Human Machine Shared Contexts

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

Interdependent Human-Machine Teams: The Path to Autonomy examines the foundations, metrics, and applications of human-machine systems; the legal ramifications of autonomy; trust by the public, and trust by the users and AI systems of their users, integrating concepts from various disciplines such as AI, machine learning, social sciences, quantum mechanics, and systems engineering. In this book, world-class researchers, engineers, ethicists, and social scientists discuss what machines, humans, and systems should discuss with each other, to policy makers, and to the public. The book establishes the meaning and operation of "shared contexts” between humans and machines, policy makers, and the public. This book explores how human-machine systems affect targeted audiences (researchers, machines, robots, users, regulators, etc.) and society, as well as future ecosystems composed of humans, machines, and systems.

This book focuses on the importance of human factors in the development of safe and reliable unmanned systems. It discusses current challenges such as how to improve the perceptual and cognitive abilities of robots, develop suitable synthetic vision systems, cope with degraded reliability in unmanned systems, predict robotic behavior in case of a loss of communication, the vision for future soldier–robot teams, human–agent teaming, real-world implications for human–robot interaction, and approaches to standardize both the display and control of technologies across unmanned systems. Based on the AHFE 2019 International Conference on Human Factors in Robots and Unmanned Systems, held on July 24–28, 2019, Washington D.C., USA, this book fosters new discussions and stimulates new advances in the development of more reliable, safer, and highly functional devices for carrying out automated and concurrent tasks.

The five-volume set CCIS 1832-1836 contains the extended abstracts of the posters presented during the 25th International Conference on Human-Computer Interaction, HCII 2023, which was held as a hybrid event in Copenhagen, Denmark, in July 2023. The total of 1578 papers and 396 posters included in the 47 HCII 2023 proceedings volumes were carefully reviewed and selected from the 7472 contributions.The posters presented in these five volumes are organized in topical sections as follows: Part I: ​HCI Design: Theoretical Approaches, Methods and Case Studies; Multimodality and Novel Interaction Techniques and Devices; Perception and Cognition in Interaction; Ethics, Transparency and Trust in HCI; User Experience and Technology Acceptance Studies.Part II: Supporting Health, Psychological Wellbeing, and Fitness; Design for All, Accessibility and Rehabilitation Technologies; Interactive Technologies for the Aging Population.Part III: ​Interacting with Data, Information and Knowledge; Learning and Training Technologies; Interacting with Cultural Heritage and Art.Part IV: ​Social Media: Design, User Experiences and Content Analysis; Advances in eGovernment Services; eCommerce, Mobile Commerce and Digital Marketing: Design and Customer Behavior; Designing and Developing Intelligent Green Environments; (Smart) Product Design.Part V: ​Driving Support and Experiences in Automated Vehicles; eXtended Reality: Design, Interaction Techniques, User Experience and Novel Applications; Applications of AI Technologies in HCI.

This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.

This book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment. DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds)

Innovation in Music: Technology and Creativity is a groundbreaking collection bringing together contributions from instructors, researchers, and professionals. Split into two sections, covering composition and performance, and technology and innovation, this volume offers truly international perspectives on ever-evolving practices. Including chapters on audience interaction, dynamic music methods, AI, and live electronic performances, this is recommended reading for professionals, students, and researchers looking for global insights into the fields of music production, music business, and music technology.