Knowledge Cybernetics as part of Post-Normal Science

Maurice Yolles ,

Cybernetics Society Conference, King College, July 2008

Abstract

Knowledge cybernetics is part of complex systems, and a post-normal science approach principally concerned with the development of agents like autonomous social collectives that survive throughknowledge and knowledge processes. Deriving from epistemological antecedents created by Stafford Beer and explored through notions of ontology by Eric Schwarz, a new form of knowledge management arises that is connected with the notions of Marshall and her new radical classifications for knowledge. These ideas can be closely associated with concepts of lifeworld and the ideas of communicative action by Habermas, andleads to a useful knowledge cybernetic framework. This has the capacity to relate to and develop a variety of what might be thought of as otherwise disparate theories that can ultimately be expressed in terms of knowledge.

1. 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), whorecognises that viable systems can pass through processes of emergence and evolution of 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.

Knowledge Cybernetics began as a theoretical development in post-normal[1] science, and that was inspired by the conceptual construction of Schwarz (1994, 1997). Since its formal inception in 2006, it has had a number of empirical developments. These include, for instance: the Guo (2006) study of Organisational Patterning that empirically explores the pathology and coherence of a number of corporations in China; deriving from a study by Yolles (2007) that explores cultural mapping, Jirapornkul (2009) has empirically examined Thai corporate cultural coherence; Fink (2008) is also examining culture shock and stretch in multicultural environments; finally, Chaiporn Achakul is currently empirically exploring the relationship between knowledge profiling (Yolles, 2006) and motivation.

Knowledge cybernetics is a paradigm of complex systems. Complexity has been explored, for instance, by Nicolis and Prigogine (1989) and Cohen and Stewart (1994). It is also implicit to the theory of autonomous viable systems as explored by Beer (1959, 1985) and by Schwarz (1997). Just as the system is normally seen as a metaphor, knowledge cybernetics is metaphorical in that it:

  • explores knowledge formation and its relationship to information;
  • provides a critical view of individual and social knowledge, and their processes of communication and associated meanings,
  • seeks to create an understanding of the relationship between people and their social communities for the improvement of social collective viability, and an appreciation of the role of knowledge in this.

In a coherent autonomous human activity system knowledge occurs in structured patterns. This provides the structure that enables the system to recognise its existence, maintain itself, and change, and its manifestations constitute systemic content. While the notion of system (attributed to Bertalanffy, 1951 through his notion of the “general system”) is used to explain behavioural phenomena, its cybernetic exploration derives from the work of Rosenblueth, Wiener and Bigelow (1943) who were interested in its teleogical properties that relate to its identity, degree of autonomy and coherence.

Autonomous system theory was a particular interest of Beer (1979). He recognised the practical utility of the idea of the metasystem explored by Whitehead and Russell (1910) in their logical study of formal systems, and used it as way of exploring the viability of complex social systems (figure 1) through processes of self-regulation, self-organisation and control. A consequence has been the emergence of a new paradigm with its own new frame of reference that transforms the way in which organisations can be examined. It takes us away from the simple input-output model of a system, in which the system components behave such a way that they transform the inputs into the outputs, to a model that explains how such behaviour is controlled.

Beer’s paradigm effectively has two dimensions: one was ontological and the other epistemological (figure 2), though his explicit interest only ever lay in the latter. While epistemological approaches enable the nature of knowledge to be explored, ontological[2] approaches define types of being in a way that enable complex cybernetic relationships to be expressed simply. This simplicity occurs because ontology (Poli, 2001 and 2005) can be represented as geometry. To explain this, consider that a function of ontology is to define a frame of reference that topologically distinguishes between arbitrarily defined distinct modes of being through the creation of a referencing system. Within a social context, this system then provides fo$$$r the creation of a social geometry through which component properties and relationships can be expressed and analytically explored. In Beer’s work, the ontology was implicit (Yolles, 2004) in that it analytically distinguishes between two types of behaviour, metasystemic that is connected with worldview and knowledge, and systemic that is to do with phenomenal energetic behaviour. The exploration of epistemological elements, however, was explicit, and resulted in Beer’s Viable System Model (VSM) that created an epistemological approach capable of analysing and diagnosing complex problem situations. An outline of VSM is provided in figure 3, though the more usual VSM map is provided in Figure 4 (from Yolles, 1999).

