Macrocognition Metrics And Scenarios

Macrocognition Metrics and Scenarios: Design and Evaluation for Real-World Teams translates advances by scientific leaders in the relatively new area of macrocognition into a format that will support immediate use by members of the software testing and evaluation community for large-scale systems as well as trainers of real-world teams. Macrocognition is defined as how activity in real-world teams is adapted to the complex demands of a setting with high consequences for failure. The primary distinction between macrocognition and prior research is that the primary unit for measurement is a real-world team coordinating their activity, rather than individuals processing information, the predominant model for cognition for decades. This book provides an overview of the theoretical foundations of macrocognition, describes a set of exciting new macrocognitive metrics, and provides guidance on using the metrics in the context of different approaches to evaluation and measurement of real-world teams.

Cognitive processes in teams have been a valuable arena for team researchers to explore. Team cognition research advances and informs a variety of disciplines, including cognitive and social sciences, engineering, military science, organizational science, human factors, medicine, and communications. There has been a great deal of progress in the team cognition literature, yet the field is still in its early stages of maturity. There is much more to be gained from the field’s insights and there is a need to unite the diverse array of scholarly ideas that permeate the field. This movement will serve to organize the research and ideas that have surfaced in the field, thereby making them more accessible to different disciplines while at the same time, motivating continued progress in the field. This book aims to be a step in this direction and acts as a forum for leading scholars to share their ideas, theories, models, and conceptions about what matters and where more attention is needed in the field of team cognition.

Team collaboration involves many operational tasks such as team decision-making or course of action selection, developing shared understanding, and intelligence analysis. These operational tasks must be performed in many situations, often under severe time pressure, with information and knowledge uncertainty, large amounts of dynamic information and across different team characteristics. Recent research in this area has focused on various aspects of human collaborative decision-making and the underlying cognitive processes while describing those processes at different levels of detail, making it difficult to compare research results. The theoretical construct of ’macrocognition in teams’ was developed to facilitate cognitive research in team collaboration, which will enable a common level of understanding when defining, measuring and discussing the cognitive processes in team collaboration. Macrocognition is defined as both the internalized and externalized mental processes employed by team members in complex, one-of-a-kind, collaborative problem solving. Macrocognition in Teams provides readers with a greater understanding of the macrocognitive processes which support collaborative team activity, showcasing current research, theories, methodologies and tools. It will be of direct relevance to academics, researchers and practitioners interested in group/team interaction, performance, development and training.

This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

The first edition of Handbook of Human Factors and Ergonomics in Health Care and Patient Safety took the medical and ergonomics communities by storm with in-depth coverage of human factors and ergonomics research, concepts, theories, models, methods, and interventions and how they can be applied in health care. Other books focus on particular human

Speed in acquiring the knowledge and skills to perform tasks is crucial. Yet, it still ordinarily takes many years to achieve high proficiency in countless jobs and professions, in government, business, industry, and throughout the private sector. There would be great advantages if regimens of training could be established that could accelerate the achievement of high levels of proficiency. This book discusses the construct of ‘accelerated learning.’ It includes a review of the research literature on learning acquisition and retention, focus on establishing what works, and why. This includes several demonstrations of accelerated learning, with specific ideas, plans and roadmaps for doing so. The impetus for the book was a tasking from the Defense Science and Technology Advisory Group, which is the top level Science and Technology policy-making panel in the Department of Defense. However, the book uses both military and non-military exemplar case studies. It is likely that methods for acceleration will leverage technologies and capabilities including virtual training, cross-training, training across strategic and tactical levels, and training for resilience and adaptivity. This volume provides a wealth of information and guidance for those interested in the concept or phenomenon of "accelerating learning"— in education, training, psychology, academia in general, government, military, or industry.

Fully up-to-date coverage of human factorsengineering—plus online access to interactive demonstrationsand exercises Engineering accomplishments can be as spectacular as a moonlanding or as mundane as an uneventful drive to the local grocerystore. Their failures can be as devastating as a plane crash or amassive oil spill. Over the past decade, psychologists andengineers have made great strides in understanding how humansinteract with complex engineered systems—humanengineering. Introduction to Humans in Engineered Systems provideshistorical context for the discipline and an overview of some ofthe real-world settings in which human engineering has beensuccessfully applied, including aviation, medicine, computerscience, and ground transportation. It presents findings on thenature and variety of human-engineering environments, humancapabilities and limitations, and how these factors influencesystem performance. Important features include: Contents organized around the interaction of the human operatorwith the larger environment to guide the analysis of real-worldsituations A web-based archive of interactive demonstrations, exercises,and links to additional readings and tools applicable to a range ofapplication domains Web content customizable for focus on particular areas of studyor research