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On Elephant Skin: Critical Data Studies and Political Economy



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Critical Data Studies (CDS) is an emerging interdisciplinary research field that examines the role of data, particularly Big Data, in effecting social change. CDS scholars generally consider it to be a subcategory of new media studies, which includes other areas of inquiry, such as Information Studies and Software Studies. Although CDS has generated much notable research, it has yet to embrace the possibilities of a critique predicated on a rigorous technical definition of the word “data.” I suggest here that this development is necessary if the field is to address concerns of political economy effectively. Making “data” in this sense a central element of CDS would allow the field’s scholars rigorously to investigate the relationships between new media and capitalism.

In her essay “On ‘Sourcery,’ Or Code as Fetish,” new media theorist Chun recounted the fable of the six blind men and an elephant (Chun, 2008, p. 299; “Blind Men and The Elephant,” 2018) In the story, each man touches a separate part of the animal and describes it differently as a result.  One likens the elephant to a wall; others say it is more like a spear, tree, palm or piece of rope. Each man believed his understanding to be accurate and the others’ flawed. Chun argued that new media scholars face a similar predicament:

It is perhaps profane to compare a poem on the incomprehensibility of the divine to arguments over new media, but the invisibility, ubiquity, and alleged power of new media (and technology more generally) lend themselves nicely to this analogy. It seems impossible to know the extent, content, and effects of new media. Who knows the entire contents of the WWW or the real extent of the Internet or of mobile networks? How can one see and know all time-based, online interactions? Who can expertly move from analyzing social-networking sites to Japanese cell-phone novels to World of Warcraft to hardware algorithms to ephemeral art installations? Is a global picture of new media possible? (Chun, 2008, pp. 299-300)

“On ‘Sourcery’” was a “sympathetic interrogation” of Software Studies, a nascent area of inquiry within media studies at the time Chun wrote. She suggested that the subfield she analyzed was flourishing partly due to the fact that software can be thought as a common denominator among new media: “All new media allegedly rely on — or, most strongly, can be reduced to — software, a ‘visibly invisible’ essence. …  “Software seems to allow one to grasp the entire elephant” (2008, p. 300). In fact, what counts is not software’s actual ubiquity, which she contended was dubious, but rather that it can be figured as a common thread among so many different technologies. In this sense, its omnipresence is a productive mirage: software seems to allow one to grasp the entire elephant. It is thus attractive as a lens for new media scholars as they attempt to gather multiple technical and social artifacts into a single field of vision.

The title “new media” is often applied to academics unwittingly. Cultural theorist McKenzie Wark has often been described as such despite having critiqued the phrase repeatedly, both for its pervasiveness in digital scholarship and as a descriptor of their research interests.  Wark has argued that new media is an “absurd” term, especially to students “whose whole conscious life has existed pretty much within the era of the internet and increasingly also of the web and the cell phone” (Wark, 2017, p. 253). Meanwhile, Kember and Zylinska have contended that, “the majority of the theorists who have used this term have always done so somewhat reluctantly, with a sense of intellectual compromise they are having to make if they want their contribution to be recognized as part of a particular debate around technology, media and newness” (Kember and Zylinksa, 2012, p. xiv). They have also asserted that Chun’s self-identification with “new media” is self-reflexive. Chun took the problem of “new media” as a point of departure, describing the ostensive “singular uniqueness” implied by the word “new” as a myth that begged undoing (Kember and Zylinska, p. xiv).

As a descriptor, “newness” may indeed do little but conceal a dearth of similarities among contemporary media forms. Like Chun, however, I am compelled by the lack of internal unity that would give “new media” categorical coherence. In my research I generally use “new media” and “digital technology” interchangeably. Most people have some notion of what the phrases “new media” and “digital technology” mean, but their common use belies an absence of cross-disciplinary consensus on their “textbook meaning.” This lack of agreement should not be taken as a problem, however. In fact, it reveals something very crucial about digital phenomena. If we consider that there are no empirical commonalities that bind all digital/new media artifacts, we can only think about new media and the digital by producing fresh metaphors. This is central to the realization of digital technology as both concept and material entity. Like Chun, I am fascinated by the interweaving of digital technology and the language we use to describe it. As it turns out, the mutual constitution of human language and digital matter is a very rich avenue for inquiry.

