Information Laws

Information Laws

Andrew Targowski (Haworth College of Business, USA)
Copyright: © 2009 |Pages: 12
DOI: 10.4018/978-1-60566-004-2.ch012
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The purpose of this chapter is to define information laws which control the development of the global and universal civilizations as well as individual autonomous civilizations. Mankind progresses in proportion to its wisdom, which has roots in practice, acquired skills, available data, and information, concepts and knowledge. To be wise, humankind needs to be both informed and knowledgeable, otherwise it will not survive its own failures. Progress in knowledge was painfully slow as long as the spatial memory was transmitted only by oral tradition. With the inventions of writing and books, the process of knowledge discovery and dissemination was accelerated. Today, computers and their networks speed up that process far beyond our imagination. In the 21st century, the Information Wave significantly controls the Agricultural and Industrial Waves through millions of computers. IT supports decision-making based on knowledgeoriented systems such as “data mining” that, for example, discover knowledge about customers and organization dynamics to achieve competitive advantage. Information and knowledge have become the strategic resource that engineering science was in the Industrial Wave. However, the discovery of human cognition potential must be guided by knowledge science, which is just emerging. One of the signs of any science is its set of data, universal rules, laws, and systems of rules and laws. Hence, this chapter offers the first attempt to develop main laws of information that should increase our awareness about the Information Wave, the new stage of civilization dynamics that is taking place at the beginning of the third millennium. The chapter also provides the framework for the analysis of human capital from an information perspective. These considerations reflect a still emerging approach which I call macro-information ecology.
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Macro-Information Ecology

Macro-information ecology is based on the premise that the growth rate of discovery of new information (knowledge) is the key determinant of macroeconomic activities in the service-industrial-global economy (so-called the “new economy”). This new emerging school of macroeconomics may be called knowledgism.

Macro-information ecology is the study of information (cognition) as a whole. It is concerned with aggregates across nations and markets. Macro-information ecology studies the behaviors of societies and economies (nationally and globally) measuring:

  • the value of human capital

  • the potential efficiency of human capital

  • knowledge output

  • Economic output driven by knowledge in a given period, and so forth

It also studies measures derived from many individual nations:

  • markets such as the price of human capital

  • the total structure of employed workers by such categories as production workers in-person service workers, and information workers

Another interesting facet of this emerging discipline is the qualitative analysis of civilization paradigm shifts and the application of civilization tools as a result of increased cognition about us.

To control national output with the development of a global economy, knowledgists stress the need to control the growth of new knowledge discovery. Given the long and variable lags of knowledge and information policies behind events and the difficulty in forecasting future economic events (such as recessions), knowledgists question the ability of industrial or service-oriented macroeconomics to implement even “correct” economic policy.

The knowledge approach suggests that direct government intervention within the economic system should be guided by the “predicted history of the futures.” Knowledge policy is the key to this intervention. In this sense, knowledge policy is closer in economic theory to the Keynesian interventionists than to “conservative” monetarists.

The supply and demand of information (knowledge) is the most basic subject of information ecology (IE). However, before presenting this model, we must examine the stages of development of the information reservoir. Figure 1 illustrates this process.

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