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.

“[An] essential book… it is required reading as we seriously engage one of the most important debates of our time.”—Sherry Turkle, author of Reclaiming Conversation: The Power of Talk in a Digital Age From drones to Mars rovers—an exploration of the most innovative use of robots today and a provocative argument for the crucial role of humans in our increasingly technological future. In Our Robots, Ourselves, David Mindell offers a fascinating behind-the-scenes look at the cutting edge of robotics today, debunking commonly held myths and exploring the rapidly changing relationships between humans and machines. Drawing on firsthand experience, extensive interviews, and the latest research from MIT and elsewhere, Mindell takes us to extreme environments—high atmosphere, deep ocean, and outer space—to reveal where the most advanced robotics already exist. In these environments, scientists use robots to discover new information about ancient civilizations, to map some of the world’s largest geological features, and even to “commute” to Mars to conduct daily experiments. But these tools of air, sea, and space also forecast the dangers, ethical quandaries, and unintended consequences of a future in which robotics and automation suffuse our everyday lives. Mindell argues that the stark lines we’ve drawn between human and not human, manual and automated, aren’t helpful for understanding our relationship with robotics. Brilliantly researched and accessibly written, Our Robots, Ourselves clarifies misconceptions about the autonomous robot, offering instead a hopeful message about what he calls “rich human presence” at the center of the technological landscape we are now creating.

In the early 1990s, NASA Goddard Space Flight Center started researching and developing autonomous and autonomic ground and spacecraft control systems for future NASA missions. This research started by experimenting with and developing expert systems to automate ground station software and reduce the number of people needed to control a spacecraft. This was followed by research into agent-based technology to develop autonomous ground c- trol and spacecraft. Research into this area has now evolved into using the concepts of autonomic systems to make future space missions self-managing and giving them a high degree of survivability in the harsh environments in which they operate. This book describes much of the results of this research. In addition, it aimstodiscusstheneededsoftwaretomakefutureNASAspacemissionsmore completelyautonomousandautonomic.Thecoreofthesoftwareforthesenew missions has been written for other applications or is being applied gradually in current missions, or is in current development. It is intended that this book should document how NASA missions are becoming more autonomous and autonomic and should point to the way of making future missions highly - tonomous and autonomic. What is not covered is the supporting hardware of these missions or the intricate software that implements orbit and at- tude determination, on-board resource allocation, or planning and scheduling (though we refer to these technologies and give references for the interested reader).

This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cyber security, defence and space.

This book examines how algorithms in criminal justice, education, housing, elections and beyond affect autonomy, freedom, and democracy. This title is also available as Open Access on Cambridge Core.

This two-volume set addresses a variety of human factors issues and engineering concerns across various real-world applications such as aviation and driving, cybersecurity, and healthcare systems. The contents of these books also present recent theories and methods related to human performance, workload and usability assessment in automated and autonomous systems. In this set, the authors discuss both current and developing topics of advanced automation technologies and present emerging practical challenges. Topics covered include unmanned aerial systems and self-driving cars, individual and team performance, human-robot interaction, and operator selection and training. Both practical and theoretical discussions of modern automated and autonomous systems are provided throughout each of the volumes. These books are suitable for those first approaching the issues to those well versed in these fast-moving areas, including students, teachers, researchers, engineers, and policy makers alike. Volume 1 - Human Performance in Automated and Autonomous Systems: Current Theory and Methods Volume 2 - Human Performance in Automated and Autonomous Systems: Emerging Issues and Practical Perspectives

Dr. Greg Zacharias, former Chief Scientist of the United States Air Force (2015-18), explores next steps in autonomous systems (AS) development, fielding, and training. Rapid advances in AS development and artificial intelligence (AI) research will change how we think about machines, whether they are individual vehicle platforms or networked enterprises. The payoff will be considerable, affording the US military significant protection for aviators, greater effectiveness in employment, and unlimited opportunities for novel and disruptive concepts of operations. Autonomous Horizons: The Way Forward identifies issues and makes recommendations for the Air Force to take full advantage of this transformational technology.

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs

For some, automation will usher in a labor-free utopia; for others, it signals a disastrous age-to-come. Yet whether seen as dream or nightmare, automation, argues Munn, is ultimately a fable that rests on a set of triple fictions. There is the myth of full autonomy, claiming that machines will take over production and supplant humans. But far from being self-acting, technical solutions are piecemeal; their support and maintenance reveals the immense human labor behind "autonomous" processes. There is the myth of universal automation, with technologies framed as a desituated force sweeping the globe. But this fiction ignores the social, cultural, and geographical forces that shape technologies at a local level. And, there is the myth of automating everyone, the generic figure of "the human" at the heart of automation claims. But labor is socially stratified and so automation's fallout will be highly uneven, falling heavier on some (immigrants, people of color, women) than others. Munn moves from machine minders in China to warehouse pickers in the United States to explore the ways that new technologies do (and don't) reconfigure labor. Combining this rich array of human stories with insights from media and cultural studies, Munn points to a more nuanced, localized, and racialized understanding of the "future of work."

The International Conference on Intelligent Unmanned Systems 2011 was organized by the International Society of Intelligent Unmanned Systems and locally by the Center for Bio-Micro Robotics Research at Chiba University, Japan. The event was the 7th conference continuing from previous conferences held in Seoul, Korea (2005, 2006), Bali, Indonesia (2007), Nanjing, China (2008), Jeju, Korea (2009), and Bali, Indonesia (2010). ICIUS 2011 focused on both theory and application, primarily covering the topics of robotics, autonomous vehicles, intelligent unmanned technologies, and biomimetics. We invited seven keynote speakers who dealt with related state-of-the-art technologies including unmanned aerial vehicles (UAVs) and micro air vehicles (MAVs), flapping wings (FWs), unmanned ground vehicles (UGVs), underwater vehicles (UVs), bio-inspired robotics, advanced control, and intelligent systems, among others. This book is a collection of excellent papers that were updated after presentation at ICIUS2011. All papers that form the chapters of this book were reviewed and revised from the perspective of advanced relevant technologies in the field. The aim of this book is to stimulate interactions among researchers active in the areas pertinent to intelligent unmanned systems.