Search

Cognitive Assistant Supported Human-Robot Collaboration covers the design and development of cognitive assistants in the smart factory era, its application domains, challenges, and current state of the art in assistance systems with collaborative robotics and IoT technologies, standards, platforms, and solutions. This book also provides a sociotechnical view of collaborative work in human-robot teams, investigating specific methods and techniques to analyze assistance systems. This will provide readers with a comprehensive overview of how cognitive assistants function and work in human-robot teams. - Introduces fundamental concepts of cognitive assistants and human-robot collaboration - Investigates the optimization capabilities of human-cyber physical systems - Discusses planning and implementation of cognitive assistant projects - Explores concepts and design elements of human collaborative workspaces

Providing a high level of autonomy for a human-machine team requires assumptions that address behavior and mutual trust. The performance of a human-machine team is maximized when the partnership provides mutual benefits that satisfy design rationales, balance of control, and the nature of autonomy. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a'collective intelligence. Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans.Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams focuses on human-machine trust and'assured performance and operation in order to realize the potential of autonomy. This book aims to take on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge the knowledge gaps, but also to advance this science to develop better solutions. - Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomy - Reviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the science - Offers a path forward to solutions - Investigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates

Exploring the Metaverse: Challenges and Applications explores the various applications and challenges facing the metaverse, from privacy and security concerns to questions about the economy and ethical considerations. Drawing on insights from experts in technology, ethics, and economics, the book's authors provide a comprehensive overview of the metaverse and its potential implications. Through a series of engaging essays and thought-provoking case studies, they examine the complex issues facing the metaverse, such as the role of virtual identity, the impact on social interactions, and the potential for addiction. Finally, they explore potential solutions to these challenges, from technological innovations to policy interventions. - Provides a comprehensive overview of the metaverse, its origins, and its potential implications - Offers a clear understanding of what the metaverse is and why it matters - Presents in-depth analysis of the key challenges facing the metaverse, such as privacy and security concerns, economic implications, and ethical considerations - Explores potential solutions to the challenges facing the metaverse, including technological innovations, policy interventions, and social norms and practices that could help to mitigate the risks and maximize the benefits of this emerging technology

Is Justice Real When'Reality is Not?: Constructing Ethical Digital Environments examines how frameworks and concepts of justice should evolve in virtual worlds. Directed at researchers working in, or with an interest in virtual reality, as well as those interested in the fields of artificial intelligence and justice, this book covers research regarding impacts on human psychological states existing within alternative ethical frameworks. With chapters dedicated to behavioral impacts of virtual events, robotics and'unconscious', and human psychological states of role playing and existing, readers will be well-equipped to navigate the virtual worlds in which millions of people currently spend time. - Provides an introduction into virtual worlds in which humans increasingly spend significant time - Analyzes the psychological impact on humans of spending time in virtual worlds - Discusses ethical and justice frameworks, robotics, the psychology of role playing and future virtual worlds

Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of'shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these'machines'may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers'think through this change in human terms,'the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. - Discusses the foundations, metrics, and applications of human-machine systems - Considers advances and challenges in the performance of autonomous machines and teams of humans - Debates theoretical human-machine ecosystem models and what happens when machines malfunction

Clinical Engineering Handbook, Second Edition, covers modern clinical engineering topics, giving experienced professionals the necessary skills and knowledge for this fast-evolving field. Featuring insights from leading international experts, this book presents traditional practices, such as healthcare technology management, medical device service, and technology application. In addition, readers will find valuable information on the newest research and groundbreaking developments in clinical engineering, such as health technology assessment, disaster preparedness, decision support systems, mobile medicine, and prospects and guidelines on the future of clinical engineering.As the biomedical engineering field expands throughout the world, clinical engineers play an increasingly important role as translators between the medical, engineering and business professions. In addition, they influence procedures and policies at research facilities, universities, and in private and government agencies. This book explores their current and continuing reach and its importance. - Presents a definitive, comprehensive, and up-to-date resource on clinical engineering - Written by worldwide experts with ties to IFMBE, IUPESM, Global CE Advisory Board, IEEE, ACCE, and more - Includes coverage of new topics, such as Health Technology Assessment (HTA), Decision Support Systems (DSS), Mobile Apps, Success Stories in Clinical Engineering, and Human Factors Engineering

Healthcare Technology Management Systems provides a model for implementing an effective healthcare technology management (HTM) system in hospitals and healthcare provider settings, as well as promoting a new analysis of hospital organization for decision-making regarding technology. Despite healthcare complexity and challenges, current models of management and organization of technology in hospitals still has evolved over those established 40-50 years ago, according to totally different circumstances and technologies available now. The current health context based on new technologies demands working with an updated model of management and organization, which requires a re-engineering perspective to achieve appropriate levels of clinical effectiveness, efficiency, safety and quality. Healthcare Technology Management Systems presents best practices for implementing procedures for effective technology management focused on human resources, as well as aspects related to liability, and the appropriate procedures for implementation. - Presents a new model for hospital organization for Clinical Engineers and administrators to implement Healthcare Technology Management (HTM) - Understand how to implement Healthcare Technology Management (HTM) and Health Technology Assessment (HTA) within all types of organizations, including Human Resource impact, Technology Policy and Regulations, Health Technology Planning (HTP) and Acquisition, as well as Asset and Risk Management - Transfer of knowledge from applied research in CE, HTM, HTP and HTA, from award-winning authors who are active in international health organizations such as the World Health Organization (WHO), Pan American Health Organization (PAHO), American College of Clinical Engineering (ACCE) and International Federation for Medical and Biological Engineering (IFMBE)