Complexity science is understood to provide metaphors and analogies that give meaning to observed, experienced, and simulated reality (Fuller, 1999; Fuller & Moran, 2000; Lissack, 1999; Stacey, 2001, 2003a; Price, 1999). The language and metaphor of complexity science have been recognized for their potential in enabling people to revisualize their world (McMillan, 2004), by means of developing new ways of speaking and thinking about it, and in turn enabling new thinking to lead to new behavior. McMillan draws on the work of Morgan (1986) in this context and suggests that of his eight metaphors describing organizations, the metaphor of the organization as an organism, with links to biology and biological thinking, appears most relevant to the pursuit of linking metaphors and analogies from the complexity science domain to organizations and work, and the experience of the individual and groups in that context. This correlates strongly, for example, with the description of bee hives, ant hills, termite mounds, and bird formations as used to explain the theory of complex adaptive systems.
The theory of complex adaptive systems and their emergent properties (for example self-organization and emergence) are often presented through metaphors and analogies from the natural sciences, in particular those of bee hives, ant and termite colonies, and birds in flight (Bentley, 2001; Bonabeau & Meyer, 2001; Johnson, 2001; Kelly, 1994; Lewin & Regine, 2001; McMillan, 2004; Resnick, 1997; Sole & Goodwin, 2000; Stacey, 1996, 2003b; Waldrop, 1992). In the literature, colorful descriptions abound. For example, Resnick (1997: 3-4) writes of birds, and of ants, traffic, and economic markets:
“A flock of birds sweeps across the sky. Like a well-choreographed dance troupe, the birds veer to the left in unison. Then, suddenly, they all dart to the right and swoop down toward the group. Each movement seems perfectly coordinated. The flock as a whole is graceful—maybe more graceful—than any of the birds within it. How do birds keep their movements so orderly, so synchronised? Most people assume that birds play a game of follow-the-leader: the bird at the front of the flock leads, and the others follow. But that’s not so. In fact, most bird flocks don’t have leaders at all. There is no special “leader bird”. Rather, the flock is an example of what some people call “self-organization”. Each bird in the flock follows a set of simple rules, reacting to the movements of the birds nearby it. Orderly flock patterns arise from these simple, local interactions. None of the birds has a sense of the overall flock pattern. The bird in front just happens to end up there. The flock is organized without an organiser, coordinated without a coordinator. Bird flocks are not the only things that work that way. Ant colonies, highway traffic, market economies, immune systems—in all of these systems, patterns are determined not by some centralised authority but by local interactions among decentralised components. As ants forage for food, their trail patterns are determined not by the dictates of the queen ant, but by local interactions among thousands of worker ants. Patterns of traffic arise from local interactions among individual cars. Macroeconomic patterns arise from local interactions among millions of buyers and sellers. In immune systems, armies of antibodies seek out bacteria in a systematic coordinated attack—without any “generals” organizing the overall battle plan.”
Likewise, Bonabeau & Meyer (2001: 108) use ants as an analogy to convey the meaning and potential of self-organization in order to solve business problems, and go on to describe the way researchers at Hewlett-Packard’s laboratories in the UK had developed a computer program based on such ant-foraging principles in order to route telephone calls efficiently. The authors also report other organizations taking this approach, such as France Telecom, British Telecom, and MCI WorldCom. Metaphors and analogies based on ants have therefore had practical value by means of which new computer programs have been inspired and developed. Subsequently these have had an impact on the improvement of other technological processes. Other examples of computer programs similarly inspired and designed more specifically to study complex adaptive systems include genetic algorithms, as developed by John Holland of the Santa Fe Institute (Holland, 1992); the Boids simulation, developed by Reynolds (1987) to simulate the flocking behavior of birds; the Vants simulation, developed by Langton (1996) to simulate the trail-laying behavior of ants; and the Tierra simulation, developed by Ray (1992) using the analogy of biological evolution to evolve computer programs.
