On Ontological and Descriptive Complexity

There’s a duality between descriptive and ontological complexity (Emmeche, 1997) and in socio-complex systems we are dealing with both. Defining ontological boundaries in complex adaptive systems is difficult because they are open systems, in constant interaction with their environment. How do we determine which parts belong to one system and which ones to another? The boundary isn’t clear and we can define the system arbitrarily.

Cilliers (2001) wrote “Boundaries are simultaneously a function of the activity of the system itself, and a product of the strategy of description involved. In other words, we frame the system by describing it in a certain way (for a certain reason), but we are constrained in where the frame can be drawn. The boundary of the system is therefore neither purely a function of our description, nor is it a purely natural thing.”

The boundary, therefore, is phenomenological as well as ontic-epistemic. It cannot be clearly defined, it’s fuzzy and has descriptive and ontological properties.

Cognitive Edge’s SenseMaker® can give us a good idea of a system and its boundaries by identifying patterns, attractors in the system, stability and fitness landscapes, and in a continued research showing their dynamics over time. In a broad sense the boundaries are constrained by the signification framework, but the narrative fragments themselves aren’t rigidly constrained and can contain anything and extend beyond what are regarded as boundaries. It does, however, provide a way for comparative ontology by combining quantitative and qualitative research, and I think it’s about the best we can do.

Emmeche (1997) said “we cannot a priori decide whether descriptive complexity entails ontological complexity.” It may, but it may not. Boundaries, likewise, can be descriptive or ontological, or both.

I suggest we could look at boundaries as a form of descriptive-ontological dualism; the descriptive aspect being crossing a domain boundary, while the ontological aspect being an ontological change, a transition in the state space, a phase shift in the system dynamics. Even highly constrained systems don’t exist in isolation and have varying degrees of freedom and connectivity – only constrained – and may be perturbed to induce a transition in the state space, so we don’t even need to limit ourselves to considering only ontologically complex systems.

(Originally posted as comments to Dave Snowden’s blog entry about Boundary conditions.)

Briefly On the Domain of Disorder in Cynefin

I consider the domain of Disorder key in Cynefin and sense-making, and understanding its significance was a Heideggerian moment of poiesis for me; the bringing-forth, unconceling something that was concealed, to quote from my polemical essay on Authenticity.

I went through my Twitter history on Disorder, and aggregated some thoughts on Disorder, as they would appear relevant. I’ve expanded some of them from the brevity of Twitter.

The most neglected domain in #Cynefin – disorder, inauthentic – is also probably the most important for understanding the nature of Cynefin.

Inauthentic(ity) (disorder) is a type of an ontological error and a cause for cognitive bias. It’s where we are most of times.

We engage in sense-making to move towards authenticity of agency but it’s a dynamical process, not a one-off categorisation.

Sense-making in Cynefin begins from the domain of ‘Inauthentic’ Disorder, from phenomenological apperception.

Inauthenticity is always present as a gradient in every Cynefin domain as fuzzy boundary conditions.

Inauthentic disorder is why we engage in sense-making and why Cynefin is dynamical sense-making framework.

Inauthentic refers to inauthentic ontological awareness. We engage in sense-making to shift agency towards authenticity.

Authentic agency is ontologically advised and epistemically validated motivation.
When our actions are informed and autonomous, not compliant or conformist, when they are consistent, aware and situated, they’re authentic.

Sense-making can advise agency towards authenticity, while true authenticity remains unattainable.

On brevity and the 140-character constraint

It often begins with a tweet, doesn’t it?

So, yesterday Jabe Bloom tweeted:

“Might it be possible that instead of the world “getting more complex” our aging models don’t fit a world, we’ve radically changed, anymore?”

As always with Jabe’s tweets and blog posts, it was another thoughtful and thought provoking question. Is the world “getting more complex” or is it a question of observational scope and trying to make everything around us fit into the models that we’re familiar with and which create the illusion of order? I replied with:

“Certainly. Due to co-evolution, expanded temporospatial and ontological awareness and bounded applicability of models.”

Now, the wording in that reply was deliberate as I was trying to compress four aspects I felt were relevant into the constraints of Twitter’s 140 characters. Specific words convey more context relevant to the ideas being put forth. But they can also appear as so many fancy words.

Ari Tanninen, my new chum who’s as sharp as they come (and if you’re interested in Agile, Lean, SW dev, complexity, you’d do well to follow in Twitter & elsewhere), replied to me saying: “I understood some of those words!”

Cheeky bastard. He understands them all (I told you he’s sharp).

