Boundary-making Practices
From a strictly technical perspective, an algorithm can be defined as a step-by-step procedure for solving a problem in a finite number of steps. Throughout this book, I have argued that algorithms are much more besides this narrow, technical concept. Algorithms do not only instruct, they mean something, and often they mean diferent and conflicting things. Algorithms manifest as objects of social concern, as they become inscribed into the fabric of everyday life. Algorithms, moreover, help to shape the ways in which we come to know others and ourselves.
If the textbook definition of algorithm is but one version implicated in the manyfoldedness of the term, then where and when besides code do algorithms manifest? As I atest in this book, algorithms exist in the conversations of academics, in media portrayals, public controversies (i.e., debates over “fake news” on Facebook), in people’s perceptions and imaginations, in representational resting points (i.e., simplified images of formulas), in metaphors (i.e., the notion of algorithm as recipe), as part of films and popular imagery, stories, and professional practices. In an expanded understanding of the term, algorithms are seen as events. Without front-loading an ontological commitment with regard to algorithms, the notion of the event helps directing atention to the ways in which algorithms make other things suddenly conceivable.
Who or what is made accountable and responsible for algorithmic outcomes depends on how and where the boundaries are drawn. Disentangling the ontological politics of algorithms requires “remembering that boundaries between humans and machines are not naturally given but constructed, in particular historical ways and with particular social and material consequences” (Suchman, 2007: 11). Again, there are at least two sides to this. What counts as an algorithm, as well as when it counts, are not given. Following Suchman, we need to pay atention to the “boundary work through which a given entity is delineated as such” (2007: 283). As we have seen, what counts as an algorithm may vary greatly. Yet, most people would probably have litle problem acknowledging that the computer science textbook definition of an algorithm, at least partly, constitutes the phenomenon in question. With this book, I hope to have made people more susceptible to the idea that algorithms exist and manifest on scales and levels that go far beyond the narrow, traditional definition.
Algorithmic Life
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