What Algorithms Want

This book explores the cultural figure of the algorithm as it operates through contemporary digital culture. Drawing on sources that range from Neal Stephenson’s Snow Crash to Diderot’s Encyclopédie, from Adam Smith to the Star Trek computer, it explores the gap between theoretical ideas and pragmatic instructions. Humans have always believed that certain invocations—the marriage vow, the shaman’s curse—do not merely describe the world but make it. This book argues that the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in the mathematical concept of “effective computability” but also in cybernetics, philosophy, and magical thinking. After bringing the full history of the term into view, the book describes how the algorithm attempts to translate between the idealized space of computation and a messy reality, with unpredictable and sometimes fascinating results. Case studies of this implementation gap include the development of intelligent assistants like Siri, Google’s goal of anticipating our questions, the rise of algorithmic aesthetics at Netflix, Ian Bogost’s satiric Facebook game Cow Clicker, Uber’s cartoon maps and black box accounting, and the revolutionary economics of Bitcoin. If we want to understand the gap between abstraction and messy reality, we need to build a model of “algorithmic reading” and scholarship that attends to process as part of a new experimental humanities.

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.

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.

Hyperloops do not threaten the notion of an effective procedure

This paper develops my (BJPS 2009) criticisms of the philosophical significance of a certain sort of infinitary computational process, a hyperloop. I start by considering whether hyperloops suggest that ‘effectively computable’ is vague (in some sense). I then consider and criticise two arguments by Hogarth, who maintains that hyperloops undermine the very idea of effective computability. I conclude that hyperloops, on their own, cannot threaten the notion of an effective procedure.Published in Lecture Notes in Computer Science 5635: 68–78.

NONSTANDARD MODELS IN RECURSION THEORY AND REVERSE MATHEMATICS

We give a survey of the study of nonstandard models in recursion theory and reverse mathematics. We discuss the key notions and techniques in effective computability in nonstandard models, and their applications to problems concerning combinatorial principles in subsystems of second order arithmetic. Particular attention is given to principles related to Ramsey’s Theorem for Pairs.