Three Universal Processes
The Evo Devo model proposes we can identify three basic processes of change that operate in replicating biological, societal, technological and universal systems:
- Evolutionary processes that generate novelty and variety in a system over time. These processes are largely unpredictable, except that they add more variety to the environment over time. Graphically, evolutionary processes look like trees, with increasing branches and interactions over time. For Examples, think of Darwin’s phylogenetic tree (“tree of life”), the way living systems create new varieties and species
of offspring. Physically, evolutionary processes generate branching novelty and variety in ways that are contingent and unpredictable. For the universe, think of quantum mechanics (branching changes based on observation), nonlinear dynamics that may branch into to “chaos”, and high-energy physics (symmetry-breaking in the early universe). For human societies, think of all the varieties of human subcultures, and all the unique new ideas, products, services, and behaviors we create every year. Mathematically, there are many early models for novelty-generating branching processes. Stochastics, combinatorics, and diffusion-limited aggregation are among our current tools and models. Exponential growth, scale-free networks, and fractals are common patterns seen in such processes. See Ball’s Branches (2011) for one account. Modeling the emergence of new ideas, technologies and businesses in the marketplace is very much in its infancy. Rogers’ Diffusion of Innovations (2005), Christensen’s The Innovator’s DNA (2011), Sawyer’s Explaining Creativity: The Science of Human Innovation (2012), and North’s Novelty: A History of the New (2013), are a few good books for foresight professionals who want to get better at understanding, generating, and managing novelty and variety in their practice.
- Developmental processes that conserve and converge a system over time. These processes create predictable future states. Graphically, developmental processes look like funnels, guiding the system to one particular set of future states. For examples, think of the energy landscape of protein folding (picture right) which funnels an astronomical number of possible 3D protein sequences into a few reliable shape-charge assemblies, over and over again in the cell. Think next of how biological development creates genetically-identical twins, which are funneled so similarly to their future states by developmental processes that you cannot tell them apart from across the room. Think also of predictable stages of psychological development. Think of the many predictable ways that economies, societies, and
technologies develop. Physically, developmental processes conserve and converge (“funnel”) complex systems toward probabilistically predictable future states. For the universe, think of the laws of classical mechanics (which determine the far future motions of planets), relativity (determining the emergence of black holes), and thermodynamics (determining an irreversible increase in entropy for the entire system). For human societies, think of any general, predictable patterns we see in social, economic, and technical development. Mathematically, processes of development are even less understood than novelty creation. Reaction-diffusion systems exponential decay, power laws, and learning curves are among our useful models. Normal and log-normal distributions (as in Gibrat’s law for the log-normal development rate of organizations, and cities) are among the regular patterns seen in development. Think of the normal distribution of IQ or height in a developing organism. See Developmental Bio: A Very Short Intro (2011), for what we know today about biological development. Social and economic development are large fields with simple models, and technological development is a small corner of science and technology studies. See Wright’s Nonzero (2001), Morris’s Why The West Rules, For Now (2011), and Pinker’s The Better Angels of our Nature (2012) for a few very good examples of predictable global patterns of social, economic, and technological development.
- Evo Devo or Adaptive processes that combine evolution and development, and involve competition and cooperation between systems involved in a life cycle (birth, growth, replication, and death), and try to adapt to their environment. Such systems are subject to natural selection, a process regulated by both evolution and development. Graphically, their changes can be drawn as selection peaks and valleys on an adaptive landscape, as in Wright’s evolutionary landscapes. Multiple adaptive peaks
representing competing or cooperating systems may merge, split into more peaks, or rise or fall in adaptation, depending on their changing abilities and the selective environment. Physically, the “complex adaptive systems” that engage in evo devo processes can show branching, funneling, cycling, accelerating, decelerating, self-organized criticality, and other complex behaviors, depending on where they are in their life cycle, and what else is happening in their environment. All such systems are “dissipative structures,” which means they maintain a resilient adaptive state using energy flows, in a far-from-equilibrium condition. For examples, think of any replicating, varying, and interacting systems, including replicating stars and prelife chemistry in the universe, replicating organisms on Earth, ideas that replicate in and between brains (“memes”), and technology applications and algorithms that replicate in economies (“temes”). Mathematically, S-curves, predator-prey, and game theory interactions are some of many patterns we see in such systems. Carroll’s Endless Forms Most Beautiful (2006) and Laubichler’s, From Embryology to Evo-Devo (2009) are good intros to evo-devo biology. To understand how both life and our universe seem to balance the use of both evolution and development to create adaptation, we must today go to systems theorists. Some leading meta-Darwinian models for living and universal systems include Wesson’s Beyond Natural Selection (1991), Salthe’s Development and Evolution (1993), Kauffman’s At Home in the Universe (1996), Denton’s Nature’s Destiny (1998), Smolin’s The Life of the Cosmos (1999), Conway Morris’s Life’s Solution (2005), Corning’s Holistic Darwinism (2005), Ried’s Biological Emergences (2011), McGhee’s Convergent Evolution (2011), and Pross’s What is Life? (2012). For more on how memes and temes compete and cooperate in society, see Wright’s Nonzero (2000), Aunger’s The Electric Meme (2002), Brandenberger’s Co-opetition (1997), and Kelly’s excellent What Technology Wants (2011).
