Theory Of Knowledge: Structures And Processes

Structures and Processes

Mark Burgin

• Publisher: WSPC
• Year: 2016
• ISBN:
  9789814522694
• Topic: Biological Sciences
• Subtopic: Science General
• Index: Biological Sciences

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This book aims to synthesize different directions in knowledge studies into a unified theory of knowledge and knowledge processes. It explicates important relations between knowledge and information. It provides the readers with understanding of the essence and structure of knowledge, explicating operations and process that are based on knowledge and vital for society.

The book also highlights how the theory of knowledge paves the way for more advanced design and utilization of computers and networks.

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Chapter 1

Introduction

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All men by nature desire knowledge.

Aristotle

There is an abundance of different books and papers treating various problems and studying different issues of knowledge (cf., for example, (Aune, 1967; Polanyi, 1974; Cleveland, 1985; Chisholm, 1989; Bloor, 1991; Burgin, 1997; Boisot, 1998; Choo, 1998; Rao, 1998; Pollock and Cruz, 1999; Bernecker and Dretske, 2000; Bean and Green, 2001; Popper, 2002; Goldman, 2004; Dalkir, 2005; Leydesdorff, 2006; Magnani, 2007; Nguen, 2008; Fantl and McGrath, 2009; Zhuge, 2012)). A lot of ideas, models, and several theories have been suggested in this area. The whole area of knowledge related activities consists of three parts:

1.Knowledge studies (theoretical and experimental).

2.Knowledge engineering.

3.Knowledge utilization and management.

The two latter parts belong to knowledge technology — knowledge engineering deals with technology of knowledge production, organization, transformation, management, preservation, capture and acquisition, while knowledge utilization studies how people and organizations use knowledge, developing new techniques and approaches for this purpose.

There are three types of knowledge theories:

1.Philosophical theories comprised by the philosophical discipline called epistemology are interested in three fundamental problems: (1) knowledge definition, i.e., trying to find what knowledge is and how to separate knowledge from beliefs; (2) limits of knowledge acquisition, i.e., what it is possible to know; and (3) ways of knowledge creation and acquisition, i.e., how knowledge is obtained.

2.Mathematical theories include mathematical logic, which provides means for formal knowledge representation and formation; theory of algorithms, which provides means for knowledge transformation and preservation dealing mostly with procedural or operational knowledge (cf., Chapter 6); and mathematical linguistics, which studies informal knowledge representation and formation.

3.Empirical theories are oriented at the practice of knowledge functioning, including theories of many disciplines, such as artificial intelligence, knowledge management, knowledge bases, cognitology, knowledge acquisition, cognitive psychology, cognitive neuroscience, cognitive anthropology, cognitive sociology, education, and the sociology of knowledge.

Experimental exploration of knowledge emerged in ancient times. A brilliant example of such an experimentation is presented in the Plato dialogue Theætetus describing how Sokrates and Theaetetus discuss and investigate the essence and nature of knowledge. For a long time, people used mental experiments for knowledge studies. With the advance of computers, computer experiment has become crucial in AI and knowledge management. Besides, various experiments have been conducted with physical carriers of knowledge. For instance, psychologists, educators and sociologists organized various experiments examining how people acquire, store and disseminate knowledge.

All research in the area of knowledge can be divided into three directions:

•Structural analysis of knowledge strives to understand how knowledge is built and what properties it has.

•Axiological analysis of knowledge aims at explanation of those features that are primary for knowledge as a social and technological phenomenon.

•Functional analysis of knowledge tries to find how knowledge functions, how it is produced and acquired.

Structural analysis of knowledge is the main tool for the system theory of knowledge, knowledge bases, and artificial intelligence (AI).

Axiological analysis of knowledge is the core instrument for the philosophy of knowledge, psychology, and social sciences, including the sociology of knowledge, which is the study of the relationship between human creativity and the social context within which it arises, of the effects knowledge has on individuals, organizations and societies dealing with broad fundamental questions, of the extent and limits of social influences on cognition, and of the social and cultural foundations of knowledge about the world.

Functional analysis of knowledge is the key device for epistemology, knowledge engineering, and cognitology.

1.1. The role of knowledge in the contemporary society

Knowledge is power.

Francis Bacon

To survive and to prosper, people have always needed knowledge. Through the ages, philosophers contemplated problems of knowledge and cognition. The importance of knowledge has grown all the time and now active knowledge assets become crucial. This is true for all levels of society. Simply to function in the contemporary society, any individual needs some basic knowledge. Many organizations feel obliged to run their business based on efficient knowledge management just to keep up. More and more people and organizations are coming to the understanding that the optimal generation, acquisition, and application of knowledge is the key to success.

Although the role of knowledge in the economy is not new, in recent years, knowledge has gained increased importance, both quantitatively and qualitatively, due to the development and utilization of information processing and communication technologies (Foray, 2004). The main roles of knowledge are (Tuomi, 1999): a resource, a product, and a restriction. Indeed, knowledge is clearly the primary resource in the technologically advanced industries, such as the computer, communication and software industries, and other knowledge-intensive industries, such as pharmaceuticals, but it is fast becoming the primary source of wealth in more traditional sectors of the economy as well (Stata, 1989). It is also estimated that knowledge now accounts for approximately three-fourths of the value increase in the manufacturing sector (Stewart, 1997).

