A consensus-shattering account of automation technologies and their effect on workplaces and the labor market In this consensus-shattering account of automation technologies, Aaron Benanav investigates the economic trends that will shape our working lives far into the future. Silicon Valley titans, politicians, techno-futurists, and social critics have united in arguing that we are on the cusp of an era of rapid technological automation, heralding the end of work as we know it. But does the muchdiscussed “rise of the robots” really explain the long-term decline in the demand for labor? Automation and the Future of Work uncovers the deep weaknesses of twenty-first-century capitalism and the reasons why the engine of economic growth keeps stalling. Equally important, Benanav goes on to salvage from automation discourse its utopian content: the positive vision of a world without work. What social movements, he asks, are required to propel us into post-scarcity if technological innovation alone can’t deliver it? In response to calls for a permanent universal basic income that would maintain a growing army of redundant workers, he offers a groundbreaking counterproposal.

Automating technologies threaten to usher in a workless future. But this can be a good thing—if we play our cards right. Human obsolescence is imminent. The factories of the future will be dark, staffed by armies of tireless robots. The hospitals of the future will have fewer doctors, depending instead on cloud-based AI to diagnose patients and recommend treatments. The homes of the future will anticipate our wants and needs and provide all the entertainment, food, and distraction we could ever desire. To many, this is a depressing prognosis, an image of civilization replaced by its machines. But what if an automated future is something to be welcomed rather than feared? Work is a source of misery and oppression for most people, so shouldn’t we do what we can to hasten its demise? Automation and Utopia makes the case for a world in which, free from need or want, we can spend our time inventing and playing games and exploring virtual realities that are more deeply engaging and absorbing than any we have experienced before, allowing us to achieve idealized forms of human flourishing. The idea that we should “give up” and retreat to the virtual may seem shocking, even distasteful. But John Danaher urges us to embrace the possibilities of this new existence. The rise of automating technologies presents a utopian moment for humankind, providing both the motive and the means to build a better future.

This book highlights the latest advancements in the use of automated systems in the design, construction, operation and future of the built environment and its occupants. It considers how the use of automated decision-making frameworks, artificial intelligence and other technologies of automation are presently impacting the practice of architects, engineers, project managers and contractors, and articulates the near future changes to workflows, legal frameworks and the wider AEC industry. This book surveys and compiles the use of city apps, robots that operate buildings and fabricate structural elements, 3D printing, drones, sensors, algorithms, and advanced prefabricated modules. The book also contributes to the growing literature on smart cities, and explores the impacts on data privacy and data sovereignty that arise through the use of sensors, digital twins and intelligent transport systems. It provides a useful reference for further research and development in the area of automation in design and construction to architects, engineers, project managers, superintendents and construction lawyers, contractors, policy makers, and students.

Artificial Intelligence for Future Generation Robotics offers a vision for potential future robotics applications for AI technologies. Each chapter includes theory and mathematics to stimulate novel research directions based on the state-of-the-art in AI and smart robotics. Organized by application into ten chapters, this book offers a practical tool for researchers and engineers looking for new avenues and use-cases that combine AI with smart robotics. As we witness exponential growth in automation and the rapid advancement of underpinning technologies, such as ubiquitous computing, sensing, intelligent data processing, mobile computing and context aware applications, this book is an ideal resource for future innovation. - Brings AI and smart robotics into imaginative, technically-informed dialogue - Integrates fundamentals with real-world applications - Presents potential applications for AI in smart robotics by use-case - Gives detailed theory and mathematical calculations for each application - Stimulates new thinking and research in applying AI to robotics

A New York Times bestselling author and tech columnist's counter-intuitive guide to staying relevant - and employable - in the machine age by becoming irreplaceably human. It's not a future scenario any more. We've been taught that to compete with automation and AI, we'll have to become more like the machines themselves, building up technical skills like coding. But, there's simply no way to keep up. What if all the advice is wrong? And what do we need to do instead to become futureproof? We tend to think of automation as a blue-collar phenomenon that will affect truck drivers, factory workers, and other people with repetitive manual jobs. But it's much, much broader than that. Lawyers are being automated out of existence. Last year, JPMorgan Chase built a piece of software called COIN, which uses machine learning to review complicated contracts and documents. It used to take the firm's lawyers more than 300,000 hours every year to review all of those documents. Now, it takes a few seconds, and requires just one human to run the program. Doctors are being automated out of existence, too. Last summer, a Chinese tech company built a deep learning algorithm that diagnosed brain cancer and other diseases faster and more accurately than a team of 15 top Chinese doctors. Kevin Roose has spent the past few years studying the question of how people, communities, and organisations adapt to periods of change, from the Industrial Revolution to the present. And the insight that is sweeping through Silicon Valley as we speak -- that in an age dominated by machines, it's human skills that really matter - is one of the more profound and counter-intuitive ideas he's discovered. It's the antidote to the doom-and-gloom worries many people feel when they think about AI and automation. And it's something everyone needs to hear. In nine accessible, prescriptive chapters, Roose distills what he has learned about how we will survive the future, that the way to become futureproof is to become incredibly, irreplaceably human.

Much has been written about the prospects of automation in recent years. While many have raised concerns over the threat of technological mass unemployment, others have anticipated a fully automated communist utopia which will provide material abundance to everyone. (De)Automating the Future gathers chapters that critically investigate automation’s ambivalences from inter-disciplinary Marxist perspectives. The contributions raise questions about automation’s affordances for postcapitalism, its transformation of manual and mental labour, and its role in the intensification of class antagonisms and exploitation.

From hidden connections in big data to bots spreading fake news, journalism is increasingly computer-generated. An expert in computer science and media explains the present and future of a world in which news is created by algorithm. Amid the push for self-driving cars and the roboticization of industrial economies, automation has proven one of the biggest news stories of our time. Yet the wide-scale automation of the news itself has largely escaped attention. In this lively exposé of that rapidly shifting terrain, Nicholas Diakopoulos focuses on the people who tell the stories—increasingly with the help of computer algorithms that are fundamentally changing the creation, dissemination, and reception of the news. Diakopoulos reveals how machine learning and data mining have transformed investigative journalism. Newsbots converse with social media audiences, distributing stories and receiving feedback. Online media has become a platform for A/B testing of content, helping journalists to better understand what moves audiences. Algorithms can even draft certain kinds of stories. These techniques enable media organizations to take advantage of experiments and economies of scale, enhancing the sustainability of the fourth estate. But they also place pressure on editorial decision-making, because they allow journalists to produce more stories, sometimes better ones, but rarely both. Automating the News responds to hype and fears surrounding journalistic algorithms by exploring the human influence embedded in automation. Though the effects of automation are deep, Diakopoulos shows that journalists are at little risk of being displaced. With algorithms at their fingertips, they may work differently and tell different stories than they otherwise would, but their values remain the driving force behind the news. The human–algorithm hybrid thus emerges as the latest embodiment of an age-old tension between commercial imperatives and journalistic principles.