Open Thinkering


Tag: language

TB872: Making choices about situations and systems

Note: this is a post reflecting on one of the modules of my MSc in Systems Thinking in Practice. You can see all of the related posts in this category.

This image illustrates the concept of setting boundaries in systems thinking. It portrays an individual making choices and connections within a vast, intricate network, emphasizing the depth and complexity of systems interactions. The network is multi-layered and complex, symbolizing the careful consideration required in defining system boundaries.

My last post was about the difference between situations and systems, and about moving from having a systemic sensibility, through to having a form of systems literacy, and then on to systems thinking in practice (STiP) capability. It was a reflection on Systems Practice: How to Act by Ray Ison.

This post picks up where that one left off by discussing Chapter 3. One of the first things to note is that STiP practitioners need to decide a boundary for the system that they create from any given situation. Ison points out that we need to be careful when doing so, and note that:

  1. We are always in situations, never outside them
  2. We have choices that can be made about how we see and relate to situations
  3. There are implications which follow from the choices we make

Ison, R. (2017) Systems practice: how to act. London: Springer. p.39. Available at:

The reading in this chapter comes from Dick Morris, a former Open University (OU) colleague of Ison’s. I want to pull out a quotation from it that I thought was interesting:

When thinking in terms of systems, we have at least partially to move away from our usual manner of thinking, which has been heavily influenced by the generally science-based model that has characterised European thought, particularly during the last century. Such thinking in science and its partner, technology, has produced enormous strides in our material well-being, but we also recognised that it has also brought some problems. A key feature of classical science has been to work under carefully controlled experimental conditions, looking in detail at one factor at a time. The success of this approach has unintentionally encouraged a widespread popular belief that we can isolate a single cause for any observed event.

Morris (2005), cited in Ison, R. ibid. p. 40

The examples that Morris gives range from blaming food additives for children’s poor behaviour through to fewer police ‘on the beat’ leading to increased crime rates. I thought this was worth pausing to discuss, especially when coupled with the quotation from John Shotter (1993) that Ison included in a footnote in Chapter 2, and which I also quoted in my last post:

Why do we fell that our language works primarily by us using it accurately to represent and refer to things and states of affairs in the circumstances surrounding us, rather than by using it to influence each other’s and our own behaviour?

Morris (2005), cited in Ison, R. ibid. p. 25

I haven’t time to explore this fully here, so I will just park (for now) the thought that conspiracy theories are a non-scientific way of thinking about the world that nevertheless attempt to ‘explain the phenomena’. By reconceptualising language as “a system to influence others” rather than “a system to accurate describe the world” might we be able to do a better job of working together to improve our world?

As we discovered in Chapter 2, Ison is not a fan of definitions but there is a definition of a ‘system’ in the reading within Chapter 3. Dick Morris (Ison, ibid. p.41) uses one from the OU’s Technology Faculty, which defines a system as:

  • A collection of entities
  • That are seen by someone
  • As interacting together
  • To do something

This means that a system is not an indivisible entity, but that it has parts or components and these components interact with one another to cause change. The difficult thing is drawing a boundary and deciding which components to include in a system. For example, is a farm a system to produce food? to produce a profit? to maintain a particular landscape?

We can’t solve all of the problems of the world in one go, and indeed setting a boundary so that the system is too large is self-defeating. As Morris says, “Choosing an inappropriate boundary, and with it, inappropriate criteria, can be misleading” (Ison, ibid. p.43). He gives the example of using animals for food production which, as a vegetarian, I don’t endorse and so won’t repeat here. I don’t think that murdering animals because it might be in some way “sustainable” can be justified.

One thing that is worth quoting from Morris is why STiP practitioners tend to use diagrams (my emphasis):

In order to share our visions, and to debate futures, we need to have some way of explaining what we regard as the system of interest and its key features. We need to have some model of the system which is necessarily simpler than the whole, complex situation itself, but shows what we think are the important aspects. It may be possible to do this in words, but often it is much quicker and more powerful to use some sort of diagram. Words have to flow in a sequential manner to make sense, and one of the features of most systems is that the interactions between entities are often recursive, that is they form loops, where A may affect B, which in turn affects C, but C can also affect A. In such a situation, a diagram can literally be ‘worth a thousand words’!

Morris (2005), cited in Ison, R. ibid. p.43

Two examples of diagrammatic forms that can be useful in this regard are given by Morris as Systems Maps (the first example below) and Multiple-cause (or ‘Causal Loop’) diagrams (the second example):

Two examples of useful diagrams for STiP practitioners: one Systems Map and one Multiple Cause (or 'Causal Loop')

Morris (2005), cited in Ison, R. ibid. p.44

As we can see, both diagrams tell us much more about a given system, and more quickly, than a page of text could do.