In addition, ants, termites, bees, and wasps have stimulated fascination and interest at a more general level, whereby individuals have come to learn about complexity science because of their interest in the collective behavior of these species:
“Social insects display some of the best examples of what we call emergent behavior. It is difficult not to become fascinated by the abundance of patterns shown by the work of ants, termites, bees, and social wasps. The huge nests of termites and raid patterns of army ants travelling through the rain forests are just two examples. We are fascinated by the collective behavior, but also by their ecological success: the dry weight of ants and termites in some rainforests is about four times that of all the other land animals. In some ecosystems ants compete successfully with rodents and other vertebrates. We find them all around the world, from deserts to the jungle, and they are strong competitors. Some authors even propose that this strong competitive ability leads to a well-defined partition of habitats, with ants and termites playing a central role and solitary insects having much less ecological relevance. But while colonies of social insects behave in complex ways, the capacities of individuals are relatively limited… generally speaking, single ants behave in a simple way… but then how do social insects reach such remarkable goals? The answer… comes to a large extent from self-organization: insect societies share basic dynamic properties with other complex systems… individual units do not gather, store and process information by themselves, instead they interact with each other in such a way that information is manipulated by the collective.” (Sole & Goodwin, 2000: 147—149)
However, in spite of the obvious appeal of ants, termites, birds, and bees, other work suggests that theoretically, a complex adaptive system view is not necessarily the most appropriate perspective to understand the way humans interact in organizations from the perspective of the individual in interactions with others. Stacey (2003b) offers a critical perspective on both the use of ants, birds, and bees, and so on as metaphors in general, and the theory of complex adaptive systems and simulations based on this in particular. In reference to metaphors such as that provided by the Boids simulation, Stacey argues that these cannot provide a source domain for analogies with human behavior, because the abstract relationships in such systems are relationships between cybernetic entities defined as deterministic, simple rules. Such simulations, he says, can only ever provide metaphors that may or may not provoke thinking about human interaction (Stacey, 2003b: 305).
Stacey does, however, support using complexity science analogies that resonate strongly with human experience, and also stresses the importance of acknowledging the importance of feelings, the importance of reflection-in-action, and the importance of abstract thinking (Stacey, 2001). In tandem with this is the possibility to explore how complexity science analogies could be used to make sense of complex responsive processes of relating. Therefore, it is the personal resonance with complexity science that individuals encounter that becomes important, and, increasingly so it seems, in the business world. Lewin (1999) validates this thought:
“In our conversations with business people we saw that there was powerful resonance between their thinking about their organizations and what is known about the world of biology. This interest in applying a complexity perspective to business organizations is growing… After all, most of us work in organizations of one sort or another, and so the world of business represents the most immediate experience of complex systems on a day-to-day basis.” (Lewin, 1999: xi)
While Lewin talks of applying a complexity perspective to business, however, Stacey’s position remains clear:
“The complexity sciences can never be simply applied to human action: they can only serve as a source domain for analogies with it.” (Stacey, 2003a: 53)
However, Lissack (1997) reported on the initial results of research carried out within a division of a biotech company with many thousands of employees and within a start-up Internet content provider with fewer than 40 full-time employees. The research focused on the use of complexity science metaphors and language by managers. From his research, Lissack referenced the use of eight metaphorical concepts taken from the complexity science domain. These included the fitness landscape, attractors, simulated annealing, patches, Tau, generative relationships, increasing returns, and sensitive dependence to initial conditions. The objective of Lissack’s research, carried out initially by means of semiotic analysis, was to differentiate domains in which certain types of metaphors were more appropriate and to identify action items stemming from those metaphors. Through this approach Lissack explored how the organizations he researched would benefit from learning about complexity science metaphorical concepts for specific tasks.
The research underpinning this paper, however, took a step back from this point of interest and sought to take into account what stimulated interest in and learning about complexity science in the first place, and how this could be seen to change over time. The study reported on in this paper deployed one main path of research, loosely inspired by the survey approach, and utilized data-collection methods commonly associated with surveys; that is, interviews and diaries. A hybrid interview style was adopted, in which elements of the different styles of semi-structured, unstructured, ethnographic, depth, intensive, and creative interviews were applied. Diaries were utilized in an open-ended format and an interactive style of ongoing research. This engaged the participation of 13 individuals in the writing of qualitative, weekly, work-focused diaries. The diarists wrote their diaries for between one and fifteen months (with an average of six months’ diary writing). Participants were also emailed text-based extracts on management theory relating to the subject of complexity science and were asked to make comments concerning these in their diary. Prior to embarking on the diary-writing exercise, participants were asked to take part in interviews, to establish the context of their own personal background in addition to their interests and motivations for taking part, any prior knowledge regarding complexity science, and how they had been stimulated to learn more about it.