Figure 1: Nature of Complex Viable Systems

Figure 2: Distinguishing between Ontology and Epistemology

Figure 3: Ontological Differentiations in the Viable System Model
based on work of Stafford Beer

Figure 4: The relationship between the elements of VSM

S3 and S4 enable requisite variety which is generated by S5, while S2 recommends regulation

This model is defined in terms of distinct systemic functions that can be summarised as follows: operations may be constituted as a single or multiple system; coordinationcan provide effective control, and has interests in a limited synergy across divisions of an organisation, trying to harmonise the culture and structure of the enterprise whilst also trying to reduce chaos and introduce order while trying to amplify the capability for control for the induction of self-regulatory operational behaviour. Integration (and control) is concerned with effective regulation of the dynamic internal to the organisation; futures is important to the identity of the organisation, and involves issues of development and strategic planning; policy is concerned with the establishment and maintenance of a coherent context for the processes of the organisation, and relates to what the organisation sets out to do and defines.

Making the implicit explicit enhances the capacity to develop the analytical exploration of social situations, and if adequately established, can offer access to social geometry that is able to richly explore social situations in a way that often otherwise requires dense narrative. One such ontological construction has been proposed by Eric Schwarz (see Schwarz, 1994, 1997, 2001; Yolles, 1999). Schwarz’s approach explains how persistent viable systems are able to maintain themselves, change and die. The approach was developed, according to Schwarz (2005), as a general theory of viable autonomous systems, and its creation was stimulated during the preparation for a course of lectures on the “Introduction to Systems Thinking” at the University of Neuchâtel, in particular by Prigogine's dissipative structures theory, Erich Jantsch's (1980) Self-Organizing Universe, Maturana and Varela's (1979) autopoietic approach and of course cybernetical concepts. Schwarz tried to extract the basic common features of these different approaches and produce a unique metamodel that constitutes a transdisciplinary epistemo-ontological framework, from which other phenomenological models could be constructed through a combination of logical deduction and intuition. The metamodel itself has some internal dynamics, coherence and self-referential character, and it also had resonances with philosophia perennis. While many (phenomenological) models show that the evolution of systems go through the successive stages of emergence, growth, stability, and decay, the interest of this metamodel is its global coherence and its questioning of the foundations of the usual materialistic, dualistic, realistic, reductionist, mechanistic approach that, for Schwarz, provides the basis for a language for a new holistic paradigm.

In this paper we explain how this metamodel can be established as a social geometry, the epistemological content of which entertains knowledge cybernetics, the structures and processes associated with knowledge that enable identity, degree of autonomy and coherence to be explored. Yolles (2005) examines the nature of autonomy, and establishes a set of principles that elaborate on Schwarz’s paradigm within the social context.

The form of the metamodel is defined by its ontology, while its content is epistemological. This content derives from a variety of works that include contributions from Beer’s cybernetic approach, Habermas’s (1971), Knowledge Constitutive Interests, Marshall’s (1975) knowledge schema that links with the ideas on generic forms of knowledge by Schutz and Luckmann (1974). The general model is referred to as Social Viable Systems (SVS), and its epistemological nature as knowledge cybernetics. In developing SVS as a social metamodel, it also needed to take into consideration communications processes. In doing this it has taken heed of the ideas of Beer (1979), ideas on lifeword by Schutz and Luckmann (1974), by Habermas (1987) in his theory of Communicative Action, with some incidental reference to Luhmann’s (1986) social communication. Overall, the SVS metamodel is intended as a way of creating social geometries that can explore and explain complex situations.

