Deep Knowledge as the Core of Sustainable Societies

Deep Knowledge as the Core of Sustainable Societies

Alex Bennet (Mountain Quest Institute, USA) and David Bennet (Mountain Quest Institute, USA)
DOI: 10.4018/978-1-61520-721-3.ch009
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Abstract

Knowledge-based social communities are critical to sustain economic levels and quality environments for community members. The pace of change, rising uncertainty, exponentially increasing complexity and the resulting anxiety (CUCA) have made competition among nations, cities and communities greater and more fierce. As economies look from industry to knowledge for their prime income generator, the role of knowledge and its supporting infrastructure become critical to economic and social health. In this chapter the authors focus on what deep knowledge is and the environment needed to maximize its contribution to the health and growth of societies. They also introduce knowledge attractor network teams as sources of power for community sustainability.
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The Starting Point

Society is taken to be all of the conditions and actions of a social community, both inter-connected and inter-dependent. A social community is a bounded group of people living together in the same locality under the same governing structure, with conditions from which emerge a culture and related behaviors. Further, a social community is a complex system which must adapt quickly to opportunities to develop knowledge-based solutions while at the same time implementing solutions for value creation and maintaining learning efficacy. When these occur the social community is behaving as an intelligent complex adaptive system. This perspective is consistent with the perception forwarded by Garcia (2006) describing cities as connected (Huysman and Wulf, 2005) complex systems of values (Carrillo, 2004), meanings (Tuomi, 2005) and conversations (Dvir, 2006).

Consistent with our previous work, information is considered the result of organization expressed by a non-random pattern or set of patterns (Bennet and Bennet, 2007b, 2008a, 2008b, 2008c, 2008d, 2009a; Stonier, 1990, 1997). Information is represented in the brain by patterns of neuron connections and the strength of those connections. Data (a form of information) is simple patterns, and data and information are both patterns but have no meaning until some organism recognizes and interprets the patterns. As a functional definition grounded in the natural world, knowledge is the capacity (potential or actual) to take effective action in varied and uncertain situations (Bennet, 2005; Bennet and Bennet, 2004, 2007b).

This definition highlights knowledge as a creation of the human mind. It exists in the human brain in the form of stored or expressed neuronal patterns that may be selected, activated, mixed and/or reflected upon through thought. From this mixing process (associative patterning) new patterns are created that may represent understanding, meaning and the capacity to anticipate (to various degrees) the results of potential actions. Through these processes the mind is continuously growing, restructuring and creating increased organization (information) and knowledge (Bennet and Bennet, 2006, 2008b, 2009a).

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