Squaring the Circle on Big Data, Class, Value and Primitive Accumulation

A recent paper by Hamid Ekbia presents an interesting Marxian theory of the relation between exploitation and computer networks.   The paper is intended as an intervention in to discussions of the accumulation of value in what is now called cognitive capitalism (I’ve attempted to synthesize some of that literature here).  The most interesting part of the Ekbia’s paper seems to me that he’s able to construct a coherent notion of class (or close to class – he acknowledges that it’s not quite a class in the strict Marxian sense) within those who are part of the networked economy.  In particular, he is able to locate those who are exploited and to roughly define them as a group: the “condensers.”  The problem of locating a specific exploited class is important and salient partly because there is no way for a Marxian theory of value to work unless somebody is exploited, but also because the behavior of prosumers in particular has been the subject of intense controversy, particularly on the subject of whether they produce value.  Ekbia’s contribution, it seems to me, is to show how and why some prosumers manage to be exploited.

Ekbia’s thesis depends on rewriting the notion of class along the lines of network inclusion: “Digital inclusion – in the sense of being connected to a network, not being a member of the privileged class – has become the modus operandi of current capitalism” (168).  That is, current information capital operates through networks.  This causes difficulty in determining where value comes from, as it is not, for example, obviously connected to socially average labor time.  One example is the creation of network value.  Compared to, say, a single car, a single telephone is pretty worthless, but the more phones that are connected to the network, the more value the network as a whole realizes, both to those who use the network and to those who own it.  As the market valuation of companies like Facebook suggests, the bulk of that value goes to those who own the networks.  A second tier of user is able to exploit the uneven distribution of connections across the network, extracting value by way of being well-connected to other points on the network.  Those who can make a living monetizing their YouTube videos come to mind here.  In both cases, the revenue stream importantly depends on the ability to sell advertising, on the premise that such targeted advertising will reach consumers whose preferences have been accurately identified: advertising will become efficient.  It is this dynamic that leads me to think that the entire system depends on an originary accumulation of users’ preferences on the part of the system (this may be purely aspirational, and the model may fail), a point to which I will return in a moment.

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