Systems Thinking, Critical Realism and Philosophy

A Confluence of Ideas

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• Publisher: Routledge
• Year: 2014
• ISBN:
  9781317684619
• Edition: 1
• Topic: Sozialwissenschaften
• Subtopic: Soziologie

Systems Thinking, Critical Realism and Philosophy: A Confluence of Ideas seeks to re-address the whole question of philosophy and systems thinking for the twenty first century and provide a new work that would be of value to both systems and philosophy. This is a highly opportune time when different fields – critical realism, philosophy of science and systems thinking – are all developing around the same set of concepts and yet not realizing it.

This book will be of interest to the academic systems community worldwide and due to it's interdisciplinary coverage, it will also be of relevance to a wide range of scholars in other disciplines, particularly philosophy but also operational research, information systems, and sociology.

Part I

Foundations

1 Introduction

1.1 Introduction

In 1972, Ervin Laszlo published a seminal book called Introduction to Systems Philosophy: Towards a New Paradigm of Contemporary Thought (Laszlo 1972). This was a book that made a major contribution to systems thinking in the sense that it covered all the main philosophical questions – ontology, epistemology, cognition, ethics, metaphysics and so on. But it was also a book that aimed to make a contribution to philosophy. Coming out of the intellectual ferment of the 1960s, it argued that philosophy also needed systems thinking: that systems provided a new and vibrant synthetic approach to traditional philosophy, especially in contrast to the sterile impoverishment of the Western analytic tradition.

Unfortunately, for many years the call fell on deaf ears – mainstream philosophy, particularly in the UK and the US, carried on in its analytic and positivist form. But outside philosophy, especially within the social sciences, huge debates developed about the nature of science, particularly social science, in terms of a conflict between positivism and interpretivism/constructivism; the development of critically inspired, neo-Marxist positions; and finally post-structuralism and postmodernism, which threatened an end to philosophy almost as Fukuyama (1992) threatened an end to history.

However, writing this some 40 years later, in 2013, I believe that there are real signs that Laszlo’s hope for a systemic philosophy may at last be being realized through developments within, and on the borders of, philosophy itself. The first of these developments, not yet perhaps within the core of philosophy but becoming extremely influential and important within the social sciences, is a philosophical approach known as critical realism. This began to develop in the late 1970s as a reaction against the irrealism and relativism of radical constructivism and, even more so, postmodernism. It is primarily associated with the name of Roy Bhaskar (1978; 1979; 1986; 1989) but many others have made contributions (Archer 1988; Archer 1995; Archer et al. 1998; Keat and Urry 1981; Sayer 1992). Interestingly, however, until quite recently Bhaskar has been only on the margins of mainstream philosophy probably because he has never been part of its institutions, either in terms of an academic position or journal publications. That is now changing with the increasing proliferation of his influence.

Put briefly, critical realism (as first developed) re-asserts the primacy of ontology over epistemology – that is, it asserts the existence of an independent, external world about which we may acquire knowledge, while recognizing the inevitably fallible and contextual nature of that knowledge. It draws on aspects of both positivism and interpretivism (as well as critical theory) but maintains a strongly realist and rationalist orientation in opposition particularly to postmodernism. What is of special interest for us, however, is that critical realism is deeply and fundamentally systemic in character. Although the main texts of critical realism make little reference to the traditional systems literature, the discourse itself, especially in its later ‘dialectical’ manifestation (Bhaskar 1993; Bhaskar 1994), is couched almost exclusively in systems terms.

The second development is within mainstream philosophy, especially within the philosophy of science. For many decades, under the aegis of positivism, the concept of explanation was tied to the idea of universal laws. Following Hume, observation would be made of constant conjunctions of empirical events; from these, universal laws would be hypothesized. Events were then ‘explained’ as deducible instances of the universal laws (the deductive-nomological model). It was not permitted to go beneath the surface of these event regularities and postulate underlying, and possibly unobservable, ‘causes’. However, in more recent years the limitations of this approach have become ever more obvious and an alternative has been generating much interest and support. This approach eschews universal laws in favour of particular ‘mechanisms’ that causally generate the phenomena of interest to the scientist (Gerring 2007; Glennan 1996; Glennan 2002; Machamer 2004; Machamer et al. 2000; Salmon 1998a; Symons 2008). Apart from avoiding many of the problems besetting the deductive-nomological model, especially concerning induction, the idea of mechanisms fits much better with the actual practices of scientists (Bechtel and Abrahamsen 2005) and, as we shall see, with explanations in everyday life.

This explanatory mechanisms view of causation is also highly systemic in nature – mechanism is but another name for system – but, as with critical realism, the literature uses the terms but does not reference the systems thinking discourse explicitly (see especially, for example, papers by Wimsatt 1994; 2007). That said, these philosophical developments have been recognized by some systems theorists, e.g. Pickel (2004; 2007) and Bunge (2004a; 2004b). But there is another connection here, and that is that the concept of causal mechanisms is also central to critical realism although once again the connection does not seem to have been realized or recognized by members of either camp. Thus, we now have two developments in philosophy – critical realism and explanatory mechanisms – which both draw strongly on the systems tradition, and both share a common conceptual framework and thereby have the potential to begin to realize Laszlo’s vision of a systems philosophy.

