Technology Review covers Stuart Kauffman‘s work to find a mathematical model for autocatalytic sets, the process by which life may emerge from molecules:
What makes the approach so powerful is that the mathematics does not depend on the nature of chemistry–it is substrate independent. So the building blocks in an autocatalytic set need not be molecules at all but any units that can manipulate other units in the required way.
These units can be complex entities in themselves. “Perhaps it is not too far-fetched to think, for example, of the collection of bacterial species in your gut (several hundreds of them) as one big autocatalytic set,” say Kauffman and co.
And they go even further. They point out that the economy is essentially the process of transforming raw materials into products such as hammers and spades that themselves facilitate further transformation of raw materials and so on. “Perhaps we can also view the economy as an (emergent) autocatalytic set, exhibiting some sort of functional closure,” they speculate.
Could it be that the same idea–the general theory of autocatalytic sets–can help explain the origin of life, the nature of emergence and provide a mathematical foundation for organisation in economics?
I find this very interesting, but don’t get too excited. These sorts of grand unification theories are extremely elusive. I’m also skeptical of these sorts of models which try to find universal rules for all types of systems.
Great new interview with Nassim Taleb by one of his former teachers at Wharton:
Taleb: The events in the Middle East are not black swans. They were predictable to those who know the region well. At most, they were gray swans or perhaps white swans. One of the lessons of “Wild vs. Mild Randomness,” my chapter with Benoit Mandelbrot in your book, is what happens before you go into a period of wild randomness. You will find a long quiet period that is punctuated with absolute total turmoil…. In The Black Swan, I discussed Saudi Arabia as a prime case of the calm before the storm and the Great Moderation [the perceived end of economic volatility due to the creation of 20th century banking laws] in the same breath. I was comparing Italy with Saudi Arabia. Italy is an example of mild randomness in comparison with Saudi Arabia and Syria, which are examples of wild randomness. Italy has had 60 changes in regime in the post-war era, but they are inconsequential…. It is a prime example of noise. It’s very Italian and so it’s elegant noise, but it’s noise nonetheless. In contrast, Saudi Arabia and Syria have had the same regime in place for 40 some years. You may think it is stability, but it’s not. Once you remove the lid, the thing explodes.
The same kind of thing happens in finance. Take the portfolio of banks. The environment seemed very placid — the Great Moderation — and then the thing explodes.
Herring: I would agree that people knew the Middle East was very vulnerable to turmoil because of the demographics, a very young population, and widespread unemployment, the dissatisfaction with the distribution of income and with regimes that were getting geriatric. But knowing how it would unfold and knowing that somebody immolating themselves in a market in Tunisia would lead to this widespread discontent — and we still don’t know how it will end — is a really remarkable occurrence that I think would be very difficult to predict in any way.
Taleb: Definitely, and it actually taught us to try not to predict the catalyst, which is the most foolish thing in the world, but to try to identify areas of vulnerability. [It’s] like saying a bridge is fragile. I can’t predict which truck is going to break it, so I have to look at it more in a structural form — what physicists call the percolation approach. You study the terrain. You don’t study the components. You see in finance, we study the random walk. Physicists study percolation. They study the terrain — not a drunk person walking around — but the evolution of the terrain itself. Everything is dynamic. That is percolation.
And then you learn not to try to predict which truck is going to break that bridge. But you just look at bridges and say, “Oh, this bridge doesn’t have a great foundation. This other one does. And this one needs to be reinforced.” We can do a lot with the notion of robustness.
The term “systems thinking” has a few different connotations. Classically, non-linear dynamic systems represents a set of principles that describe the organization of energy as an extropic function of information, driven by power laws and bounded by limits. The formulas within this domain are often applied to natural systems such as populations, fluid dynamics, and so-called chaotic processes like dripping faucets and epileptic seizures. Some of the better-known ideas within dynamic systems are attractors, bifurcations, and the process of iteration.
More broadly, systems thinking refers to a widening perspective when studying networked domains. For example, the recent trends in Life Cycle Analysis in product design & manufacturing attempts to go beyond the material & energetic costs of the physical object – eg a plastic bottle of water – to consider every aspect of its life cycle from sourcing all of materials and manufacturing support, cost of shipping, human impact of the workers, environmental impact, and end-of-life in a landfill or recycling depot. Wal-Mart, to its credit, has made great strides across its supply chain by optimizing efficiency in the life cycle of the many products that end up on its shelves and in people’s lives. Some of these solutions can be a simple and radical as redesigning packaging for minimal materials use and shipping weight.