The research interviews conducted with research participants prior to their embarking on the diary-writing study revealed that four of the participants had been explicitly stimulated to find out more about complexity science because of a combination of having their curiosity aroused by the natural sciences in addition to experiencing some kind of emotional connection with the subject.
Personal interest in the natural sciences therefore played a key role. Two research participants referred to their own environmental awareness as being a stepping stone into complexity science, in terms of their understanding of nature and bio-ethics. Analogies from the animal kingdom had attracted and drawn two participants further into an understanding of complexity science. Specifically mentioned were ants, bats, bees, birds, and termites. The following extracts reveal the context surrounding this.
Research Participant 1: “If I had time at the moment, then I would definitely be looking at genetics […] Part of what for me came out of that phase of looking at chaos theory was then also looking at this whole emotion of how do we come to be here, who we are and that linked me in with the nature/nurture thing which links in with this whole genetics thrust that there is and the whole of bio ethics … At the moment there’s also been a bit of a thread of work which I’ve been doing around bio ethics … So at the moment my interest is in that field.”
Research Participant 2: “If you take it to the ant example for instance, I like animals, I love animals, I really do. I do a yearly charity thing for Save the Rhino, which is a charity that helps save Rhino’s basically, because it’s what you call an indicator species—a measurement for how an ecology is working. And I like animals, I love Africa, and these sort of places, this is what I do […] Humans are not ants. Ant models are lovely to think about certain things, but they are not human beings. All these lovely programmes that have been created that describe ants and flocks of animals, describe only that. They don’t explain why I fall in love or…., you know. I think they are very, very limited in their thinking. And I also think that animals are much richer than we give them credit for […] I think humans are animals in some form, but they are different types of animals… we think as humans and therefore we are different from others […] But, I like animals because they are part of who we are in that world. I’m prepared to put my energy into some of this, because I think it’s important that we have at least some responsibility for the survival of species and things like that […] Jack Cohen and Ian Stewart wrote a very famous chapter somewhere in one of their books, it’s called “what would it be like to be a bat?” How would a bat think about being a bat? And the answer is you don’t know, because you are not a bat. And you won’t ever know […] I think it’s an interesting example with Termites, where they recently found out there’s a whole different evolutionary path that we didn’t know about, why they have soldiers going on searches, and the point would be to go and capture the other colonies and kill the king and inform. It’s very complex. I mean, this is not something you can explain with very simple rules. So, yes, I like that […] But I’m very uncomfortable to say because ants, termites or bees, or birds behave in a certain way that that tells me how humans behave. It’s a very anthropocentric way of looking at the world and it doesn’t quite work that way for me. It doesn’t help.”
Research Participant 3: “For example, now I know of the ants, ooh look at these, and they never clash with each other, then they work for one objective and they are so happy. They are so happy. And some of them die, and others are explorers that go and explore things, and then I don’t know why, they call the others, and then they go too. And now I can’t kill an ant for instance—I can’t.
“And one thing that interested me, when I first started to investigate, was the biological system and things like this, the birds, and biology and so on.
“For example, I have already read about the birds […] and the formations that they do, and the things that they know, and things like that. And the other day I was really looking at it. Well it’s amazing, and now this will be in my head forever […] because it’s an experience. You experience what somebody already experienced, because when people write about it, people report experiences. So they are expressing what they experience. But it’s not the experience itself. And when you read it, you are not experienced, you are reading these things. But then when you experience what they experience, then it’s yours also, it’s part of you also.
As mentioned above, the interest stimulated by ants, bats, birds, bees, and termites was wrapped up in a larger emotional experience. Emotional triggers of exploration into the domain of complexity science were different among all participants, but included such things as feelings of amazement, attraction, enjoyment, and generally having their interest stimulated or having “wow moments,” as the following extracts show.
