From machine learning and artificial intelligence to blockchain or simpler news-feed filtering, automated systems can transform the social world in ways that are just starting to be imagined.
Redefining these emergent technologies as the new systems of knowing, pioneering scholar David Beer examines the acute tensions they create and how they are changing what is known and what is knowable. Drawing on cases ranging from the art market and the smart home through to financial tech, AI patents and neural networks, he develops key concepts for understanding the framing, envisioning and implementation of algorithms.
This book will be of interest to anyone who is concerned with the rise of algorithmic thinking and the way it permeates society.
Social media platforms hold vast amounts of biographical data about our lives. They repackage our past content as ‘memories’ and deliver them back to us. But how does that change the way we remember?
Drawing on original qualitative research as well as industry documents and reports, this book critically explores the process behind this new form of memory making. In asking how social media are beginning to change the way we remember, it will be essential reading for scholars and students who are interested in understanding the algorithmically defined spaces of our lives.
This chapters explores the pushing back of the boundaries of the known and the knowable. Taking Katherine Hayle’s concept of the ‘cognizer’, the chapter looks at how super cognizers are merging that act as bridges into an algorithmic new life. The chapter then develops a series of features of these super cognizers and uses these to think about the tensions created and agency meshes into the form of new forms of knowing. The chapter uses this central concept to think about the tension created by the stretching of the known.
Exploring the tensions that are created as different forms of agency mesh, this chapter looks at where the human actor is reintegrated into algorithmic thinking. Using a case study of a large risk-management system, it looks directly at how the boundaries around the acceptability of automation are managed. The chapter argues that notions of overstepping and of too much automation are embedded into understandings of these limits. The chapter looks at how human agency is circumscribed within algorithmic thinking, and how limits are boundaries are managed and breached in the expansion of algorithmic systems.
Algorithmic thinking creates both new knowns and new unknowns. This chapter reflects on the tension generated by unknowability. Drawing on Georges Bataille’s concept of ‘nonknowledge’, the chapter examines the historical development of advancing neural network technologies. The chapter argues that the presence of nonknowledge is now pursued in the advancement of these forms of automation and AI. It closes by reflecting on what the presence of nonknowledge might mean for the development of algorithmic thinking and how we can identify a suspension knowing that operates in these systems.
Drawing together the threads of the book, this chapter argues that algorithmic thinking can only be understood through an analysis of its tensions. It looks at the different forces and tensions explored throughout the book to build upon this central argument. In addition, the chapter then turns to Michel Foucault’s concept of the ‘will to know’, arguing that what we are now seeing is a mutation of this into a desire or will to automate.
Taking case studies of the art market and the smart home, this chapter looks at the sidelining of the human within algorithmic systems. Focusing on the application of blockchain, the chapter looks at the vulnerabilities within systems and how humans are perceived to represent weak points within data systems. The chapter argues that a posthuman security is emerging, in which the human is bypassed in order to produce images of a secure society.
Beginning by thinking about the broader shifts towards algorithmic processes and systems, this chapter reflects on the core issues discussed in the book. In particular, it develops the idea of algorithmic thinking and looks at how this might be contextualized. The chapter introduces the idea of the ‘algorithmic new life’ and how this conception of the changes algorithms will bring is crucial to future developments. The chapter closes by looking at the importance of tensions in understanding algorithms and provides an outline of the two key tensions that structure the book’s content.
Social media profiles inevitably leave traces of a life being lived. These biographical data trails are a tempting resource for ‘platform capitalism’ (Langley & Leyshon, 2017; Srnicek, 2017). As they have integrated themselves deeply into everyday routines and interactions, social media have captured a wealth of biographical information about their users. The production and maintenance of profiles has led to the recording and sharing of detailed documentary impressions. This accumulation of the day-to-day has led to the conditions in which prior content can be readily repurposed to suit the rapid circulations of social media. Moving beyond their initial remit as communication and networking platforms, social media have expanded to become memory devices. As people’s lives are captured, social media platforms continue to seek out ways to recirculate these traces and to render them meaningful for the individual user. The archive is vast, and so automated approaches to memory making have been deployed in order to resurface this past content, selecting what should be visible and rendering it manageable. It is here that this book makes an intervention – this is a book about algorithmic memory making within social media. What is particularly important, as we will show, are the ways that social media’s automated systems are actively sorting the past on behalf of the user.
In a short fragment composed around 1932, a piece that went unpublished in his lifetime, Walter Benjamin wrote of the ‘excavation’ of memories. Memories, the fragment suggests, are something to be actively mined from the continually piling remnants of everyday life.
Inevitably, classification processes are powerful within any type of archive. The way content is classified shapes how documents are interpreted and, crucially, how they are retrieved. If we approach social media as a form of archive, then we can begin to see how the ordering process of classification and sorting that occur within these media may be powerful for how people engage with their past content and how individual biographies are made accessible. As we will explore, the ordering of the archive is crucial for understanding its functioning and what can be pulled from its vast stores.
The types of archives that are used to document life are powerful in their presence and outcomes. For some it has been placed at the centre of modern power formations. Derrida (1996: 4 n1) famously argued that, ‘there is no political power without control of the archive, if not of memory. Effective democratization can always be measured by this essential criterion: the participation in and the access to the archive, its constitution, and its interpretation.’
If we treat social media as a population of people effectively participating within a large archival structure, then social media bring the politics of the archive to the centre of everyday life and social interaction (see Beer, 2013). Derrida’s point is that the structures of the archive afford its uses and what can then be said with it or retrieved from it. He argues that ‘the technical structure of the archiving archive also determines the structure of the archivable content even in its very coming into existence and in its relationship to the future’ (Derrida, 1996: 17; original emphases).