Central to Chun’s analysis is the popular but, as she argued, misconceived, notion that views software interfaces as the singular and scientifically inevitable outcome of their source code. She contended that analysts should instead consider such an assumption concerning the connection between code and software as fetishistic, where that term implies a process by which causality is inferred from desire, as opposed to reason: “Software as source relies on a profound logic of ‘sourcery’ — a fetishism that obfuscates the vicissitudes of [code] execution … the relationship among code and interface, action and result, however, is always contingent and always to some extent imagined” (Chun, 2012, p. 310). Chun insisted that Software Studies’ strength lies in its capacity to point up the fact that humanity’s relationship with technology is largely imagined. As such, the subfield’s analyses should reveal the muddying function of fetishistic reason. Mystification as a foundational concept for a scholarly field may appear to be misguided. But a deemphasis on software qua software draws attention to the necessary place of metaphor and creative thought—fundamentally, acts of language—in humans’ relationship with the digital. These insights represented the cornerstone of Chun’s conception of Software Studies.

I would like to suggest a similar role for data and Critical Data Studies while noting a key difference. As with Software Studies, a primary function of such inquiries should be to clarify the role of the imagination in our conceptualization and apprehension of new media. But if the overarching goal is to excavate digital technologies from their varying contexts so as to grasp their social impact better, Critical Data Studies has potential to be more useful than Chun’s Software Studies. To explain why this is so, and how Software Studies highlights the privileged role I am suggesting for data, it is necessary to offer a working technical definition of “data.”  The benefit of using data as a basis on which to organize thought on new media cannot be understood by studies that illuminate its exogenous effects—which, in fact, neatly describes the majority of existing CDS analyses. While these are very helpful, they must be supplemented with the technical, endogenous definitions of data employed in the discipline of computer science.

Data is information that can be processed and transmitted by computer systems.  Strictly speaking, “data” is a plural noun—I employ “data is” rather than “data are” for stylistic purposes—that refers to binary digits: zeros and ones, also known as “bits.” Data is measured in groupings of bits. Eight bits comprise a byte; a terabyte is 240 (or 1 million million) bytes. Data becomes meaningful through acts of interpretation and contextualization.

The phrase “Big Data” refers to large volumes of information. Researchers originally employed the term to describe the exponentially accelerating global quantity of digital data as a social concern. Critical Data Studies has emphasized Big Data as a societal constituent. But, in fact, data is (or data are) discrete computable integers; figures that comprise or denote a symbolic language. And, importantly, data may be the only common thread that runs among all forms of new media / digital technology. Digital technology is data technology.

This argument might appear to suggest that Chun was incorrect in tying the role of imagination to any understanding of new media—the fact of data, manifest as digital technology, would seem to be true regardless of what humans imagine. But, that assertion misses the reality that human beings invest digits with power and agency by an imaginative consensus concerning their meaning and purport. This insight, in turn, suggests why a technical definition of data becomes important for political theory. As the basis for all signifying language acts in computer systems, data is the signature form of the digital age. I reference the Marxist notion of sign value, originally conceptualized to refer to the translation of real-world usefulness into capital, which has no tangible use until it is exchanged for a good or service.

In this sense, capital becomes valuable through acts of imagination—the mental process by which 10 dollars is related to an item of clothing or food, for example. Data also becomes valuable through imagined resemblances.  Rendered by the interpretive functions of a programming language, data is constructed to resemble human language, visual imagery, sound and so on. Data and capital are virtual and immaterial entities. Analogical cognitive leaps, the actions that make something appear as functionally similar to something else, are required if humans are to come to believe that they are interchangeable with tangible phenomena; e.g., data becomes akin to human language; 10 dollars can be seen to relate to a t-shirt, and so on. In this very radical sense, imagination is the means by which digital technology becomes an economic vehicle.