2. Social Viable Systems theory

The basis of SVS, the ontology of which is shown in figure 5, was developed from Yolles (1999) , and with its current formulation is available in Yolles (2005). The three domains constitute distinct modes of being: measurable energetic phenomenal behaviour, information rich images or systems of thought, and knowledge related existence that is expressed through patterns of meaning. The term existential is taken directly from Schwarz’s usage; the term noumenal is taken from the positivist work of Kant (e.g., see Weed, 2002), and though we also refer to the sphere of mind and thinking as did he, our approach is constructivist; and the term phenomenal has been adopted because of intended consistency with the principles of phenomenology as founded by Husserl (1950) (deriving from his 1882 doctoral thesis; also see Osborn, 1934) and after him Heidegger (1927).

Figure 5: Social Viable Systems (SVS) model based on Schwarzian model of Autonomous Viable Systems, where autonomy is a function of both autogenesis and autopoiesis

The three domains of SVS are analytically distinct classifications of being, and they each properties that are manifestations of knowledge. The phenomenal domain has social interests adapted from Habermas’s (1971) in a way explained in Yolles and Guo (2003). The other domain properties arise as an extension of this, are listed in table 1, and draw on both systemic and cybernetic notions. There is a connection here to Schutz and Luckmann (1974) in that the epistemological content of each of the 3 domains can be defined in terms of relevancies. The existential domain has thematic relevance that determines the constituents of an experience; the noumenal or virtual domain has interpretative relevance that creates direction through the selection of relevant aspects of a stock of knowledge to formulate ideate structures or a system of thought; and the phenomenal domain is associated with motivational relevance that causes a local conclusion through action. The notions of conscious, subconscious and unconscious derive from Freudian psychology, are connected to the ideas of Wollheim’s (1999), and also related to the ideas of organisational psychology as promoted, for instance, by Kets de Vries (1991).

Sociality
Cognitive
Properties / Kinematics
(through social motion) / Direction
(determining social trajectory) / Possibilities/potential
(through variety development)
Cognitive interests / Technical / Practical / Critical Deconstraining
Phenomenal
(conscious)
domain
Activities
Energy / Work. This enables people to achieve goals and generate material well-being. It involves technical ability to undertake action in the environment, and the ability to make prediction and establish control. / Interaction. This requires that people as individuals and groups in a social system to gain and develop the possibilities of an understanding of each others' subjective views. It is consistent with a practical interest in mutual understanding that can address disagreements, which can be a threat to the social form of life. / Degree of emancipation. For organisational viability, the realising of individual potential is most effective when people: (i) liberate themselves from the constraints imposed by power structures (ii) learn through precipitation in social and political processes to control their own destinies.
Cognitive purposes / Cybernetical / Rational/Appreciative / Ideological/Moral
Noumenal
or virtual
(subconscious) domain
Organising
Information / Intention. Within the governance of social communities this occurs through the creation and pursuit of goals and aims that may change over time, and enables people through control and communications processes to redirect their futures. / Formative organising. Within governance enables missions, goals, and aims to be defined and approached through planning. It may involve logical, and/or relational abilities to organise thought and action and thus to define sets of possible systematic, systemic and behaviour possibilities. It can also involve the (appreciative) use of tacit standards by which experience can be ordered and valued, and may involve reflection. / Manner of thinking. Within governance of social communities an intellectual framework occurs through which policy makers observe and interpret reality. This has an aesthetical or politically correct ethical positioning. It provides an image of the future that enables action through politically correct strategic policy. It gives a politically correct view of stages of historical development, in respect of interaction with the external environment.
Cognitive influences / Socio / Base / Political
creating cultural disposition
Exustential
(unconscious)
domain
Worldviews
Knowledge / Formation. Enables individuals/groups in a social community to be influenced by knowledge that relates to its social environment. It affects social structures and processes that define the social forms that are related to community intentions and behaviours. / Belief. Influences occur from knowledge that derives from the cognitive organisation (the set of beliefs, attitudes, values) of other worldviews. It ultimately determines how those in social communities interact, and it influences their understanding of formative organising. Its consequences impact of the formation of social norms. / Freedom. Influences occur from knowledge that affect social community polity, determined in part, by how participants think about the constraints on group and individual freedoms; and in connection with this, to organise and behave. It ultimately has impact on unitary and plural ideology and morality, and the degree of organisational emancipation.

