Knowledge About Knowledge

A Practical Handbook
1. Auflage 2027
ISBN: 978-1-041-32367-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 304 Seiten, Format (B × H): 156 mm x 234 mm

This book is about what knowledge is, what types of knowledge there are, and what the implications are for understanding humans and for understanding AI, clarifying how knowledge differs from the data and information that underpin computing and the Internet.

The authors explain why there are types of knowledge that are difficult or impossible to put into words and show how this semi-tacit and tacit knowledge enables people to deal with the complexities of the real world. They also discuss how this knowledge is different from the explicit verbal knowledge underpinning most forms of AI, and explain the strengths and weaknesses of each type of knowledge. The book describes methods, drawn from a wide range of domains, for finding out about people’s knowledge, with explanations of how to represent knowledge systematically, and how to test it for errors. It also covers efficient ways of transmitting knowledge, and their applications in education and training. It concludes by considering the implications for a knowledge infrastructure revolution that goes beyond the Internet and AI.

Knowledge About Knowledge is a practical handbook for practitioners, academics, and students. It presents a radical new framework built on a broad range of sources and will prove invaluable in fields as diverse as social sciences, management, market research, education, public policy, design, human computer interaction, and artificial intelligence.

Zielgruppe

Academic and Professional Practice & Development

Autoren/Hrsg.

Rugg, Gordon

Gerrard, Sue

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

1. Knowledge: What It Is, and Why It Matters 2. Concepts: Underpinning Elements 3. Elicitation Methods: Getting Knowledge from Human Beings 4.  Representing Knowledge: Showing How Knowledge is Structured 5. Error: What It Is, and What To Do About It 6. Transferring Knowledge: Getting Knowledge Across to Others 7. Where Next? AI, Knowledge Infrastructure, and Beyond 8. Materials

Über Autor(innen)

Gordon Rugg is a researcher with a multidisciplinary background, including archaeology, psychology, and computing. His PhD was in Experimental Psychology, and he is a former Senior Lecturer in Computing at Keele University. His work has featured in Scientific American, Wired and television documentaries.

Sue Gerrard has a first degree in Psychology/Zoology and an MSc in Occupational Psychology. She’s worked as a primary school teacher, an arts festival administrator, and in publishing. Her interests are in cognitive neurology and systems theory, particularly in relation to public policy and special education.