Human Machine Shared Contexts

Book Description :

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

Book Description :

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.

Book Description :

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.

Book Description :

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)

Book Description :

Download book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Book Description :

Doctors, patients, investigators, administrators, and policymakers who assign diagnoses assume three elements: the name describes an entity with conceptual or evidentiary boundaries, the person setting the name has a high degree of certainty, and the name has a consensus definition. This book challenges this practice and offers an alternative to assigning diagnoses: quantitating diagnostic uncertainty in personal and public medical plans. This book offers the stakeholders' views participating in a workshop, sponsored by the Barbara Volcker Center/Hospital for Special Surgery, taking place in April 2020, about uncertain diagnoses. Chapters examine the circumstances in which diagnosis names are "unassignable", either because patients do not fit within diagnostic "boxes" or because health abnormalities evolve and change over time. In addition, the book deconstructs the processes of diagnosis and explores how different stakeholders used diagnosis names for various purposes. In examining pertinent questions, the book offers a roadmap to achieving consensus definitions or including measures of uncertainty in personal care, research, and policy. Diagnoses Without Names: Challenges for Medical Care, Research, and Policy is an essential resource for physicians and related professionals, residents, fellows, and graduate students in internal medicine, rheumatology, and clinical immunology as well as investigators, administrators, policymakers.

Book Description :

The aim of the CEEMAS conference series is to provide a biennial forum for the presentation of multi-agent research and development results. With its p- ticular geographicalorientation towards Central and Eastern Europe, CEEMAS has become an internationally recognised event with participants from all over the world. After the successful CEEMAS conferences in St. Petersburg (1999), Cracow (2001) and Prague (2003), the 2005 CEEMAS conference takes place in Budapest. The programme committee of the conference series consists of est- lished researchers from the region and renowned international colleagues, sh- ing the prominent rank of CEEMAS among the leading events in multi-agent systems. In the very competitive ?eld of agent oriented conferences and workshops nowadays(suchasAAMAS,WI/IAT,EUMAS,CIA,MATES)thespecialpro?le of CEEMAS is that it is trying to bridge the gap between applied research achievements and theoretical research activities. Our ambition is to provide a forum for presenting theoretical research with an evident application potential, implemented application prototypes and their properties, as well as industrial case studies of successful (but also unsuccessful) agent technology deployments. This is why the CEEMAS proceedings volume provides a collection of research and application papers. The technical research paper section of the proceedings (see pages 11–499) contains pure research papers as well as research results in application settings while the application papers section (see pages 500–530) contains papers focused on application aspects. The goal is to demonstrate the real life value and commercial reality of multi-agent systems as well as to foster communication between academia and industry in this ?eld.

Book Description :

The abundance of information and increase in computing power currently enable researchers to tackle highly complicated and challenging computational problems. Solutions to such problems are now feasible using advances and innovations from the area of Artificial Intelligence. The general focus of the AIAI conference is to provide insights on how Artificial Intelligence may be applied in real-world situations and serve the study, analysis and modeling of theoretical and practical issues. This volume contains papers selected for presentation at the 6th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI 2010) and held in Larnaca, Cyprus, during October 6–7, 2010. IFIP AIAI 2010 was co-organized by the University of Cyprus and the Cyprus University of Technology and was sponsored by the Cyprus University of Technology, Frederick University and the Cyprus Tourism Organization. AIAI 2010 is the official conference of the WG12.5 “Artificial Intel- gence Applications” working group of IFIP TC12, the International Federation for Information Processing Technical Committee on Artificial Intelligence (AI). AIAI is a conference that grows in significance every year attracting researchers from different countries around the globe. It maintains high quality, standards and welcomes research papers describing technical advances and engineering and ind- trial applications of intelligent systems. AIAI 2010 was not confined to introducing how AI may be applied in real-life situations, but also included innovative methods, techniques, tools and ideas of AI expressed at the algorithmic or systemic level.

Book Description :

There is a growing consensus in the human factors/ergonomics community that human factors research has had little impact on significant applied problems. Some have suggested that the problem lies in the fact that much HF/E research has been based on the wrong type of psychology, an information processing view of psychology that is reductionistic and context-free. Ecological psychology offers a viable alternative, presenting a richer view of human behavior that is holistic and contextualized. The papers presented in these two volumes show the conceptual impact that ecological psychology can have on HF/E, as well as presenting a number of specific examples illustrating the ecological approach to human-machine systems. It is the first collection of papers that explicitly draws a connection between these two fields. While work in this area is only just beginning, the evidence available suggests that taking an ecological approach to human factors/ergonomics helps bridge the existing gap between basic research and applied problems.

Book Description :

The two-volume set LNCS 8525-8526 constitutes the refereed proceedings of the 6th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2014, held as part of the 16th International Conference on Human-Computer Interaction, HCI 2014, in Heraklion, Crete, Greece, in June 2014, jointly with 13 other thematically similar conferences. The total of 1476 papers and 220 posters presented at the HCII 2014 conferences were carefully reviewed and selected from 4766 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The total of 82 contributions included in the VAMR proceedings were carefully reviewed and selected for inclusion in this two-volume set. The 39 papers included in this volume are organized in the following topical sections: interaction devices, displays and techniques in VAMR; designing virtual and augmented environments; avatars and virtual characters; developing virtual and augmented environments.

Book Description :

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Book Description :

In recent years, new applications on computer-aided technologies for telemedicine have emerged. Therefore, it is essential to capture this growing research area concerning the requirements of telemedicine. This book presents the latest findings on soft computing, artificial intelligence, Internet of Things and related computer-aided technologies for enhanced telemedicine and e-health. Furthermore, this volume includes comprehensive reviews describing procedures and techniques, which are crucial to support researchers in the field who want to replicate these methodologies in solving their related research problems. On the other hand, the included case studies present novel approaches using computer-aided methods for enhanced telemedicine and e-health. This volume aims to support future research activities in this domain. Consequently, the content has been selected to support not only academics or engineers but also to be used by healthcare professionals.

Book Description :

Emerald Studies In Finance, Insurance, And Risk Management 7B explores how AI and Automation enhance the basic functions of human resource management.

Book Description :

This volume addresses context from three comprehensive perspectives: first, its importance, the issues surrounding context, and its value in the laboratory and the field; second, the theory guiding the AI used to model its context; and third, its applications in the field (e.g., decision-making). This breadth poses a challenge. The book analyzes how the environment (context) influences human perception, cognition and action. While current books approach context narrowly, the major contribution of this book is to provide an in-depth review over a broad range of topics for a computational context no matter its breadth. The volume outlines numerous strategies and techniques from world-class scientists who have adapted their research to solve different problems with AI, in difficult environments and complex domains to address the many computational challenges posed by context. Context can be clear, uncertain or an illusion. Clear contexts: A father praising his child; a trip to the post office to buy stamps; a policewoman asking for identification. Uncertain contexts: A sneak attack; a surprise witness in a courtroom; a shout of "Fire! Fire!" Contexts as illusion: Humans fall prey to illusions that machines do not (Adelson’s checkerboard illusion versus a photometer). Determining context is not easy when disagreement exists, interpretations vary, or uncertainty reigns. Physicists like Einstein (relativity), Bekenstein (holographs) and Rovelli (universe) have written that reality is not what we commonly believe. Even outside of awareness, individuals act differently whether alone or in teams. Can computational context with AI adapt to clear and uncertain contexts, to change over time, and to individuals, machines or robots as well as to teams? If a program automatically "knows" the context that improves performance or decisions, does it matter whether context is clear, uncertain or illusory? Written and edited by world class leaders from across the field of autonomous systems research, this volume carefully considers the computational systems being constructed to determine context for individual agents or teams, the challenges they face, and the advances they expect for the science of context.

Book Description :

Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time. To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.