But it’s a good point, and I thought I’d briefly open up the choise of wording in that tweet of mine.

Coevolution. In Complex Adaptive Systems, the agents and the system co-evolve. Agents (people, ideas, etc) acting in the system, through interaction with each other and the system, modify (change) the system, and the modified system changes the agents acting in it. My point was that due to coevolution, our models will never be accurate in the first place. The only accurate model of a complex adaptive system is the system itself. Ashby’s Law of Requisite Variety comes to mind, yet again.

Temporospatial. This simply means relating to time and space, or distance. I wanted to suggest that largely through advances in technology, we’re more aware of what goes on around us. We’re increasingly connected, not only acting in the immediate physical here and now. The notion of locality and time has changed. We’re connected to more and wider networks than we used to be even ten or twenty years ago, let alone 50 years ago. The observational scale we choose determines the degree of perceived complexity.

Yaneer Bar-Yam writes in his paper Multiscale Complexity/Entropy:

“The complexity as a function of scale of observation is expressed in terms of subsystem entropies for a system having a description in terms of variables that have the same a-priori scale. The sum of the complexity over all scales is the same for any system with the same number of underlying degrees of freedom (variables), even though the complexity at specific scales differs due to the organization / interdependence of these degrees of freedom. This reflects a tradeoff of complexity at different scales of observation.” -Yaneer Bar-Yam, New England Complex Systems Institute, Cambridge, Massachusetts 02138

Ontological. A philosophical term in metaphysics meaning the nature of things. We’re more aware of the nature of things around us. The way things are determines what we can know about it and how we can act in it. Ontology precedes epistemologyEverything isn’t the same around us, and there isn’t a cookie cutter way of working. This is a reference to Cynefin and multi-ontological sense-making.

Bounded applicability. This ties into the notion of ontology, and means that there are natural limits to the usefulness of things. The context advices the approach.

So has the overall complexity of the world around us grown in real sense, or is it a question of scope and view, and how we choose to define the boundaries of the system we’re investigating? I think it’s a question of the scale of observation and inauthentic ontological awareness. Googling for entropy and complexity, I came across Yaneer Bar-Yam’s paper on Multiscale Complexity/Entropy. Sounds like the right avenue to continue exploring this topic.

Complexity and all that jazz…

One thing I’ve always liked about Twitter is how it sparks new thoughts and ideas.  It’s fragmented nature lends itself to serendipitous discovery and connection of thoughts, people and ideas.  Not always profound, but often delightful, and interesting enough to explore a bit further.

Like a couple of days ago.

With CALMalpha, which I’m eagerly anticipating, only a few days away now I’ve been thinking about the nature of complexity perhaps more than usually. Now, complexity and complex adaptive systems theory are getting traction as the next Big Thing in management and social business – a thought that quite frankly scares the hell out of me.  Complexity and complex adaptive systems theory, among other disciplines like evolutionary biology and cognitive sciences have real utility in management science (and I use the word science here only illustratively), but they are also easy prey to airport management book authors who get enthralled by the language and references to natural systems, and quickly churn out a new book and a series of keynotes and lectures with complexity slapped on as a superstructure to old thinking and old ideas.  Dave Snowden speaks about this often, and addressed it in a recent blog post, and I agree with him.

So I recognize the folly of trying to see complexity in everything because not all systems, human made or natural, are complex adaptive systems.

But sometimes complexity metaphors – even imperfect ones – have utility, which takes me back to a Twitter exchange earlier between Heimo Laukkanen (@huima) and myself.

It happened to be about jazz.

Heimo tweeted that he’d been searching for jazz playlists on Spotify (an indication that he’d become an old fart nearing retirement age – his words), and being a jazz devotee of sorts myself, I replied with a couple of recommendations of the usual suspects.  Turned out that Joseph Pelrine, another complexity scholar and part of the CALMalpha faculty, had beat me to it with great recommendations so I wrapped up by saying how it occurred to me that jazz and complexity have interesting parallels, and with a few caveats jazz serves as a useful metaphor for a complex adaptive system.

Complex adaptive systems have certain common characteristics, such as self-similarity, emergence, and self-organization (Wikipedia).  They have high degree of adaptive capacity, and they’re resilient to perturbations.  Complex adaptive systems have many independent but interacting agents acting mostly locally but with global, system wide consequences.  The agents and the system co-evolve.  Small changes may have system wide results, interactions in the system have feedback loops, the systems are dynamic and dissipative exchanging energy and never functioning at an equilibrium.  It’s also impossible to determine the system’s behavior by observing individual agents; complex adaptive systems exhibit emergent behaviour, and their dynamics evolve towards a representation of the systems typical behaviour, an expression of the dynamics of the system at some point in time, also known as an attractor. The system’s history defines its future states, the agents and the system co-evolve, and the system’s boundaries may be fuzzy.

