Catálogo de publicaciones - libros
Título de Acceso Abierto
The Everyday Life of an Algorithm
Daniel Neyland
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Science and Technology Studies; Culture and Technology; Computers and Society; Data Structures and Information Theory; Mathematical Logic and Formal Languages
Disponibilidad
Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
---|---|---|---|---|
No requiere | 2019 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-030-00577-1
ISBN electrónico
978-3-030-00578-8
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2019
Información sobre derechos de publicación
© The Editor(s) (if applicable) and The Author(s) 2019
Cobertura temática
Tabla de contenidos
Introduction: Everyday Life and the Algorithm
Daniel Neyland
This chapter introduces the recent academic literature on algorithms and some of the popular concerns that have been expressed about algorithms in mainstream media, including the power and opacity of algorithms. The chapter suggests that, in place of opening algorithms to greater scrutiny, the academic literature tends to play on this algorithmic drama. As a counter move, this chapter suggests taking seriously what we might mean by the everyday life of the algorithm. Several approaches to everyday life are considered and a set of three analytic sensibilities developed for interrogating the everyday life of the algorithm in subsequent chapters. These sensibilities comprise: how do algorithms participate in the everyday? How do algorithms compose the everyday? And how (to what extent, through what means) does the algorithmic become the everyday? The chapter ends by setting out the structure of the rest of the book.
Pp. 1-20
Experimentation with a Probable Human-Shaped Object
Daniel Neyland
This chapter sets out the algorithms that will form the focus for this book and their human and non-human associations. The chapter focuses on one particular algorithmic system developed for public transport security and explores the ways in which the system provided a basis for experimenting with what computer scientists termed human-shaped objects. In contrast to much of the social science literature on algorithms that suggests the algorithm itself is more or less fixed or inscrutable, this chapter will instead set out one basis for ethnographically studying the algorithm up-close and in detail. Placing algorithms under scrutiny opens up the opportunity for studying their instability and the ceaseless experimentation to which they are subjected. An important basis for this experimentation, the chapter will suggest, is elegance. The chapter will suggest that elegance opens up a distinct way to conceive of the experimental prospects of algorithms under development and their ways of composing humans.
Pp. 21-43
Accountability and the Algorithm
Daniel Neyland
This chapter develops insights on human-shaped objects and elegance in exploring the possibility of rendering the everyday life of algorithms accountable and the form such accountability might take. Although algorithmic accountability is currently framed in terms of openness and transparency, the chapter draws on ethnographic engagements with the algorithmic system under development to show empirically the difficulties (and indeed pointlessness) of achieving this kind of openness. Rather than presenting an entirely pessimistic view, the chapter suggests that alternative forms of accountability are possible. In place of transparency, the chapter focuses on science and technology studies (STS) work that pursues the characteristics, agency, power and effect of technologies as the upshot of the network of relations within which a technology is positioned. Moving away from the idea that algorithms have fixed, essential characteristics or straightforward power or agency, opens up opportunities for developing a distinct basis of accountability in action.
Pp. 45-71
The Deleting Machine and Its Discontents
Daniel Neyland
Deletion was a central component of the algorithmic system studied in this book. Deletion is also a key motif of contemporary data management: concepts such as proportionality, necessity, a shelf-life for data, right to be forgotten or right to erasure and specific definitions of privacy all relate to deletion. In this chapter, the calculative basis for deletion will be used to provide insight into not just the content of an algorithm, but its everyday composition, effects and associated expectations. However, the chapter suggests that deletion also poses a particular kind of problem: the creation of nothing (the deleted) needs to be continually proven. These focal points and the difficulties of providing proof are used to address suggestions in contemporary research that algorithms are powerful and agential, easily able to enact and execute orders. Instead, the chapter calls for more detailed analysis of what constitutes algorithmic success and failure.
Pp. 73-92
Demonstrating the Algorithm
Daniel Neyland
This chapter explores the problems involved in demonstrating an algorithmic system to a variety of audiences. As the project reached its final deadlines and put on demonstrations of the technology-under-development to various audiences—including the project funders—it became ever more apparent that in a number of ways promises made to key audiences, may not be met. In project meetings, it became rapidly apparent that a number of ways of constituting a response to different audiences and their imagined demands could be offered. To manage this problem, the chapter shows that a range of different more or less ‘genuine’ demonstrations with greater or lesser integrity were discursively assembled by the project team, and ways to locate and populate, witness and manage the assessment of these demonstrations were brought to the table. The notion of integrity is used to incorporate sight, materiality and morality into the growing literature on algorithms.
Pp. 93-122
Market Value and the Everyday Life of the Algorithm
Daniel Neyland
The final chapter explores how a market can be built for an algorithmic system. It draws together studies of algorithms with the growing literature in science and technology studies (STS) on markets and the composition of financial value. It uses performativity to explore market making for algorithms. To accomplish market work and build a value for the algorithm, the chapter suggests, the project coordinators had to build a market of willing customers who were then constituted as a means to attract others to (potentially) invest in the system. This final chapter will suggest that market work is an important facet of the everyday life of an algorithm, without which algorithmic systems such as the one featured in this book, would not endure. The chapter concludes with an analysis of the distinct and only occasionally integrated everyday lives of the algorithm.
Pp. 123-137