Book Description :

The digital transformation of higher education institutions has accelerated in the last decade due to the confluent development of digital technologies. Understanding how artificial intelligence-enabled changes and improvements in universities in relation to teaching, management, sustainability, and research allows researchers to understand the advances and identify the challenges that may arise. This knowledge provides technological instruments as well as cognitive, philosophical, and epistemological tools to address different current issues. Strategy, Policy, Practice, and Governance for AI in Higher Education Institutions offers both empirical and theoretical information focused on artificial intelligence and its various applications in higher education institutions. It includes research results, authoritative overview articles, high quality analysis on trends, comparative studies, and analysis of cases that focus on issues including ethical issues and risks for applying AI in higher education, policies to introduce AI in curricula, and applications in teaching and learning. Covering topics such as artificial intelligence ethics, energy efficiency, and postsecondary administrative leadership, this premier reference source is an essential resource for computer scientists, AI scientists, administration of higher education institutions, educators and faculty of higher education, pre-service teachers, researchers, IT professionals, and academicians.

Book Description :

Artificial Intelligence for Healthcare Applications and Management introduces application domains of various AI algorithms across healthcare management. Instead of discussing AI first and then exploring its applications in healthcare afterward, the authors attack the problems in context directly, in order to accelerate the path of an interested reader toward building industrial-strength healthcare applications. Readers will be introduced to a wide spectrum of AI applications supporting all stages of patient flow in a healthcare facility. The authors explain how AI supports patients throughout a healthcare facility, including diagnosis and treatment recommendations needed to get patients from the point of admission to the point of discharge while maintaining quality, patient safety, and patient/provider satisfaction. AI methods are expected to decrease the burden on physicians, improve the quality of patient care, and decrease overall treatment costs. Current conditions affected by COVID-19 pose new challenges for healthcare management and learning how to apply AI will be important for a broad spectrum of students and mature professionals working in medical informatics. This book focuses on predictive analytics, health text processing, data aggregation, management of patients, and other fields which have all turned out to be bottlenecks for the efficient management of coronavirus patients. Presents an in-depth exploration of how AI algorithms embedded in scheduling, prediction, automated support, personalization, and diagnostics can improve the efficiency of patient treatment Investigates explainable AI, including explainable decision support and machine learning, from limited data to back-up clinical decisions, and data analysis Offers hands-on skills to computer science and medical informatics students to aid them in designing intelligent systems for healthcare Informs a broad, multidisciplinary audience about a multitude of applications of machine learning and linguistics across various healthcare fields Introduces medical discourse analysis for a high-level representation of health texts

Book Description :

The current model for electricity generation and distribution is dominated by centralized power plants which are typically associated with combustion (coal, oil, and natural gas) or nuclear generation units. These power models require distribution from the center to outlying consumers and have many disadvantages concerning the electric utilities, transmission and distribution, and greenhouse gas emissions. This resulted in the modelling and development of cleaner renewable power generation with alternative sources such as photovoltaic (PV), wind, and other sources. Further, due to matured PV technology, constant drop-in installation cost, greenhouse emissions reductions, energy efficiency, reduced transmission and distribution investments, minimization of electric losses, and network support, the development of PV systems is proliferating. In view of this development, this book provides an idea for setting up the PV plant from initial study of the site to plan sizing. Once the first planning is covered, the book focuses on the modeling aspects of power electronics converter and control elements associated with it keeping the operating standards specified for the development of distributed generation systems in check. This book will be useful for industrial professionals and researchers who are working toward modeling of PV plants, and their control in grid connected operation. All the necessary information related to these fields is available in the book.

Book Description :

The two-volume set LNCS 8525-8526 constitutes the refereed proceedings of the 6th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2014, held as part of the 16th International Conference on Human-Computer Interaction, HCI 2014, in Heraklion, Crete, Greece, in June 2014, jointly with 13 other thematically similar conferences. The total of 1476 papers and 220 posters presented at the HCII 2014 conferences were carefully reviewed and selected from 4766 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The total of 82 contributions included in the VAMR proceedings were carefully reviewed and selected for inclusion in this two-volume set. The 39 papers included in this volume are organized in the following topical sections: interaction devices, displays and techniques in VAMR; designing virtual and augmented environments; avatars and virtual characters; developing virtual and augmented environments.

Book Description :

Winner of a 2013 CHOICE Outstanding Academic Title Award The third edition of a groundbreaking reference, The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications raises the bar for handbooks in this field. It is the largest, most complete compilation of HCI theories, principles, advances, case st