Understanding Computers and Cognition presents an important and controversial new approach to understanding what computers do and how their functioning is related to human language, thought, and action. While it is a book about computers, Understanding Computers and Cognition goes beyond the specific issues of what computers can or can't do. It is a broad-ranging discussion exploring the background of understanding in which the discourse about computers and technology takes place. Understanding Computers and Cognition is written for a wide audience, not just those professionals involved in computer design or artificial intelligence. It represents an important contribution to the ongoing discussion about what it means to be a machine, and what it means to be human. Book jacket.

In these ground-breaking essays, Heinz von Foerster discusses some of the fundamental principles that govern how we know the world and how we process the information from which we derive that knowledge. The author was one of the founders of the science of cybernetics.

Highlighting and illustrating several important and interesting theoretical trends that have emerged in the continuing development of instructional technology, this book's organizational framework is based on the notion of two opposing camps. One evolves out of the intelligent tutoring movement, which employs artificial-intelligence technologies in the service of student modeling and precision diagnosis, and the other emerges from a constructivist/developmental perspective that promotes exploration and social interaction, but tends to reject the methods and goals of the student modelers. While the notion of opposing camps tends to create an artificial rift between groups of researchers, it represents a conceptual distinction that is inherently more interesting and informative than the relatively meaningless divide often drawn between "intelligent" and "unintelligent" instructional systems. An evident trend is that researchers in both "camps" view their computer learning environments as "cognitive tools" that can enhance learning, performance, and understanding. Cognitive tools are objects provided by the instructional environment that allow students to incorporate new auxiliary methods or symbols into their social problem solving which otherwise would be unavailable. A final section of the book represents researchers who are assimilating and accommodating the wisdom and creativity of their neighbors from both camps, perhaps forming the look of technology for the future. When the idea of model tracing in a computer-based environment is combined with appreciation for creative mind-extension cognitive tools and for how a community of learners can facilitate learning, a camp is created where AI technologists and social constructivist learning theorists can feel equally at home.

A proposal that human social cognition would not have evolved without mechanisms and practices that shape minds in ways that make them easier to interpret. In this novel account of distinctively human social cognition, Tadeusz Zawidzki argues that the key distinction between human and nonhuman social cognition consists in our complex, diverse, and flexible capacities to shape each other's minds in ways that make them easier to interpret. Zawidzki proposes that such "mindshaping"—which takes the form of capacities and practices such as sophisticated imitation, pedagogy, conformity to norms, and narrative self-constitution—is the most important component of human social cognition. Without it, he argues, none of the other components of what he terms the "human sociocognitive syndrome," including sophisticated language, cooperation, and sophisticated "mindreading," would be possible. Challenging the dominant view that sophisticated mindreading—especially propositional attitude attribution—is the key evolutionary innovation behind distinctively human social cognition, Zawidzki contends that the capacity to attribute such mental states depends on the evolution of mindshaping practices. Propositional attitude attribution, he argues, is likely to be unreliable unless most of us are shaped to have similar kinds of propositional attitudes in similar circumstances. Motivations to mindshape, selected to make sophisticated cooperation possible, combine with low-level mindreading abilities that we share with nonhuman species to make it easier for humans to interpret and anticipate each other's behavior. Eventually, this led, in human prehistory, to the capacity to attribute full-blown propositional attitudes accurately—a capacity that is parasitic, in phylogeny and today, on prior capacities to shape minds. Bringing together findings from developmental psychology, comparative psychology, evolutionary psychology, and philosophy of psychology, Zawidzki offers a strikingly original framework for understanding human social cognition.

We effortlessly recognize all sorts of events--from simple events like people walking to complex events like leaves blowing in the wind. We can also remember and describe these events, and in general, react appropriately to them, for example, in avoiding an approaching object. Our phenomenal ease interacting with events belies the complexity of the underlying processes we use to deal with them. Driven by an interest in these complex processes, research on event perception has been growing rapidly. Events are the basis of all experience, so understanding how humans perceive, represent, and act on them will have a significant impact on many areas of psychology. Unfortunately, much of the research on event perception--in visual perception, motor control, linguistics, and computer science--has progressed without much interaction. This volume is the first to bring together computational, neurological, and psychological research on how humans detect, classify, remember, and act on events. The book will provide professional and student researchers with a comprehensive collection of the latest research in these diverse fields.

Computers and Thought showcases the work of the scientists who not only defined the field of Artificial Intelligence, but who are responsible for having developed it into what it is today. Originally published in 1963, this collection includes twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers.