The starting premise for this chapter is that algorithms are becoming habitual and part of a felt presence as people inhabit mediated spaces. This is not to say that algorithms are necessarily consciously present to people but that they have the capacity to call forth “something that feels like something” (Stewart, 2007: 74). Sometimes, this something may take the form of an event such as the #RIPTwiter protest, a moment when “collective sensibilities seem to pulse in plain sight” (2007: 74). Most of the time, however, algorithmic impulses become barely noticeable in the mundane moments of everyday life. Recall, for example, the targeted ads for the Lisbon hotel recommendation or the party dress that seemed to creep up on me while I was surfing the Web (as described in chapter 1), or the oddity of having your credit card company put a security ban on you without being able to explain why (as mentioned in chapter 3). In moments like these, algorithms make themselves known even though they often remain more or less elusive. They become strangely tangible in their capacity to create certain afective impulses, statements, protests, sensations and feelings of anger, confusion or joy.
In this chapter, we move away from the disciplinary power of algorithms explored in the previous chapter toward the “micropolitics” of power imbued in the afective and phenomenological dimensions of algorithms. By “micropolitics,” I mean something akin to Foucault’s (1978) notion of microphysics as a way to pay atention to the generative potential of specific everyday practices and techniques. More specifically, micropolitics “refers to the barely perceived transitions in power that occur in and through situated encounters” and the idea that “diferent qualities of encounter do diferent things” (Bissell, 2016: 397). This is not a kind of power and politics that is necessarily repressive, discriminatory, or hierarchical but, rather, productive in the sense that it produces certain capacities to do and sense things. What I am interested in is the question of how algorithms and people meet, and what these encounters make possible or restrict? The notion of afect becomes important in terms of describing what is at stake in thinking about the barely noticeable and more sensible dimensions of algorithms as a key to understanding the power and politics of algorithmic life. Without going much further into the notion of “afect” (many books have been dedicated to this concept alone), sufice it, at this point, to say that “afect” describes the domains of “the more-than or less-than rational” in life, including “mood, passion, emotion, intensity, and feeling” (Anderson, 2006: 734).5 I specifically focus on the ways in which algorithms have the capacity to afect and be afected (Deleuze & Guatari, 1987) by looking at how users perceive and make sense of algorithms as part of their everyday lives.
The point, however, is not to assess the extent to which people actually feel algorithms as such but to highlight experience and afective encounters as valid forms of knowledge of algorithms (see chapter 3 for a discussion on the phenomenological approach to algorithms). The argument is made that algorithms do not just do things to people, people also do things to algorithms. The word to is important as it extends more classic accounts of media use and arguments of audience power. It is not just that people do things with the help of algorithms. By using algorithms, they also do things to them—modulate and reconfigure them in both discursive and material ways. As we discussed in chapter 2, the machine-learning algorithms proliferating on social media platforms are never set in stone. These algorithms are continuously molded, shaped, and developed in response to user input. If the previous chapter made a case for analyzing algorithms as governmental techniques directed at the “right disposition of things” through rankings and weights as architectural forms of power, this chapter considers the “productive power” of cultural imaginaries and the significant role users have in reconfiguring the algorithmic spaces that they themselves inhabit.
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