Knowledge Cybernetics: A Metaphor for Post-Normal Science

Introduction

Systems theory has been developed to allow us to model what we see about us so that we can increase our understanding of the problem-solving and decision-making processes that allow us to create improvement. It is not important whether the systems are regarded as a metaphor or as real, since they provide us with templates of ideal relationships and modes of being that can be applied to the complex human activity situations that we see around us. Where complex situations are represented as systems that, over time, represent characteristics of durability, notions of viable systems using cybernetic principles have developed. These enable us to explain how and why such durability continues, and gives us a better understanding about the nature of the complexity. There are very few theoretical formulations for autonomous viable systems, the most well known being that of managerial cybernetics as developed by Stafford Beer (1959, 1985). However, a different approach was developed by Eric Schwarz (1994, 1997), who recognises that viable systems can pass through processes of emergence and evolution towards complexity and autonomy. This occurs through the development of patterns: patterns of self-organisation that accommodate phenomenal change through morphogenesis and new forms of complexity; patterns for long term evolution towards autonomy; and patterns that lead to systems functioning viably through their capacity to create variety. One of the problems with Schwarz’s theory is that it is does not engage with theory that relate to human activity systems, for instance from social or psychological sciences. While it provides templates for creating structures and mechanisms of viability, it has no human related content. Knowledge Cybernetics is a development of Schwarz’s approach to modelling viable systems, drawing on a variety of other works to fill this epistemological gap.

Like the promise of Schwarz’s modelling approach, Knowledge Cybernetics has developed as part of post-normal¹ science. Since its formal inception in 2006, it has had a number of empirical developments. These include, for instance: Guo’s (2006) study of Organisational Patterning that empirically explores the pathology and coherence of a number of State banking corporations in China in relation to their capacity to successfully undertake transformational change; Jirapornkul’s (2009) empirical examination of Thai corporate cultural coherence that derives from a study by Yolles (2007) exploring cultural mapping; Fink’s (2008) exploration of culture shock and culture stretch in multicultural environments, in particular within and processes of hybridisation; Choudhury et al. (2007) have developed a new mathematical area of knowledge processes from ideas asserted within KC; and Achakul is currently in the process of empirically exploring the relationship between knowledge profiling (Yolles, 2006) and motivation.