Research Participant 2: “I graduated formally in 2002 I think […] You start to see what appeals or doesn’t appeal, in your way of thinking, what resonates […] with my experience as a consultant, and as a human being basically. Then I started to make connections based on what I’ve learned there […] There was one book I read years ago, Kevin Kelly’s Out of Control, which I am sure you know, I’m not sure if you’ve read it, but you should, it’s quite an interesting book. What he does, he describes clearly how when, he talks about machines, he said that when they interact the behavior emerging out of that is actually quite interesting. He calls it flocking behavior, or that sort of stuff, which is machines, it isn’t human beings but he draws some parallels with that in his book, and I think it’s quite an interesting book. And what he really describes is that [...] there is no form of control other than our own behavior […] but we can pay attention to that on the micro level, and that’s all we can do, and use that in order to make more sense. And he uses an interesting example that was kind of a “wow” moment for me; if we do an excursion to Mars we send a multimillion expedition vehicle out there, a rover, that goes and crawls the planet and collects samples, it’s very susceptible to one little failure somewhere, so why don’t we use half of that money and send a hundred thousand little ant-like vehicles to Mars to crawl over it, and if 50% fails we still have 50,000 functioning machines, and what we do, what we create is weights in these little machines that can connect to each other, so that they know what each other is doing—which is of course a very powerful complexity principle. And, I thought, “golly, yes, it’s very interesting, as a tax payer you worry about that they send these big things out there.” Well, that’s a shift. That’s a shift in thinking, and that helped me big time, that sort of thing. So perhaps it was that book, I don’t know, at least some of the reading.
“Similarly, some of the concepts that Mitchell Waldrop talks about, although very much from an economics point of view, very often, particularly at the beginning of the book, were a bit like that, so was it a wow moment? I’m not sure. But that was definitely a wow moment […] Well, there were always wow moments, I mean, one other wow moment I had […] was when I started to realize, that, and that’s what Stacey taught me basically, is that the concept of a system is a very difficult concept to work with, because it implies a certain outsider looking in perspective, as if you can look at the world as something you can control without being affected by it in some generic sense. That did worry me in a way […] and that’s why I stopped feeling comfortable with that concept […] You are always part of the conversation, whether you like it or not. And even worse, you’ve got a certain power position very often, so whatever you say and do, has a major effect […] I think it’s an interesting example with Termites, where they recently found out there’s a whole different evolutionary path that we didn’t know about, why they have soldiers going on searches, and the point would be to go and capture the other colonies and kill the king and inform, and it’s very complex, I mean this is not something you can explain with very simple rules. So, yes, I like that.”
Similarly, research participant 3 described her and her colleague’s amazement in what they had learned at a broader level:
“Chaos Theory interests me, because it is like whoa everything is chaos, it is amazing […] when I arrived at this company, the first project that I did with innovation, we had to do some concepts about a technology that the client had. It was a thing on three dimensions […] And this is, “Whoa, what is the 4th dimension?” And I started to look for the maths and so on […] It was fantastic because it was so amazing these things about […] everything depends on everything, and everything is changing, and so on. And then this related to complexity theory […] It’s because it’s amazing how we know these things, by theory also. There’s a gap, a very big gap between theory and how we do things. There’s lots of people that know about this and they, it doesn’t mean anything for their life, and this really changed my life. Really changed like respecting things […] [One of my colleagues and I] have lots of conversations, really amazing. But he knows so much, and well, he knows lots of things and he links everything, and this is great because you can learn a lot from him.”
Research participant 3 also described her like of and enjoyment in learning about patterns and behaviors through the natural sciences, stressing her emotional connection with this:
“And I like to observe a lot […] Because, I like anthropology and sociology, and I also like object theory. And because it makes you think a lot […] And so I, I read lots of things, but I personally like more philosophical things. And I think it’s also, more than anything, I think is good to have other perspectives […] Also to identify patterns of behaviors. Sometimes it’s good for relationships. You find patterns, and it’s like, “Ok, ok, this guy is a little bit like this, maybe it’s because of this, this and this and this,” and it makes you like people more, because you can understand them […] Everything is intelligent. And we humans think that we are intelligent because we have information, and this is not true, intelligence is everywhere […] Cells are intelligent, trees are intelligent and this is amazing, this is so, I don’t know, but when I talk about these things, I feel very happy. I don’t know why it’s something even emotional, I don’t know, it’s something that makes me happy. I don’t know how or why things are like this.”
