This book explores the fundamental contradiction at the heart of the digital environment: technology offers all manner of promises, yet habitually fails to deliver. This failure often arises from numerous problems: the proficiency of the technology or end-user, policy failure at various levels, or a combination of these. Solutions such as better technology and more effective end-user education are often put into place to solve these failures. Mike Healy argues that such approaches are inherently faulty drawing upon qualitative research informed by Marx’s theory of alienation. Using Marx’s theory, he considers participants in three distinct settings: the workplace of information and communications technology (ICT) professionals; university scholars researching the ethical and societal implications of our digital environment; and a group of pensioners living in South London, UK, undertaking ICT training. By delving beneath the surface of how digital technologies are created, researched and experienced, this study illustrates the contradictory nature of our digital lives, as they directly arise from the needs of capitalism. The book also places Marx’s theory in contrast to the mainstream approaches derived from Seaman and Blauner. In researching and comprehending ICT, this book reaffirms the superior explanatory power of Marx’s theory of alienation.

This book explores a fundamental contradiction of the digital environment: technology offers all manner of promises, yet habitually fails to deliver. By exploring how digital technologies are created, researched and experienced, Healy illustrates the contradictory nature of our digital lives, as they directly arise from the needs of capitalism.

The past several years have brought staggering advances in the field of Artificial Intelligence. And Marxist analysis has to keep up: while machines were always central to Marxist analysis, modern AI is a new kind of machine that Marx could not have anticipated. Inhuman Power explores the relationship between Marxist theory and AI through three approaches, each using the lens of a different Marxist theoretical concept. While the idea of widespread AI tends to be celebrated as much as questioned, a deeper analysis of its reach and potential produces a more complex and disturbing picture than has been identified. Inhuman Power argues that on its current trajectory, AI is likely to render humanity obsolete and that the only way to prevent it is a communist revolution.

A wide-ranging, myth-busting and balanced materialist account of an overheated discourse

In the Nineteenth-century, English textile workers responded to the introduction of new technologies on the factory floor by smashing them to bits. For years the Luddites roamed the English countryside, practicing drills and manoeuvres that they would later deploy on unsuspecting machines. The movement has been derided by scholars as a backwards-looking and ultimately ineffectual effort to stem the march of history; for Gavin Mueller, the movement gets at the heart of the antagonistic relationship between all workers, including us today, and the so-called progressive gains secured by new technologies. The luddites weren't primitive and they are still a force, however unconsciously, in the workplaces of the twenty-first century world. Breaking Things at Work is an innovative rethinking of labour and machines, leaping from textile mills to algorithms, from existentially threatened knife cutters of rural Germany to surveillance-evading truckers driving across the continental United States. Mueller argues that the future stability and empowerment of working-class movements will depend on subverting these technologies and preventing their spread wherever possible. The task is intimidating, but the seeds of this resistance are already present in the neo-Luddite efforts of hackers, pirates, and dark web users who are challenging surveillance and control, often through older systems of communication technology.

This book argues that Marxist theory is essential for understanding the contemporary industrialization of the form of artificial intelligence (AI) called machine learning. It includes a political economic history of AI, tracking how it went from a fringe research interest for a handful of scientists in the 1950s to a centerpiece of cybernetic capital fifty years later. It also includes a political economic study of the scale, scope and dynamics of the contemporary AI industry as well as a labour process analysis of commercial machine learning software production, based on interviews with workers and management in AI companies around the world, ranging from tiny startups to giant technology firms. On the basis of this study, Steinhoff develops a Marxist analysis to argue that the popular theory of immaterial labour, which holds that information technologies increase the autonomy of workers from capital, tending towards a post-capitalist economy, does not adequately describe the situation of high-tech digital labour today. In the AI industry, digital labour remains firmly under the control of capital. Steinhoff argues that theories discerning therein an emergent autonomy of labour are in fact witnessing labour’s increasing automation.