At this point, I want to share a brief anecdote as it will help me reflect on the difference between a situation and a system, and the importance of knowing where to place a boundary. I’m a member of the Green Party, although not currently a very active one. I emailed the Green’s candidate in the upcoming North East Mayoral elections recently asking them to come in behind Jamie Driscoll, who is running as an independent after being kicked out of the Labour party for being too closely aligned with Jeremy Corbyn.

I’m not going to share the details of my emails with the Green candidate, especially as they asked me not to, but suffice to say that they seemed much more interested in the technical details of candidacy and party politics than me. The emails to party members reflect this. While this is perhaps understandable, if we look at language as a way of influencing other people’s behaviour, they’re not doing a particularly good job.

It’s not quite the language of systems, and perhaps I’m reading too much into it, but the latest post by Jamie Driscoll on his website talks of there being “no template” for what he’s doing and that “nobody knows” what the future holds:

There’s no template for running a successful combined authority. Devolution is just a vehicle, you need the right driver. My goal was always to build a zero-carbon, zero-poverty, North East, with thriving modern industries and richer communities. We’re making real progress. And we’ve done this without borrowing money or putting a penny on your council tax bills. People of ordinary means already pay enough tax.


So what does the future hold? The truth is nobody knows. So, instead of making predictions I’ll make a resolution. To finish the job I started in 2019.

It’s time to finish the job I started…. (26 December 2023) Jamie Driscoll, North of Tyne Mayor. Available at: (Accessed: 30 December 2023).

I guess my point is that to make change we have to embrace uncertainty, and act based on values.

As a segue back to Chapter 3, I’ll just note that one of Driscoll’s key pledges is around a “fully integrated public transport [system] under public control” (Driscoll, 2023). Here, the word ‘system’, as is relatively normal in everyday usage, is a thing as opposed to a process.

A constraint to thinking about ‘system’ as an entity and a process is caused by the word ‘system’ being a noun — a noun implies something you can see, touch or discover, but in contemporary systems practice more attention can be paid to the process of ‘formulating’ a ‘system’ as part of an inquiry process in particular situations.

Ison, R. (2017). Ibid. p.47.

In other words, a system is an epistemological device used to engage with a situation, rather than having any ontological status. As he goes on to say (Ison, ibid. p.54) “contemporary systems practice is concerned with overcoming the limitations of the word ‘system’.” Hence, I suppose, Ison’s use of terms like ‘system of interest’ or ‘a system to x’.

Top image: DALL-E 3

Creative Ambiguity and Digital Literacy

I’m (re-)writing my first journal article at the moment, ostensibly in order to make my viva easier when I’ve finished my Ed.D. thesis. It’s easier to prove an ‘original contribution to knowledge’ when some of it has been published in a peer-reviewed journal! You’ll understand, therefore, why this post, which constitutes the first part of the article, is Copyright (All Rights Reserved).

All human communication is predicated upon vocabularies. These can be physical in the form of sign language but, more usually, are oral in nature. Languages, therefore, are codified ways in which a community communicates. However, such languages are not static but evolve over time to meet both changing environmental needs and to explain and deal with the mediation and interaction provided by tools.

As Wittgenstein argued, a private language is impossible as the very purpose of it is communication with others. Those with whom one is communicating must have the ‘key to open the ‘box’. Yet if all language is essentially public in nature it begs the question as to how popular terms can be used in such a variety and multiplicity of ways. Terms, phrases and ways of speaking have overlapping lifecycles used by various communities at particular times. A way of describing a concept often enters a community as a new and exciting way of looking at a problem, perhaps as a meme. Meanwhile, or soon after, the same concept might be rejected by another community as out of date, as ‘clunky’ and lacking descriptive power.

Thomas Kuhn’s The Structure of Scientific Revolutions provides some insight into this process. Kuhn identified periods of ‘normal’ science in a given field which would be followed by periods of ‘revolutionary’ science. The idea is that a community works within a particular paradigm (‘normal’ science) until the anomalies it generates lead to a crisis. A period of ‘revolutionary’ science follows in which competing paradigms that can better explain the phenomena are then explored. Some are accepted and some are rejected. Once a paradigm gains general acceptance then a new period of ‘normal’ science can begin and the whole process is repeated. Kuhn’s theory works in science because there are hard-and-fast phenomena to be explored; theories and concepts can be proved or disproved according to Popper’s falsifiability criterion.