Research participant 3 located the stimulation of her interest in the way she positioned herself in relation to what she was learning and seeking to understand, therefore making the experience a very personal one:
“Sometimes I read some point of view, “ah read this, this is very interesting,” it is a very good book […] Because I start to see how it’s affecting me […] because everything is connected, and this stuff interests me a lot, and it makes me change […] I’m a designer, and a little bit ego-centric, because a product has always a little bit of you, of your personality. If I have to draw or to design a chair, it will be completely different than if it’s you who designed it. Even if they have four legs and a thing to sit on and so on, it will be completely different. And this has to be about, your experiences, your influences, and what you are thinking…. So this always has to be, something behind the object, something behind the painting that you are seeing, behind the sculpture that you are seeing, behind anything that you are seeing. And this “behind” always interested me. What is behind things?”
Research participant 4 explained her need to develop new insights and have her interest stimulated:
“And I didn’t really know anything and I think it was probably the fact that I wanted to… because I do feel that I mean there’s like loads of energy in this town but I do sometimes feel that you know ideas can be too repetitive or people don’t have enough kind of outside influences so I think it was very much the thing of getting new outside influences […] I mean there’s a lot of artists using computer programmes and if you think of the media there will be somebody in media art doing stuff. It’s just finding the ones that are really doing interesting stuff […] I think I just don’t feel the artists are expanding enough, I think that’s it […] I was reading a biography, I was really, and they were talking in relation to economics and stuff like that, that really interested me.”
Therefore, as these interviews show, individuals not only experienced an emotional connection with what they were learning, but sometimes actively sought that emotional connection out. Their subsequent intellectual interest generated in ants, termites, birds, and so forth was packaged in this emotional response. This was shown when, following the interviews, the research participants embarked on a personal, diary-writing exercise. These diaries, especially from six of the thirteen diarists, further revealed that the behavior of ants, termites, and birds stimulated thought, debate, contention, and inspiration for them.
Research participant 5 referred frequently to ants and termites and her interest in the topic:
“Termite colonies and connected lives of ants, brains, cities, software and complex adaptive systems—coincidence or a pattern…? It does remind me of my rambly diary last week about the conflict between business outcomes and the personal needs of employees.” (Diary entry 14).
“Emergence was my holiday book—and although I only managed a chapter on ants it was interesting to see that’s exactly where I left off more or less with the diary as well […] Anyway the piece I managed to read was about the greater scheme of things within the ant world that regulates and I was thinking that this is probably the root of religion/gods etc. Our need as a species to make sense of things—was Gods etc created as an explanation for things that people couldn’t explain/rationalise […].” (Diary entry 15)
“Ants seem to be quite interesting at the moment—the idea of an individual contributing to a wider context—simultaneously self organizing and being organized/regulated by reading the signs of other ants’ self-organization. Kind of feels like a “glocal” approach—engage and take care of the local and the bigger picture looks after itself as the influences are felt on a micro level creating the macro-picture.” (Diary entry 22)
“I was thinking again about ants—how they can’t see the bigger picture and could this be one of the roles of artists/creatives, is this contradictory to “scratching your own itch” theory but I wondered if there was a relationship to laterality, abstract and spatial awareness that enables a wider perspective other than the what’s in front of your nose. Kandinsky has his theory of the triangle with artists at the apex pulling “society” forward […].” (Diary entry 23)
Research participant 2 commented on the analogies of ants and termites from a more critical perspective:
“I can see the appeal of looking at termite mounds and be in awe with the self-organizing nature of it. I think it is quite another thing to then draw the parallel to human society […]. For me, he makes the fundamental mistake that many people make that want to apply complexity science to human organizing. They apply it, per se. Take the rules […] and import them in human society. I think one cannot just do that… Again, I come back to Stacey’s recent work (this is no coincidence, because it really resonates with me). He builds up a theory of human relating (not ants or termites!) and then uses the principles of self-organization and emergence as an analogy to explain the pattern forming that we experience in social interaction […].” (Diary entry 6)
