groups as transnational feminist collectives and national or even local labor and data cooperatives. Of course, the bearers of change may not be proletarian workers but may be, as were Amin's native anti-imperialists, highly flawed subjects who might in the end thwart their own revolutionary potential and subvert solidarity to class interest. This is certainly the story with other political formations such as the “third world” as outlined in the work of Vijay Prashad and others (Prashad, 2008). Despite their flaws, such classes represent a vector for change that might be a continued counter-conduct worth documenting. Movements such as those currently mobilized against data centers in many parts of the world, including in the United States and South America, might represent nascent attempts to thwart data politics as usual (Rest of World, 2025).

A second and related extension of the uneven datafication argument is the question of how different kinds of subjects might be enrolled in colonialist or anti-colonialist projects. Here, the question of intent falls by the wayside because uneven datafication takes the question of the extraction, commodification, and use of data out of the context of whether particular uses of data and practices of data are good or bad, and shifts attention to the causes and consequences of datafication. Uneven datafication can be viewed as an unfolding process that is also contradictory, which does not homogenize global relations but differentiates them. Akbari reminds critical scholars that “uneven datafication creates hierarchies of oppression, despite Marxists’ resistance to differentiated oppression.” While this statement is certainly true prima facie, a further elaboration of the uneven datafication argument might show in some granular detail how this comes to be, not only because of enduring colonial legacies, but also because of data and its unique valorization problem. That is, it would be useful to understand how such issues as information asymmetry and the invisibility of unequal wealth transfers around data contribute to the making of stratification and the breaking of possible solidarities, be they organized transnationally, regionally, or nationally. Here, it could be interesting to look at the tactics of such groups as the Data Labelers Association for a diagnosis of what can be revealed and what remains hidden in these moments of organizing.

In an earlier moment of considering world-systems theory, anthropologist of Guatemala Carol A. Smith argued that world-systems theory needed the contributions of local and regional study to complement the general thesis of underdevelopment—a thesis with which she is largely sympathetic (Smith, 1987). In her detailed study of questions of unequal wages and capitalist expansion in post-colonial Guatemala, “Regional Analysis in World Systems Perspective,” written in 1987, she concludes that “no structural tendencies are immutable: to explain the situation of any place requires us to look at numerous factors, some global and some local, all of which can affect the outcome in distinctive ways” (Smith, 1987: 642). If she is correct, and I believe she is, the same would hold true for uneven datafication. To understand more fully how uneven datafication affects the world and what the possibilities for new worlds to emerge might be (whether revolutionary or revanchist), it might be necessary to tack back and forth between the world stage of data write large and the local and regional contexts that will help determine capitalism and its futures, both because, as Smith suggests, “capitalism in the periphery is not like capitalism in the core” and because it is in the interaction across sites of unevenness that systems of data will be pushed into new containers and bent to new purposes.