Jazz is a mix of musical styles, and it’s probably easier to say what is not jazz than what is, although even then interesting debates would surely follow.  There are certain common characteristics, including improvisation, and group interaction, call-response patterns, use of blue notes, polyrythms, syncopation and swung notes (Wikipedia), but jazz is constantly evolving and seeking new paths, experimenting and breaking form, exploring and stretching its boundaries.  Trombonist J.J. Johnson has said “Jazz is restless. It won’t stay put and it never will”, and according to Pat Metheny, it’s not the music of Kenny G.

It’s not a big stretch to draw parallels and to create a metaphor of complexity from jazz.

Finding self-similarity in a jazz combo is perhaps a bit of a stretch. I suppose we could imagine jazz exhibiting self-similarity with regard to the size of the combo and the dynamics of jazz, in the rhythmic patterns of instruments and so on, but there are better parallels.

Like unpredictability.  As with a complex adaptive system and its agents, a jazz band’s performance and what kind of music they will be playing cannot be determined by listening to the individual players. We’ll only know when the musicians start playing together, and the band starts swinging – when the system starts exploring its phase space, the possible outcomes of the session.  A jazz session doesn’t have a set destination which has to be reached. Instead, to borrow Snowden, the musicians explore the evolutionary potential of the present.

Small changes may have large consequences. Musicians play off of each other, picking up subtle cues and responding to them.  Every new note played, every bar, every modulation is like a probe into the complex adaptive system of a jazz combo, a safe-to-fail experiment, using Cognitive Edge’s Cynefin


The Cynefin framework

terminology.   If the response of the experiment is beneficial and the band picks up on it, it gets amplified.  If it doesn’t get picked up and reciprocated, it gets dampened. It’s a constant feedback loop, where improvisations, cues, notes, melodies, body movements, and even audience reactions affect the future direction of the music.

The history of the system determines its future direction, and history is created every second.  Every note played up until any given time determines the direction that the music will take, and this gets repeated every moment.  It’s a dynamical session.

Jazz sessions are also irreversible.  It is not possible to call “halt”, rewind back time and start over, playing exactly like before.  Everything in the band (the system), including the players (agents) and the band have changed, co-evolved, and what has happened is not perfectly repeatable.  It may be close, but not just like it.

Emergence is an obvious characteristic of a jazz session.  Swinging, improvising, experimenting, interacting, will produce patterns that we perceive as pleasant or exhibiting coherence.  The musicians call it the groove.  Groove is not a pre-decided goal where the jazz session is merely the means of transport towards it; instead it’s an emergent pattern arising from the complex interactions of the jazz band and the session.  Groove is an attractor of the system of a jazz band.

Modulators.  To quote Wikipedia, modulation in music refers to “the act or process of changing from one key to another”.  Modulations “articulate or create the structure or form of many pieces, as well as add interest.”  In complex adaptive systems modulation is a form of perturbance, an intentional or unintentional influence on the system tending to alter its behaviour.  Modulation is an oblique way, as opposed to a direct driver, of trying to influence the behaviour of a system.  In jazz and in music generally, (musical) modulation techniques belong to the fundaments; they are a part of improvisational techniques and constructs of melodic and harmonic progressions.  They’re also system modulators.  They perturb the system by introducing variations, gentle nudges to the rest of the band to keep exploring the possibilities and to avoid an equilibrium.

While jazz can serve as a metaphor for complexity and emergence, obviously grooves and albums like Kind of Blue don’t ‘just happen’ through emergence if you put a bunch of musicians in a room with instruments, and make them play.  Even jazz has constraints, and creative processes can be managed, only not directly; in a complex space you “manage the beneficial coherence within attractors, within boundaries.” (Dave Snowden, Cognitive Edge).

Other parallels could easily be drawn for instance between jazz and Cynefin domain boundaries, but that perhaps goes beyond what my intention was writing this entry.  Mostly, I’m just thinking out loud by writing.

Metaphors are useful because they can have a basis in everyday experience, and therefore have a subjective interpretive layer.  Interpretation introduces variation to the sense-making process between individuals, and helps to avoid early convergence of thoughts and ideas.  In discourse it increases beneficial dissent and as a consequence improves decision making and scanning range of available options. In short, it makes for more interesting conversation.

But when I put on Kind of Blue, there’s no room for analysis.  There’s only music.