6.3 Where is the complexity and what is it?

When I reflect on my experiences of child-support, I attribute the properties of mess, complex, or hard-to-understand to the situation. So, are mess, complex, and hard-to-understand the same thing? If they are, why is the course called Managing Complexity, rather than, say, Managing Messes? A glib answer is you might not have been attracted to it because of the everyday meaning of mess. Yet another answer is that complexity is a rich term whose everyday meanings have been further enriched by the so-called new sciences of chaos and complexity .

Let me try to explore some of this rich set of meanings by briefly examining the computer world.

I do not regard myself as computer literate and I'm not particularly enthusiastic about computers, so when I encounter a story about which new software or technology will be the new find or dominate the market I experience the situation as complex. I do so because there are many actors in the situation. The issue has a global span. There is apparent or potential conflict, suggesting a range of perspectives on the situation. And the outcomes of these different technological trajectories are likely to have profound economic and social implications. When I use complex in this way – and it has been used in this way most of the time in the unit so far – I am speaking about perceived complexity.

John Casti (1994) said ‘when we speak of something being complex, what we are doing is making use of everyday language to express a feeling or impression that we dignify with the label complex.’ He also argues that the meaning we give to the word complex is dependent on the context. For Casti, the complexity of a situation or a system is not an intrinsic aspect of the situation or ‘system’ taken in isolation but ‘a property of the interaction between two ‘systems’ where one of these is more often than not an observer and/or controller’ (i.e. a person). So, in this explanation, complexity arises in the relationship between the observer and the observed. This is my response to the question in Figure 2. It is also another way to understand what is happening in Figure 3.

Although the language is different, the process I have just described is the same as the one I described earlier for messes. Perceived complexity arises because of our cognitive limitations as well as characteristics of the situation. Our embodied ways of knowing – individuals and the explanations they accept have different traditions and histories – lead to only seeing aspects of a situation never the whole as discussed in Section 6.

There is no viewpoint or perspective that can appreciate the full variety of a situation. It is from the recognition of these limitations that a range of systems approaches have been developed. But are there other ways complexity is currently used? The short answer to this is: Yes, lots.

There are in fact many explanations provided for what complexity is or is not. Someone who went to the trouble of counting in the early 1990s claimed to have found 31 different definitions. Five pages, many more than for any other concept, are devoted to aspects of complexity in the International Encyclopaedia of Systems and Cybernetics. This situation has arisen partly because in the 1990s the field of complexity science has emerged, made popular by the activities of the Santa Fe Institute in the USA; partly because of a series of popular books; and the association of complexity with chaos research (Gleick, 1987). Horgan (1996), a sceptic and critic, describes the academic field as ‘chaoplexity’.

A selected range of perspectives on complexity are provided in Appendix C. This appendix is background material if you want to explore the subject matter in more detail. It is not essential reading and can be extended by a search of the World Wide Web. I outline the context in which complexity science is evolving below.

I suggest you browse Appendix C now before moving on. As you read you may like to add to the spray diagram you began to develop as part of Activity 18.

Click on the 'View document' link below to read 'Some perspectives on complexity'

One of the main driving forces behind the current interest in complexity is the advent of computers and sophisticated non-linear mathematical techniques. Horgan claims these ‘will help modern scientists understand chaotic, complex, emergent phenomena that have resisted analysis by reductionist methods of the past’ (Horgan, 1996, p.192). He uses the following quote to exemplify some of the claims being made:

In an essay entitled ‘The Lure of Complexity’, Steve Talbott (2002) asks whether claims that the study of complex systems, or complexity is a new scientific revolution are, instead, a ‘retrenchment and strengthening of the most serious limitations of traditional science’. He asks if in the drive toward generality and abstraction complexity theorists have lost the features of a qualitative science that refuses to sacrifice the phenomena to abstraction in the first place? For me, as a member of an Open University group that has been teaching and researching systems approaches to managing complexity for the best part of 30 years, many claims made by complexity theorists appear extravagant. (This is taken up in Appendix C.) While I do not wish to deny the potential unleashed by increased computing power and non-linear mathematical techniques, and thus the new questions that are being asked, my preference would be to situate these ideas in a historical context. If this were to happen, and those making these claims were to look into the traditions that give rise to these claims, there would be much to be learned – particularly about the difficulties caused by a multiplicity of meanings embedded in one word as well as a lack of attention to the theory–practice relationship.

Given the wealth of ideas within the notion of complexity, is it possible to be clear what is meant by the terms complex situation and a complex system? Does a historical context illuminate this question? The next section, represented by the second blob on the main spine of Figure 19, explores these issues.