Recently, systems thinking has been applied to the design process suggesting that designers are uniquely empowered to engineer powerful solutions for complex problems in ways that benefit many different human and non-human stakeholders, eg nature is a primary stakeholder, as are future generations saddled with our often myopic creations.
I tend to use systems thinking to describe all of these connotations rolled up into a general way of looking at the world that goes beyond what is immediately visible and reaches into the extended connections and unseen impacts within a domain. In some respects, this way of thinking is a natural part of simply paying attention to things. In other ways, it’s a challenging and sometimes overwhelming course of study that can easily move from Aha! moments to a very dis-empowering sense of total non-determinism. In the face of such huge complexity it can seem impossible to make any actionable sense of things. Finding the balance and determining the appropriate scope of research in analyzing a domain is a critical skill that must be developed individually through practice, lest you tug on that thread and find you’ve unraveled the entire sweater.
Some resources to get you thinking about the micro & macro of complex systems:
Complexity: a Guided Tour by Melanie Mitchell. A great, thorough introduction to complexity and systems thinking. Beginner to intermediate. Don’t be scared by the equations – there’s lot’s of good info here. “Readers will marvel at the sheer range of settings in which complex systems operate: from ant hills to the stock market, from T cells to Web searches, from disease epidemics to power outages, complexity challenges theorists’ intellectual adroitness. With refreshing clarity, Mitchell invites nonspecialists to share in these researchers’ adventures in recognizing and measuring complexity and then predicting its cascading effects.”
Turbulent Mirror: An Illustrated Guide to Chaos Theory and the Science of Wholeness by John Briggs. A solid introduction to systems, chaos, and wholeness. “Briggs and Peat look at how chaos theory has also influenced other scientific disciplines, offering a model, for example, for understanding the human brain and developing computer systems for artificial intelligence. The book’s chapter heading quotations from Chinese Taoist texts and Alice in Wonderland are clues that readers are being led into abstruse territory. But encouraging readers to appreciate nuances of truth rather than to seek a reductionist version of truth may be what chaos theory–and this book–is all about.”
The Web of Life: A New Scientific Understanding of Living Systems by Fritjof Capra. A great analysis of how complexity and non-linearity inform the foundations of our natural world. “…brilliant synthesis of such recent scientific breakthroughs as the theory of complexity, Gaia theory, chaos theory, and other explanations of the properties of organisms, social systems, and ecosystems. Capra’s surprising findings stand in stark contrast to accepted paradigms of mechanism and Darwinism and provide an extraordinary new foundation for ecological policies that will allow us to build and sustain communities without diminishing the opportunities for future generations.”
Cradle to Cradle: Remaking the Way We Make Things, by William McDonough and Michael Braungart. An excellent general introduction to smart design and life cycle analysis that advocates for both prosperity and sustainability. “…the authors present a manifesto calling for a new industrial revolution, one that would render both traditional manufacturing and traditional environmentalism obsolete. The authors, an architect and a chemist, want to eliminate the concept of waste altogether, while preserving commerce and allowing for human nature.”
The Omnivore’s Dilemma by Michael Pollan. A highly-readable & engaging study of the vast, interconnected, and interdependent systems of agriculture, energy, and the journey of food to our plate.
Systems Science, a blog series by George Mobus. Scroll down (and go back a page) to start at “Systems Science, Part 1.” Mobus provides a good overview of systems theory.
Finally, just start training yourself to look beyond the visible, to follow connections, and to think in more holistic terms when considering the larger interconnections at play in all domains. Consider, for example, all of the machines, organizations, people, and processes that contributed to your dinner tonight. Nothing is as simple as it seems yet, often, there are very simple rules underlying their complexity.
In addition to the number of frameworks and ideas, and the density of the interconnections among them, there was a strong normative quality to the material and its presentation. “If one hopes to make any progress at all,” we were told, “you need to both understand and accept these related ideas.”
This particular version of systems thinking is not unusual in this respect. Peter Senge’s 1990 edition of The Fifth Discipline describes one manager’s reaction to a five-day introductory workshop on his approach, which among other things, requires growing comfortable with eight archetypes: “It reminds me of when I first studied calculus (p. x).” Systems dynamics, the Soft Systems Method and other approaches face similar concerns.
Each of systems thinking’s various manifestations demands some degree of subscription to an orthodoxy (a particular view of just what systems thinking is). And each requires that the user master a large number of related ideas and techniques, most of which are not particularly useful on their own.