As noted, imagination is a critical component in Chun’s Software Studies. But if Critical Data Studies was to emphasize the technical understanding of data as sign just outlined, such analyses would more powerfully reveal the connections among digital technology and political economy. Chun’s software imaginary does not implicate the economic function of digital matter, but rather bends back into new media studies, “This emphasis on imagined networks I hope makes it clear that I’m not interested in simply exorcising the spectral or the visual, but am rather trying to understand how its spectrality lies elsewhere” (2008, p. 323). Or, as she also has contended, “Capturing ghosts often entails looking beyond what we ‘really’ see to what we see without seeing, and arguably, digital media’s biggest impact on our lives is not through its interface, but through its algorithmic procedures” (2008, p.323). It may be true that algorithms have a greater impact on end-users than do the graphical interfaces of software. But the “elsewhere” that is so distant from optics in her contention is not the space of algorithms, servers or any other digital device or dimension. In fact, it is not the domain of anything properly digital at all. Instead, that spectrality is ultimately native to capital, which produces all sorts of specters and spectacles in its representations of financial value.

Chun fails to indicate that data, the raw material of software, deploys imagination in the same sense that capital does. Instead, her essay concluded with a proverbial guilty verdict for algorithms. To be fair, the term “spectral” —which she uses frequently throughout her article—evokes theorists influenced by Marx. But even if Chun, or any other scholar, were to come to view political economy as a specter-haunting algorithms (or code, information or content, etcetera), the study of data leads one to that insight more directly.

It matters that data is omnipresent across digital applications. As software programs cross-pollinate across internet networks and application programming interfaces (APIs), their boundaries become increasingly porous. More than a decade has passed since major corporations introduced smartphones, and with them, the notion of “apps.” Now, the term applications/apps—infrastructure-agnostic software—may be more appropriate than “software” to describe the underpinnings of graphical user interfaces. But even as individuals decompose  and recombine software into new forms, data remains. It is an irreducible element of the modular digital ecosystem. It is more foundational than code, algorithms, content or information, all of which rely on functions and contexts that data does not by definition require. Conceived as a basis for new media studies, data can be thought as the skin of the elephant. The skin is the body’s largest organ. In seeking an image around which to organ-ize thought on new media, one could hardly do better. The skin is also humans’ most visible organ, the part of the body that is most commonly read for signs of organic functionality. This is not a meaningless coincidence in this analogy, especially if one views data as a sign form, as I argued above.

If scholars only examine data’s effects on society, they may miss this point of connection between political economy and digital technology/new media. Data is a highly productive starting point for the social study of digital technology. Critical Data Studies is important in that it allows the particularities of data to serve as a grounding logic for such investigations. In sum, this emerging field would benefit strongly from a rigorous technical understanding of data as language, irreducible integer and sign, because such a definition points up the way data’s functionality mirrors the function of capital. This similarity, I think, should serve as the foundation of Critical Data Studies.

Works Cited

“Blind Men and the Elephant.” 2018. AllAboutPhilosophy.Org. Accessed December 3, 2018.

Chun, Wendy. 2008. “On ‘Sourcery,’ Or Code As Fetish.” Configurations 16 (3): 299–324.

Kember, Sarah, and Joanna Zylinska. 2012. Life After New Media: Mediation As A Vital Process. Cambridge, MA: The MIT Press.

Wark, McKenzie. 2017. General Intellects: Twenty-One Thinkers for The Twenty-First Century. London, England: Verso Books.

Emma Stamm

Emma Stamm is a Ph.D. candidate in the Alliance for Social, Political, Ethical, and Cultural Thought (ASPECT) and Instructor in the Department of Political Science. Her research explores the epistemic effects of data science by investigating methodology in experimental psychiatry research. Her past research examined computer hacking, blockchain technology and machine learning through continental philosophy and critical theory frameworks. She has given talks on these subjects at conferences throughout the United States and Europe. Emma is also a freelance writer and web developer, and is co-editor elect of SPECTRA, a peer-reviewed journal housed by ASPECT. She holds a B.A. from Bard College and an M.S. from The New School. Her website is

Publication Date

December 6, 2018