the data issue


Recently I wrapped up one of the more exciting projects I've ever worked on. I was the co-guest editor, along with Marvin Jordan, of a special issue of DIS magazine. Known as the Data Issue it took as its starting point the rise of so-called "big data", or more broadly the series of shifts associated with the ubiquitous nature of parallel processing, large data sets, and digital networks. 

The issue was predicated on a simple adjustment to the current discourse in art and theory. While various discussions and art practices are focused on the circulation of images and their potential vis-a-vis "the internet," the issue took for its main subject the totalizing effect of the massive amounts of data with which we are now imbricated as social subjects. These are data that are stored on the backend of ubiquitous platforms, without user interfaces, much less accessible on the consumer web. A central thesis for the Data Issue was that the most interesting things are happening off screen.

The works and texts were attempts to explore the intermingling of bodies in "datafied terrains", (to paraphrase an excellent paper on the topic) that are subject to new architectures and social relationships.

AuthorMike Pepi


I've finally gotten around to cleaning up and posting my remarks from Theorizing the Web 2014 from April. I am trying to do "Platform Studies" for the various vendors of big data analytics and architectures, paying close attention to the often ignored parts of big data commentary, that being the hardware and software and their implications for epistemology and historiography. I've posted the talk here.


"When new sources of data suddenly hit a system and there are not enough tools or schemas to deal with them, a common reaction is to deny the agency of the data sources. Then, for a brief period, to suspend interpretation until new tools are built to handle the new variety. My fundamental point is that this occurs both with cultural discourses as well as with information. Big data, then, is likewise an attempt at forming new flexible schemas in order to continue the project of interpretation under radically new conditions."

AuthorMike Pepi


I would like to thank Antoinette Rouvroy (@arouvroy) for her comments in response to an essay I wrote recently about the connected discourses surrounding postmodernism and the nascent discussions of "Big Data." While in no way was the essay perfect in an academic sense, it was my hope that it would at least start to lend a hand in a larger assessment of a phenomenon that has great implications for culture, epistemology, and historiography. Rouvroy's criticisms are right on point, I think, because they scrutinize Big Data in the same manner. Though ultimately she seems to reach a different conclusion, a conclusion which I welcome and hope to consider as a way to sharpen my own position. 

While the comments were in twitter form, I think I grasp their point. However, I think they merit more than 140 characters in response, and I would like to continue the dialogue below.


Point one:

Despite what I think is a valid reading of the essay, I don't know that I necessarily equate analytics with a quest for certainty as much as I want/meant to point to the method of data collection and integration that analytics engages in, and what that says about the value given to empiricism. Big Data is a hyper-empiricism because, now that we can finally use so many more data, we potentially reanimate the critiques leveled at narrative during the end of Modernity. This began to seem, to me, to be very similar the loosening of historical agency that either lead to or was an outcome of postmodernism's imperative to take into account new types of cultural production and/or anti-teleological developments.

At its heart this essay was about historiography, and for me the shifts from modernist accounts to postmodern accounts carried the same ideological changes. A quote from Charles Harrison, historian and member of the conceptual art group Art & Language, brings this into light. For Harrison Modernism prized, or in fact required, “a critical difference and development with respect to other recent and approved ‘major’ work in the same medium—which tended to be sculpture or painting.” This again reminded me of issues of data integrity that come with traditional relational databases, something many Big Data frameworks attempt to circumvent through innovations in storage and organization. 


Point Two:

The above is a good point, and an example of how Big Data is at this point a catch-all term for both a research method (medicine, sociology, etc..) and a storage infrastructure (e-commerce, computing etc..) among other things. While this difference is obvious on its face, the difference also extends to the ideological questions I tried to raise, and so I think it makes some sense to separate them. In its manifestations in e-commerce, advertising, or risk models, etc.. I think Big Data does implicitly promise a sort of decisioning power that is assessed at the individual level. I don't deny that it contributes "to [a] multiplicity of impersonal behavioral patterns," though this aspect of its application has looser ties to the shift from relational databases to schema-less databases that is the heart of the discourse I am investigating.

One comment in response to this piece (written elsewhere) said "big data is just statistics with lots of data." While in part this is true, when you begin to ask about what kind of data are being used, then the structures required to process and store these data start to mimic the developments that accompanied the end of modernist teleology and narrative. Also, it would be a mistake to assume that the "just statistics" doesn't carry its own assumptions about knowledge. 


Point Three:

You noted the problems with the word "truth" above, and here I think it relates to your third point. In the end the word "truth" is scary and loaded even if you are talking about the denial of it existing as a knowable entity. So I suppose its use here was muddling my point: really I am concerned with the means and not the ends of Big Data. And perhaps here we could start to see a funny shape emerging here. When people talk about Big Data the marketing speak focuses on the ends, where most all of the other stuff is about the methods and tools, literally the breakthroughs in data science. So the layman's descriptions traffic in a language of "pinpointing", "discovery", "enhancement", that uses certainty as a form of currency, even it somehow knows it won't deliver it. It explains its worth by favorable comparison to legacy systems that could not "handle" everything "out there." What is "out there" is a another question about the promises its end users make for themselves. Postmodern accounts were, like Big Data, an answer to the modernist account that simply had a logic embedded in it that did not allow it to "scale up".


Final Point:

This last point is a strong conclusion built off of the initial statements about multiplicity and neutrality. We agree that Big Data carries with it a critique of existing assumptions and, in turn, knowledge structures, what with the way it holds out the promise to "reveal" and/or counter accepted notions about our world, a business, or a group of actors on a historical stage. 

AuthorMike Pepi

I anticipated a number of responses to an essay I published with The New Inquiry recently regarding the epistemologies of postmodernism and the rise of Big Data as a cultural phenomena. There were several risks here, not least the ridiculously small audience that would overlap across tech and philosophy fields. People were bound to have a problem with my formulation of postmodernism, "Big Data", or the very fact that these discourses are even related. In fact that was part of the impetus. At first glance, their similarities lay in their historical contingencies and myths. They both have a sort of ideology that accompanies them. The fundamental point of the essay was that there are epistemological parallels in the shift from modernity to postmodernity and the shift from relational SQL databases to Big Data analytics and schema-less noSQL databases along with some its larger "goals." To borrow a phrase from the tech world, Modernity wasn't built to scale.

A few central points that pull that into sharper focus are below.

"Postmodern relativism was a cultural crisis instigated by too much data, as the volume, variety, velocity, and veracity of cultural inputs expanded. The arguments about contingency that animated poststructuralism, literary theory, feminist theory, and the postcolonial were each in their own way a declaration that the way we received, stored, and analyzed data was ignorant of and insufficient for entire sections of cultural production."

"Big Data might come to be understood as Big Postmodernism: the period in which the influx of unstructured, non-teleological, non-narrative inputs ceased to destabilize the existing order but was instead finally mastered, processed by sufficiently complex, distributed, and pluralized algorithmic regime."

You can read the full piece here.

AuthorMike Pepi