The same is not necessarily true in the social sciences, however: it can be unclear what would constitute a falsification of certain widely-held concepts and theories. Indeed it is often the case that they gain or lose traction by the status of the people advocating them rather than the applicability and ‘fit’ of the concept. In addition, a concept or theory may serve a purpose at an initial particular point in time but this utility may diminish over time. Unfortunately, it is during this period of diminishing explanatory power that terms are often evangelised and defined more narrowly. This should lead to a period of ‘revolutionary’ social science but this is not necessarily always the case. If, for example, a late-adopting group holds political power or controls funding streams, even those in groups who have rejected the concept may continue to use it.

An example of this process would be the coining of the terms ‘digital natives’ and ‘digital immigrants’ in 2001 by Marc Prensky. This led to a great deal of discussion, both online and offline, in technology circles, education establishments and the media. Debates began about the maximum age of a ‘digital native’, what kind of skills a ‘digital native’ possessed, and even whether the term ‘digital immigrant’ was derogatory. As the term gained currency and was fed into wider and wider community circles, the term became more narrowly defined. A ‘digital native’ was said to be a person born after 1980, someone who was ‘digitally literate’, and who wouldn’t even think of of prefixing the word ‘digital’ to the word ‘camera’.

It is our belief that the explanatory power of a concept, theory or term in the social science comes, at least in part, through its ‘creative ambiguity’. This is the ability of the term – for example, ‘digital native’ – to express a nebulous concept or theory as a kind of shorthand. The amount of ambiguity is in tension with the explanatory power of the term, with the resulting creative space reducing in size as the term is more narrowly defined. Creative spaces can also bring people together from various disciplines, allowing them to use a common term to discuss a concept from various angles.

The literal meaning of a term is the denotative element and includes surface definitions of a term. For ‘digital literacy’ this would be to simply equate the term with literacy in a digital space. The implied meaning, on the other hand, is the connotative element and deals with the implied meaning of a term. With digital literacy this would involve thoughts and discussion around what literacy and digitality have in common and where they diverge. The creative space is the ambiguous overlap between the denotative and connotative elements:

Such creative ambiguities are valuable as, instead of endless dry academic definitions, they allow for discussion and reflection, often leading to changes in practice. In order to maximise the likelihood and impact of a creative space it is important that a term not be too narrowly defined, for what it gains in ‘clarity’ it loses in ‘creative ambiguity’. There is a balance to be struck.

Terms and phrases, however, can be ambiguous in a number of ways. Some of these types of ambiguity allow for creative spaces between the denotative and connotative elements of a new term to a greater or lesser degree. In other words, they involve greater or smaller amounts of ambiguity.


Prensky, M. (2001) Digital Natives, Digital Immigrants (On The Horizon, 9(5), available online at, accessed 14 December 2010)

The rest of the journal article deals with Empson’s 7 types of ambiguity as related to the above. You may want to check out the posts I’ve written previously relating to creative ambiguity. I’d welcome your comments!

Under-promise and Over-deliver: the language of productivity.

Remember time lost cannot be regained

I’m not going to look up the fancy psychological name for the process, but it’s a truism that we often don’t know what our opinions are or where we stand on a subject before we talk about it with someone else. That back-and-forth and interface with others not only helps cement our views on a topic, but helps to form our identity. It’s natural, therefore, that interactions with colleagues and friends shapes our self-identity.

When you’re communicating with others, you’re actually also communicating with yourself. Why? Because you’re the type of person who says the things that you’re saying. I’m sure I’m not the only one who is about to fire off an angry email, but goes back and re-drafts it in order not to further fan the flames. What I’m saying is that what you say about yourself to other people can actually shape how you are.

Most people over-promise and under-deliver. They say they’re going to be back from work before dinner. Then they’re not. They say that they’ll be able to achieve a certain target. Then they fail to hit it. I was the same until I read a productivity blog last year (I forget which) that talked about Tom Peters‘ mantra that you should under-promise and over-deliver. No-one is surprised when you achieve something you said you would or arrive at an agreed time. However, surpassing the target, or arriving early is often looked upon as a very positive trait in an individual.

Allied to this is the language you then use in your interactions. Be the type of person who can be trusted, the type of person who delivers. Which of the following would you rather receive?

Response A

Thanks for your email. Just got it. I’m working on a portfolio until late tomorrow, but will get the file to you then!

Followed by:

Here’s the file I promised you. Look forward to catching up next week!

Response B

On the other hand, there’s the usual:

Sorry I haven’t got back to you for a couple of days. I’ve been snowed under and then forgot! Oh well, apologies again, and please find the file you wanted attached.

Response A gives off the vibe of someone in control and who can cope with what’s being thrown at them. They’re the type of person who can deliver. Response B, however, smacks of someone who can barely cope with their inbox on a daily basis.

Who would you rather do business with?

(Image = Time Lost by gothick_matt @ Flickr)