At the same time, in contrast to many other resources, people can produce knowledge, which now plays the role of a product. As a result, importance of knowledge production and creation grows very fast. Governments and other organizations invest more and more into knowledge production.

Knowledge has become an intellectual property, attached to a name or group of names and certified by copyright, or some other form of social recognition, e.g., publication or awarding prizes (Granstrand, 1999). As an economical commodity, knowledge and knowledge production are paid for in the research, communication, and educational areas. As the result, knowledge has moved to the social overhead investment of society in the form presented in books, articles, patents or computer programs, written down, printed or recorded at some point for transmission and utilization (Bell, 1973).

Our civilization is based on knowledge and information processing. In contemporary knowledge-driven economy, organizations ultimately gain their value from intellectual and knowledge-based assets rather than material commodities. That is why it is so important to know properties of knowledge and how to work with it. For instance, the principal problem for computer science as well as for computer technology is to process not only data but also knowledge. Knowledge processing and management make problem solving much more efficient and are crucial (if not vital) for big companies and institutions (Ueno, 1987; Osuga, 1989; Dalkir, 2005). To achieve this goal, it is necessary to make a distinction between knowledge and knowledge representation to know regularities of knowledge structure, functioning and representation, and to develop software (and in some cases, hardware) that is based on theses regularities. Many intelligent systems search knowledge spaces, which are explicitly or implicitly predefined by the choice of knowledge representation. In effect, the knowledge representation serves as a strong bias.

People increasingly rely on AI processing systems, which in turn, depend on their software, while information is processed in the search of knowledge. Sophisticated safety-critical software is embedded in a diversity of systems across most industry sectors, ranging from automotive and aerospace to energy and maritime (Kandel and Dick, 2005). This situation once more demonstrates importance of knowledge because software is a form of operational knowledge representation.

At the same time, the National Institute of Standards and Technology (NIST) reported that low quality software costs the U.S. economy almost $60 billion per year (Tassey, 2002; Thibodeau, 2002). Besides, only one quarter of software projects are judged a success (Standish Group). Software defects are accepted as inevitable by both the software industry and the long-suffering user community. In any other engineering discipline, this defect rate would be unacceptable. Moreover, when safety and security are at stake, the extent of current software vulnerability also becomes unsustainable (Croxford and Chapman, 2005). Therefore, validation of operational knowledge in the form of software has become an urgent task for contemporary society.

In our time, importance of knowledge has grown very fast with the advancement of society. Thus, in the 20^th century, with the advent of computers, knowledge has become a concern of science. As a result, now knowledge is studied in such areas as AI, computer science, data and knowledge bases, global networks (e.g., the Internet), information science, knowledge engineering, and knowledge management. Philosophers also continue their studies of knowledge (Chisholm, 1989).

However, knowledge is not an easy concept to understand. As Land et al. (2007) write, knowledge is understood to be a slippery concept, which has many definitions. This is apparent in the many questions philosophers and other thinkers ask themselves about the essence, distinctive characteristics, functions and roles of knowledge in society. These questions can vary from theoretical considerations to practical applications.

For instance, relations between knowledge and information are blurred in contemporary society. Some comprehend knowledge as a kind of information (cf., for example, (Osuga and Saeki, 1990; Davenport, 1997; Probst et al., 1999; Gundry, 2001; Stenmark, 2002; Dalkir, 2005)), while others claim that information is a kind of knowledge (cf., for example, (Kogut and Zander, 1992; Tuomi, 1999)). In addition, there are opinions that information and knowledge are essentially different essences (cf., for example, (Davenport and Prusak, 1998; Lenski, 2004; Burgin, 2010)).

All basic questions about knowledge are related to the way in which we organize and direct the development and application of knowledge on different levels — from individuals through companies and organizations through the whole society. For instance, in many organizations, knowledge management has come to occupy a central place in their functioning. It is a role that makes great demands on an organization’s strategic insight, problem solving ability, and successful development.

As Kalfoglou et al. (2004) write, managing knowledge is a difficult and tricky enterprise. A wide variety of technologies have to be invoked in providing support for knowledge requirements, ranging from the acquisition, modeling, maintenance, transmission, dissemination, retrieval, reuse, and publishing of knowledge. Knowledge is a valuable asset and resource. So, any toolset capable of providing support for operating with knowledge would be valuable as its effects can percolate down to all the application domains structured around the domain representation.

To reflect importance of knowledge, the term knowledge society was coined as a description of the contemporary society by its pivotal characteristic. Some researchers suggest that knowledge society is the next stage of the information society. In essence, every s...

Table of contents

• Cover
• Halftitle
• Series Editors
• Title
• Copyright
• Contents
• Preface
• Acknowledgments
• About the Author
• 1. Introduction
• 2. Knowledge Characteristics and Typology
• 3. Knowledge Evaluation and Validation in the Context of Epistemic Structures
• 4. Knowledge Structure and Functioning: Microlevel or Quantum Theory of Knowledge
• 5. Knowledge Structure and Functioning: Macrolevel or Theory of Average Knowledge
• 6. Knowledge Structure and Functioning: Megalevel or Global Theory of Knowledge
• 7. Knowledge Production, Acquisition, Engineering, and Application
• 8. Knowledge, Data, and Information
• 9. Conclusion
• Appendix
• Bibliography
• Subject Index