Research participant 3 discussed her feelings and thoughts about ants and termites:
“[…] The mound is an architectural marvel […] as a whole, members of the mound constitute a sophisticated society that makes it possible to meet the ever changing needs of the colony. […] This is really amazing!!!! One thing that is bothering me, and that is making me think is: are they conscious of it? Is it done by habit by impulse? Even if it is marvellous and precise, we will never know […] the why, how, and what for […].” (Diary entry 34)
Research participant 3 discussed the gap between instinct and action after reading an extract concerning the simulation of flocking birds:
“Take a simple example, namely a flock of birds […] Reynolds (1987) simulated the flocking behavior of birds with a computer program consisting of a network of moving agents called Boids. Each Boid follows the same three simple rules—in my point of view they act by instincts, we humans, we have instincts but also a mind, that makes us think in all that we feel. In a flock of birds, each one acts on instinct, they don’t think “aaaaaaaaaaaaaaaa, I have to follow that guy” they just do it, there is no gap between action and instinct, and in humans there is a huge gap between thought and action, sometimes even action does not take place (which can be good or bad, judgement is not important now).” (Diary entry 35)
Research participant 6 referred to the dominant themes in the literature pertaining to metaphors of bird and ants, and not people:
Discussion and conclusions
From the research findings presented, two main issues become clear. First, that analogies or metaphors relating to the natural sciences are of interest to some people, can stimulate their interest in complexity science further, and provide food for thought. Therefore, it is a reasonable assumption to make that when teaching or providing learning material on the topic of complexity science, it is of value to include metaphors and analogies on ants, termites, birds, and bees, and other phenomena from the natural sciences.
Second, the arguments around the validity of the congruence with such analogies and human relating are accepted by complexity science students, and this is acknowledged by them retrospectively as an important step in their learning. Once an individual has been introduced to this thought or makes the leap themselves, they are then ready to develop their ideas further and actively question the extent to which analogies about ants, termites, birds, or bees can be of use or relevance to them as humans. Following this, progression can be made to searching out theories more relevant to human relating, such as, for example, Stacey’s complex responsive processes of relating.
There is therefore some response needed to Stacey’s assertions that simulations based on ants, termites, birds, and bees cannot provide a source domain for analogies with human behavior, because, he says, such simulations can only ever provide metaphors that may or may not provoke thinking about human interaction (Stacey, 2003b: 305). The findings in this paper acknowledge this point but also reiterate the value of that very point, emphasizing that it is precisely the fact that these simulations can provide metaphors that provoke thinking about human interaction that makes them of value to individuals learning about complexity science. There is justification in being presented with analogies and metaphors based on the natural sciences because they inspire and stimulate interest and the conversation needed in order to take a step further in developing an awareness and understanding about all that complexity science can offer.
In supporting the use of complexity science analogies that resonate strongly with human experience, and stressing the necessity of acknowledging the importance of feelings, the importance of reflection-in-action, and the importance of abstract thinking (Stacey, 2001), Stacey’s critique of simulations, metaphors, and analogies based on ants, termites, birds, and bees misses the essence of what it is about complexity science that initiates such a process in the first place—a process that is often grounded in an emotional pull followed by intellectual stimulation.
In this paper, Stacey’s position that “The complexity sciences can never be simply applied to human action: they can only serve as a source domain for analogies with it” (2003a: 53) is therefore acknowledged but rephrased as: “Complexity science can never be simply applied to human action, but can serve as an emotionally inviting, intellectually inspiring and stimulating source domain for metaphors and analogies with which to begin to develop further understanding of it.”
In this way, complexity science metaphors and analogies based on ants, termites, birds, and bees are reaffirmed in their role as having value as images and vivid words. As Weick (1995) said, this can draw attention to new possibilities and provide the means by which to offer people, or organizations, access to more varied images in order to engage in sense making that is more adaptive than for those with more limited vocabularies.