1.2 Developments in systems thinking

As well as these advances in philosophy, there have also been many developments within systems thinking itself (Mingers and White 2010). I would like to highlight three – the rise of second-order cybernetics and soft systems; the impact of Forrester’s system dynamics; and the emergence of chaos and complexity theory.

1.2.1 Second-order cybernetics and soft systems

Cybernetics (meaning the study of self-governing mechanisms) is a particular branch of systems theory orginating in the 1940s (Heims 1993; Pickering 2002) and developed by scientists such as Norbert Weiner (1948), Ross Ashby (1956), Gregory Bateson (1973b) and Gordon Pask (1976). They were interested particularly in the way that systems could control themselves autonomously through the transmission of information within error-controlled feedback loops. This enabled them to explain the particular nature of living systems and also to explore how the brain and our cognitive processes worked. In studying, for example, the nature of perception¹ it became clear that what we perceive is no passive refection of the external world but rather a very active construction of the human nervous system. Thus we have to recognize that, in principle, the observer is always part of the system being observed.

This insight developed into what became known as second-order cybernet-ics.² First-order cybernetics studies the mechanisms of the external world, while second-order cybernetics studies the process of observation itself. It is the Cybernetics of Cybernetics (Von Foerster 1975) or the study of Observing Systems (Von Foerster 1984) (where ‘Observing’ is to be read as both a noun and a verb), as two of the major works by Heinz von Foerster put it. Much of this work was carried out at the Biological Computer Laboratory (BCL) at the University of Illinois and reached its most developed form in the work of Maturana (1970a) and Maturana and Varela (1975; 1980) on ‘autopoietic’ systems – systems that produce or construct themselves (Mingers 1995b).

Autopoiesis is a fundamental concept that has radical consequences. In terms of physical molecular systems it defnes the nature of life itself. Living systems are bounded networks of processes of biochemical production that produce the very components of which they are constituted. Although they interact with their environment, they are organizationally closed in the sense that they both produce, and are produced by, themselves. The concept of autopoiesis has been influential in a range of disciplines including law (Teubner 1987), sociology (Luhmann 1982b; Mingers 2002), management (Von Krogh and Roos 1994), computing (Winograd and Flores 1987) and literature (McGann 1991). Stemming from, but separate to, autopoiesis, Maturana and particularly Varela developed a theory of mind that was much more phenomenological than computational, conceptualizing cognition as non-representational and embodied (Maturana and Varela 1987; Varela et al. 1991).

At the same time, analogous developments were occurring in another area of systems – applied systems thinking or systems engineering. The systems approach was successfully being used in the design of complex engineering projects such as oil refineries, and methodologies for tackling these problems had emerged (Hall 1962). However, when these methodologies were applied to problems in human organizations they were not found to work well. The issue is that human beings are significantly different from machines and buildings. People, through self-consciousness and language, have the ability to conceptualize themselves and the systems that they are part of – they exist in a world of meaning and signification. This means that we cannot just take for granted, from the outside, the nature of a particular social system or social interaction but have to engage with the participants and become active observers.

This led to the development of an alternative systemic approach to problem-solving in organizations – what became known as ‘soft systems thinking’ as opposed to the ‘hard systems thinking’ of traditional engineering. This represents a similar paradigm shift to second-order cybernetics – problematizing the role of the observer/participant in systems analysis. It was most fully articulated by Checkland (1981; Checkland and Poulter 2006; Checkland and Scholes 1990) in a practical intervention approach called soft systems methodology (SSM) which, he argued, was underpinned by a phenomenological social theory (Husserl 1973, orig. 1913).

Both second-order cybernetics and SSM were mirroring changes that were occurring in social science more generally, as mentioned above. In particular, there was movement away from a positivist view of social science as little different from natural science towards one based on interpretivism and constructivism that argued, to varying degrees, that the social world was intrinsically very different from the material world and required a wholly different, hermeneutic approach. This led to a major dislocation within social science (and systems thinking) between what were seen as fundamentally incommensurable para-digms.³ This in turn paved the way for critical realism to try to overcome or synthesize the fracture.

1.2.2 System dynamics

In general terms, system dynamics simply means the changing behaviour of systems, but in practice it has become associated specifically with the work of Jay Forrester at MIT, who has developed an approach to simulating the behaviour of large complex systems. Forrester was initially interested in the dynamic behaviour of whole industries such as supply chains (Forrester 1961) and of populations of people as in the growth and decay of cities (Forrester 1969). He identified the major flows of people, materials and money and the ways in which these were controlled through feedback loops. He then modelled these using systems of differential equations which were run on a computer to display the dynamic behaviour of the system over time.

The most ambitious model developed was called the ‘world model’ (Forrester 1973) and was actually a model of the whole world economy run to cover a period of 50 years (up to 2020). It involved the interaction of five major factors – population growth, food production, industrialization,...

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• List of figures
• List of tables
• Acknowledgements
• Part I Foundations
• PartII Ontological issues
• PartIII Epistemological issues
• PartIV Practical issues
• Bibliography
• Index