The past few decades have seen an explosion of research on causal reasoning in philosophy, computer science, and statistics, as well as descriptive research in psychology about how people reason about causes. Causation with a Human Face integrates these lines of research and argues for an understanding of how each can inform the other: normative ideas can suggest interesting experiments, while descriptive results can suggest important normative concepts. Woodward's overall framework builds on an interventionist treatment of causation, and discusses proposals about the role of invariant or stable relationships in successful causal reasoning and the notion of proportionality. He argues that these normative ideas are reflected in the causal judgments that people actually make as a descriptive matter.

Embodied conversational agents (ECA) and speech-based human–machine interfaces can together represent more advanced and more natural human–machine interaction. Fusion of both topics is a challenging agenda in research and production spheres. The important goal of human–machine interfaces is to provide content or functionality in the form of a dialog resembling face-to-face conversations. All natural interfaces strive to exploit and use different communication strategies that provide additional meaning to the content, whether they are human–machine interfaces for controlling an application or different ECA-based human–machine interfaces directly simulating face-to-face conversation. Coverbal Synchrony in Human-Machine Interaction presents state-of-the-art concepts of advanced environment-independent multimodal human–machine interfaces that can be used in different contexts, ranging from simple multimodal web-browsers (for example, multimodal content reader) to more complex multimodal human–machine interfaces for ambient intelligent environments (such as supportive environments for elderly and agent-guided household environments). They can also be used in different computing environments—from pervasive computing to desktop environments. Within these concepts, the contributors discuss several communication strategies, used to provide different aspects of human–machine interaction.

There is now a serious discussion taking place about the moment at which human beings will be surpassed and replaced by the machine. On the one hand we are designing machines which embed more and more human intelligence, but at the same time we are in danger of becoming more and more like machines. In these circumstances, we all need to consider: • What can we do? • What should we do? • What are the alternatives of doing it? This book is about the human-centred alternative of designing systems and technologies. This alternative is rooted in the European tradition of human-centredness which emphasises the symbiosis of human capabilities and machine capacity. The human-centred tra dition celebrates the diversity of human skill and ingenuity and provides an alternative to the 'mechanistic' paradigm of 'one best way', the 'sameness of science' and the 'dream of the exact language'. This alternative vision has its origin in the founding European human-centred movements of the 1970s. These include the British movement of Socially Useful Technology, the Scandinavian move ment of Democratic Participation, and the German movement of Humanisation of Work and Technology. The present volume brings together various strands of human-centred systems philosophy which span the conceptual richness and cultural diversity of the human-centred movements. The core ideas of human-centredness include human-machine symbiosis, the tacit dimension of knowl edge, the system as a tool rather than a machine, dialogue, partici pation, social shaping and usability.

Readings in Cognitive Science: A Perspective from Psychology and Artificial Intelligence brings together important studies that fall in the intersection between artificial intelligence and cognitive psychology. This book is composed of six chapters, and begins with the complex anatomy and physiology of the human brain. The next chapters deal with the components of cognitive science, such as the semantic memory, similarity and analogy, and learning. These chapters also consider the application of mental models, which represent the domain-specific knowledge needed to understand a dynamic system or natural physical phenomena. The remaining chapters discuss the concept of reasoning, problem solving, planning, vision, and imagery. This book is of value to psychologists, psychiatrists, neurologists, and researchers who are interested in cognition.

There is a need for integrated thinking about causality, probability and mechanisms in scientific methodology. Causality and probability are long-established central concepts in the sciences, with a corresponding philosophical literature examining their problems. On the other hand, the philosophical literature examining mechanisms is not long-established, and there is no clear idea of how mechanisms relate to causality and probability. But we need some idea if we are to understand causal inference in the sciences: a panoply of disciplines, ranging from epidemiology to biology, from econometrics to physics, routinely make use of probability, statistics, theory and mechanisms to infer causal relationships. These disciplines have developed very different methods, where causality and probability often seem to have different understandings, and where the mechanisms involved often look very different. This variegated situation raises the question of whether the different sciences are really using different concepts, or whether progress in understanding the tools of causal inference in some sciences can lead to progress in other sciences. The book tackles these questions as well as others concerning the use of causality in the sciences.

This book shares Chinese scholars’ philosophical views on artificial intelligence. The discussions range from the foundations of AI—the Turing test and creation of machine intelligence—to recent applications of AI, including decisions in games, natural languages, pattern recognition, prediction in economic contexts, autonomous behaviors, and collaborative intelligence, with the examples of AlphaGo, Microsoft’s Xiao Bing, medical robots, etc. The book’s closing chapter focuses on Chinese machines and explores questions on the cultural background of artificial intelligence. Given its scope, the book offers a valuable resource for all members of the general public who are interested in the future development of artificial intelligence, especially from the perspective of respected Chinese scholars.

Integrated Human-Machine Intelligence: Beyond Artificial Intelligence focuses on deep situational awareness in human-computer integration, covering the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. The book also details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making to provide basic theoretical support for a development strategy in the field of national intelligence. Sections focus on describing a new form of intelligence produced by the interaction of human, machine and environmental systems which will become the next generation of AI. From the perspective of deep situational awareness in human-computer integration, the book studies the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. In addition, it details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making, so as to provide basic theoretical support for a development strategy in the field of national intelligence. - Summarizes the key ideas of computing, perception, cognition and insight into intelligence - Provides intelligent omni-directional multi-angle stereo understanding, including the relevant basic concepts and the realization process of intelligence - Proposes the concept, definition and framework of deep situational awareness, which is conducive to the realization and development of man-machine integrated intelligent systems - Outlines the essence of intelligence, such as facts and values, reason and sensibility, contradiction and balance, etc.

In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. Michael Leyton's arguments about the nature of perception and cognition are fascinating, exciting, and sure to be controversial. In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. He elaborates a system of rules by which the conversion to memory takes place and presents a number of detailed case studies--in perception, linguistics, art, and even political subjugation--that support these rules. Leyton observes that the mind assigns to any shape a causal history explaining how the shape was formed. We cannot help but perceive a deformed can as a dented can. Moreover, by reducing the study of shape to the study of symmetry, he shows that symmetry is crucial to our everyday cognitive processing. Symmetry is the means by which shape is converted into memory. Perception is usually regarded as the recovery of the spatial layout of the environment. Leyton, however, shows that perception is fundamentally the extraction of time from shape. In doing so, he is able to reduce the several areas of computational vision purely to symmetry principles. Examining grammar in linguistics, he argues that a sentence is psychologically represented as a piece of causal history, an archeological relic disinterred by the listener so that the sentence reveals the past. Again through a detailed analysis of art he shows that what the viewer takes to be the experience of a painting is in fact the extraction of time from the shapes of the painting. Finally he highlights crucial aspects of the mind's attempt to recover time in examples of political subjugation.