Technicity
How are we to think of the capacity that algorithms have to bring new realities into being? At the start of the book, I suggested a specific approach to the question of “how algorithms shape life in the contemporary media landscape,” by looking at how platforms like Facebook condition and support specific forms of sociality in ways that are specific to the architecture and material substrate of the medium in question. I described how Facebook encodes friendship in ways that essentially support the circuit of profit, and introduced the notion of programmed sociality. At the same time, in chapter 1 I warned against taking this notion of programmed sociality to credit for technological determinism. Software and algorithms do not simply operate in isolation or exercise power in any unidirectional way. Rather, their capacity to produce sociality always already occurs in relation to other elements, and as part of an assemblage through which these elements take on their meaning in the first place.
This is the technicity of algorithms, understood as the capacity they have to make things happen as part of a co-constitutive milieu of relations. For the French philosopher Gilbert Simondon, who introduced the concepts of transduction and technicity as useful frames to account for the productive power of technical objects, humans and machines are mutually related, where the technical object always already appears as a “theatre of a number of relationships of reciprocal causality” (1980: 22). Technicity, then, pertains not so much to what the technical objects are, but rather to the “forces that it exercises on other beings as well as in and through the new virtualities, and hence realities, it brings into being” (Hoel & van der Tuin, 2013: 190). This understanding comes close to the Foucauldian manner in which power was perceived in chapter 2. For Foucault, power pertains precisely to its exercise and force, to the “way in which certain actions modify others” (1982: 788). For an understanding of algorithms, this implies resisting reading algorithms as either technology or culture. Rather one is prompted to think of algorithms as “dramas”—or “theatre” of relationships in Simondon’s terms—that algorithmic mediations bring about. The concept of technicity, then, ofers a way of thinking about the productive power of algorithms that doesn’t rely on the atribution of power to some fixed characteristics or stable artefact devoid of human agency. To speak of the technicity of algorithms is to emphasize how algorithms do not possess power in and of themselves, but how power unfolds as an “ontological force” (Hoel & van der Tuin, 2013).
Let’s briefly consider the examples of Amazon book recommendations and Twiter’s “While you were away” feature. The technicity here should be understood as the coevolving conditions that emerge from the algorithm’s dynamic functioning. An analysis of an event such as the recommendation of a book, or having one’s fear of missing out catered to by a promise of a peek into what happened “when you were away,” should be grounded in an “understanding of the nature of machines, of their mutual relationships and their relationships with man, and of the values involved in these relationships” (Simondon, 1980: 6). Though I have not made any claims about “the nature” of algorithms, I propose that algorithmic modes of existence are grounded in the relational drama of diverse environments. In the process of recommending books, Amazon’s “collaborative filtering” algorithms create conditions through which certain books are brought to user atention while others remain elusive. Collaborative filtering is based on the assumption that customers who share some preferences would also share others. Rather than matching users with similar customers, Amazon uses “itemto-item” collaborative filtering to recommend similar books or other items, and this calculated chain of similarity relies heavily on user input. Thinking of the power of algorithms in terms of their technicity leaves no one of the agential hook, so to speak. The nature of the machine always needs to be understood in relation to other machines and “man,” in Simondon’s terms. On Amazon, we buy books (often several at the same time), put them into wish lists, search for items, browse the platform, write reviews, and provide ratings. On Twiter, we tweet, browse, spend time, build nonreciprocal networks of relationships, reply, and retweet. We are already implicated. According to Barad, “we are responsible for the world in which we live not because it is an arbitrary construction of our choosing, but because it is sedimented out of particular practices that we have a role in shaping” (2007: 203). This means that we cannot treat the power of algorithms as a one-way street. If power refers to the way in which certain actions modify others, our actions count too. The tweets we post, items we purchase, and likes we hand out all factor in to the sum total. As we saw in chapter 4, actions such as these modify what becomes visible to us and to our networks.
Algorithmic Life
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