This chapter ofers the conceptual groundwork I believe is necessary to appreciate the multiple levels at which algorithms exist and operate, both technically and theoretically. The first part of this chapter explains what algorithms are in a more technical sense, particularly with regards to machine learning, as most of the algorithms operating in the media landscape depend on systems that are able to learn from data and make predictions. This should provide readers with enough background knowledge to appreciate the question of how algorithms intersect with power and politics on a more philosophical and sociological scale—the concern of the second part of this chapter. While I do not mean to suggest that algorithms can be understood from either a technical or a sociological perspective—as if there exists one single object called an “algorithm” that we might understand from diferent perspectives—the aim is to show how dynamic both the notion of an algorithm and the concerns they foster are in order to introduce readers to the complexities of algorithmic power and politics. The third part of this chapter uses Foucault’s conceptualizations of power to map how power and politics intersect with algorithms as an emerging social concern. I make the argument that algorithms do not merely have power and politics; they are fundamentally productive of new ways of ordering the world. Importantly, algorithms do not work on their own but need to be understood as part of a much wider network of relations and practices. The view to which I am subscribing in this book (and which I will further elaborate on in the next chapter), sees algorithms as entangled, multiple, and eventful and, therefore, things that cannot be understood as being powerful in one way only.
A Beginning
H IS TO R I E S A N D T E C H N IC A L I T I E S
Let’s take a step back. What exactly do (most) people mean when they invoke the term “algorithm”? According to standard computer science definitions, an algorithm is a set of instructions for solving a problem or completing a task following a carefully planned sequential order (Knuth, 1998). Although the algorithm is a key concept in computer science, its history dates back to the medieval notion of “algorism,” understood as a way of performing calculations with natural numbers. Algorism goes as far back as the 9th century when the Persian astronomer and mathematician Abdullah Muhammad bin Musa al-Khwarizmi (circa 780–850) was indirectly responsible for coining the term. When his scripts were translated into Latin in the 12th century, his name was rendered as “Algorithmi.”1 These scripts described the basic methods of arithmetic in the Hindu-Arabic numeral system, which much later formed the basic operations of computer processors (Miyazaki, 2012). As Wolfgang Thomas describes, many paragraphs of the scripts translated from al-Khwarizmi’s text “Computing with the Indian Numbers” started with the phrase “Dixit Algorizmi,” where algorithm referred to a “process of symbol manipulation”
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