Building the Star Trek Computer

This chapter explores the ways in which Google, Apple, and other corporations have turned the development of cultural algorithms into epistemological quests for both self-knowledge and universal knowledge. This effort to construct a new framework for reality has its roots in Diderot and d’Alembert’s Encyclopédie, a keystone of the European Enlightenment. Apple’s intelligent assistant Siri, Spike Jonze’s film Her, and Google’s ambition to realize the Star Trek computer serve as exemplars for the algorithmic pursuit of knowledge. These quests are both romantic and rational, seeking a transcendent state of knowing, a state that can be reached only with mechanisms that ultimately eclipse the human. Through their ambitions to develop algorithms that can “answer, converse, and anticipate” with ever-greater intimacy, the technology titans shaping our algorithmic future are constructing a new epistemological framework of what is knowable and desirable: an intellectual hierarchy of needs that will ultimately map out not only the public sphere of information but the interior space of human identity.

Counting Bitcoin

This chapter uses the growing dominance of algorithmic high frequency trading in finance to frame a reading of Bitcoin and related cryptocurrencies. By defining the unit of exchange through computational cycles, Bitcoin fundamentally shifts the faith-based community of currency from a materialist to an algorithmic value system. Algorithmic arbitrage is forcing similar transitions in the attribution of value and meaning in many spaces of cultural exchange, from Facebook and Google’s Page Rank algorithm to journalism. The fundamental shift from valuing the cultural object itself to valuing the networks of relations that the object establishes or supports leads to new practices and aesthetics of production, where form and genre give way to memes and nebulous collaborative works. Using Bitcoin and its underlying blockchain technology as an example of this new value model, the chapter considers the consequences of programmable value for the notion of a public sphere in the twenty-first century, an era when arbitrage trumps content.

House of Cards: The Aesthetics of Abstraction

This chapter explores the rise of algorithmic aesthetics through the lens of Netflix. The company’s rejection of a big-data statistics approach to taste in favor of a hybrid human-computational model has led to the Borges-esque project of taxonomizing all real and potential films into one of 76,897 genres. This massive analytical enterprise shapes the company’s creative investments in original work, particularly its original television series House of Cards. The story of the show’s development, distribution, and aesthetics illuminates algorithmic models of culture that are increasingly influential and inescapable. House of Cards embodies a pillar of the algorithmic age: the seduction of bespoke and intimate content personalization underwritten by monolithic computational enterprises. The chapter closes by arguing that Netflix demonstrates the power and pitfalls of cultural arbitrage by manipulating certain kinds of computational abstraction to achieve cultural and financial success.

Introduction

The introduction lays out the central argument of the book: that algorithms are best understood as complex “culture machines” that we engage on the levels of magical thinking, epistemology, social identity, and ideology as well as rationality and computation. Opening with a discussion of Neal Stephenson’s novel Snow Crash and our long-running fascination with the power of language to create the world, the chapter proceeds to describe our current relationship to code in terms of the “cathedral of computation.” This metaphor expresses the intermingling of empiricism and belief that underlies our cultural relationships with algorithms—relationships that are growing more powerful, creative, and intimate every day. In order to understand these systems that tell us where to go, whom to date, and what to think about, we need to develop a method for “algorithmic reading.”

Coda: The Algorithmic Imagination

The coda retraces the genealogy of the algorithm to consider our future prospects for achieving the twinned desires embedded in the heart of effective computability: the quest for universal knowledge and perfect self-knowledge. Central to this is the question of algorithmic imagination, particularly given the startling advances in the field of machine learning. The metaphors we use to access and influence the complexity and processes of computational systems will ultimately determine our prospects for true collaboration with intelligent machines. These questions are particularly vital for the humanities, and the chapter argues for a new mode of scholarly and public engagement with computation: the experimental humanities. This is how we can begin to understand the figure of the algorithm as a new territory for cultural imagination and become true collaborators with culture machines rather than their worshippers or, worse, their pets.

Coding Cow Clicker: The Work of Algorithms

Chapter 4 begins with Ian Bogost’s satirical Facebook game Cow Clicker and its send-up of the “gamification” movement to add quantification and algorithmic thinking to many facets of everyday life. Such games trouble the boundaries between work and play, as do much more serious forms of gamification like Uber and the high-tech warehouse workers whose every second and step are measured for efficiency. Taken together, these new models of work herald a novel form of alienated labor for the algorithmic age. In our science fiction present, humans are processors handling simple tasks assigned by an algorithmic apparatus. Drawing on the historical figure of the automaton, a remarkable collection of Mechanical Turk-powered poetry titled Of the Subcontract, and Adam Smith’s conception of empathy in his Theory of Moral Sentiments, the chapter explores the consequences of computational capitalism on politics, empathy, and social value.

What Is an Algorithm?

This chapter defines the algorithm as a critical concept across four intellectual strands, beginning with its foundations in computer science and the notion of “effective computability.” The second strand considers cybernetics and ongoing debates about embodiment, abstraction, cognition, and information theory. The third explores magic and its overlap with symbolism, engaging with notions of software, “sourcery,” and the power of metaphors to represent reality. The fourth draws in the long history of technicity and humanity’s coevolution with our cultural tools. Synthesizing these threads, the chapter offers a definition of the algorithm as culture machine in the context of process and implementation, and closes with a summary of the essential facets of algorithmic reading and a brief glimpse of algorithmic imagination.