Table 1: Domain cognitive properties that determine Social Orientation (sociality)
developed from Habermas’s Knowledge Constitutive Interests

The nature of autopoiesis and autogenesis is or particular interest in SVS. Here autopoiesis is constituted simply as a network of processes that enables noumenal activity to become manifested phenomenally, conditioned by autogenesis – a network of principles that create a second order form of autopoiesis that guides autopoietic processes. After Schwaninger (2001), autopoiesis may be thought in terms of processes of operative management, and autogenesis as process of strategic management.

In another investigation, Marshall (1995) was interested in exploring the way military personal made decisions in the field. To progress her work she abandoned the traditional way of defining knowledge as procedural and declarative (Davis and Olson, 1984), and instead defined a new set of classifications the essence of which is provided in table 2.

Interestingly, Marshall’s notions were not entirely new. While she was not apparently aware of it, Schutz and Luckmann (1974) had identified three types of generic knowledge: thematic, interpretive and motivational that have already been referred to the domains of SVS, and which provides an entry for Marshall’s knowledge types (Figure 6). The specification of Schutz and Luckmann’s generic knowledge types allows us to reduce Marshall’s 4 types of knowledge to 3, conveniently connecting her notions with SVS (Figure 7). It may be noted that the idea that planning knowledge is embedded in the existential domain is also consistent with Beer’s VSM, in which system 4 is planning (shown later in figure 12).

Knowledge type and use / Nature of Knowledge
According to Marshall et al / Nature of Knowledge
According to Paris et al
Identification
Used in the creation of pattern recognition / In complex situations people respond to a large number of events that sometimes unfold rapidly and often unexpectedly. Time constraints may be tight, and there may be a need to identify almost instantaneously which aspects of the situation demand their immediate attention and which do not. Identification knowledge relates to situation awareness. Essentially, this schema is needed as an overall control mechanism and is used repeatedly in tactical settings. It is the knowledge required to recognise the nature of situations. / Effective identification involves recognising a situation by focusing on the particular configuration of features that are present in it. Such configurations, which tap into an individual’s knowledge, allow operators to identify specific tracks of possible action, project future actions of those tracks, and ultimately assign threat potential to them. Effective identification further requires the timely and accurate reporting of the ongoing state of those features to fellow team members, within and beyond ownership.
Planning
Used to connect a goal state to a set of possible actions to realize that state. / A full response by an individual in a tactical setting often requires that a series of response actions be developed and carried through. This activity requires a third type of knowledge, namely the ability to create, organize, and prioritise plans for each contact of interest on the display. This knowledge involves additional specific details about how events may unfold in real time and about steps needed to ready various response mechanisms. It involves the application of rules and strategies to the current situation, and enables us to connect a goal state to a set of possible actions to realize that state. / Effective planning arises from:
(1) a solid body of experience/ knowledge which addresses the appropriateness and optimal timing of specific responses to potential threats, and
(2) rules of engagement that define the current situational constraints and provide the specific framework within which that knowledge must be implemented.
Elaboration
Used in the creation a mental model about the current problem situation / After the initial identification has been made, individuals need to elaborate their understanding and interpretation of a target. To do so, they call on their already-existing knowledge of similar situations and use them to develop a better understanding of the current situation. Some of this elaboration is similar to the critical thinking skills outlined by Cohen, Freeman, & Thompson (1997), and some is analogous to case-based reasoning (Kolodner, 1993). It is the knowledge needed to determine what tasks have high priority. / Elaboration taps the background store of information that summarizes what has been learned previously about similar situations. It enables operators to create mental models of particular situations. Effective elaboration involves applying previous knowledge (e.g., of mission profiles) to the current situation, such that the most reliable and acceptable hypothesis may be formulated with regard to the intent of a specific track.
Execution
Used to guide implementation & determines who should perform required actions. / Centres on how to carry out the plans that have been developed. This knowledge includes knowing who should be informed about current plans, who has responsibility for various operations and activities required in the plans, and when to issue the appropriate commands. / Effective execution requires sufficient follow-through by all team members to accomplish stated objectives.

Table 2: Types of knowledge in Marshall's (1995) Knowledge Schema, related to the view of Paris et al (1998)