Again, we see the model and its three graphical aids (trees, funnels, and selection peaks) in the diagram below right. For foresight professionals, the key takeaways from this graphic is that our world is made up of a mix of unpredictable, tree-like, and predictable, funnel-like processes that interact to create the adaptive landscapes (preference maps) we observe all around us.
We understand the world as a privileged set of competing and cooperating peaks (high fitness configurations) and a minefield of threatening valleys (low fitness configurations). As foresight professionals, it is our job to continually track and rebuild useful preference maps, and to help our clients find and steer toward the peaks while avoiding the valleys. Adapting well is a worthy and ceaseless challenge, and is much easier discussed in abstract than done in reality. We wish you well in that work.
Recall that Aristotle (350 BCE) championed the universality of these three perspectives, in his model of human intellect as a mix of the theoretical, or truth-associated, the productive, or beauty-associated, and the practical, or goodness-associated categories of mind. The 95/5 rule lets us reorder Aristotle’s three values as “beauty, truth, and goodness” (evo, devo, evo devo). Beauty is aways far more plentiful, and much easier to see, than truth. Goodness, in turn, is always a judicious mix of both.
Evolution’s mandate is to unpredictably fan out into perennial new diversity and variety. It produces a natural world of astonishing beauty. Development’s mandate is to predictably funnel all this chaos to a small set of predictable futures, invariant truths, or structures and functions will emerge, at developmentally appropriate times, in all corners of the universe. Evo devo’s mandate is to combine these two processes to create local adaptiveness, some of which will turn out to be universally adaptive as well.
This is a good time to point out that evolutionary development is nothing like Aristotle’s scala naturae (Ladder of Nature, Great Chain of Being), model of life, where all the important processes are predestined by a Creator into a strict hierarchy of emergence. In the evo devo model, a 5% developmental framework of universal complexification is statistically
Nor is an evo devo universe a Newtonian or Laplacian “clockwork universe” model, which proposes total physical predetermination, though it is a model with some statistically clockwork-like features, including the timing of various hierarchical emergences over the universe’s lifespan and death, just as we see in biological development. Neither the Aristotelian nor Laplacian models of the universe are developmental (positing statistically predetermined emergence and lifecycles) but rather caricatures of it, one-sided models that allow no room or role for evolution.predetermined to emerge. But that framework says nothing about the creative 95% evolutionary painting itself, which is the bulk of the work of art. Recall the all-important differences in tissue microarchitecture and mental processes and life choices between two genetically (developmentally) identical twins. Evolution is as or more important to adaptiveness as development, and evolution is far more of what we see.
It appears that our universe is significantly more complex, intelligent, resilient, and interesting than any of these models suppose – it is predictable, constrained, and conservative in certain critical parts that are necessary for its function and replication, and it is intrinsically unpredictable and creative in all the rest of its parts. Furthermore, unpredictable evolution and predictable development may be constrained to work together in ways that maximize intelligence and adaptation, both for leading-edge systems, and for the universe as a system.Nor is an evo devo universe the random, deaf-and-dumb Blind Tinkerer that universal evolutionists like Richard Dawkins (The Blind Watchmaker, 1996) portray. Blind Tinkerer models misunderstand convergent evolution, and are as incomplete in describing universal change as neo-Darwinian theory is in describing biological change today.
If we live in an evo devo universe, it must be statistically near-impossible for Earth-like civilizations to not invent critical adaptive technologies like language, electricity, internal combustion engines, factories, computers, mobile phones, and soon, human-surpassing AI. But what is entirely within our choice is the path we take to and beyond each of these developmental destinations.
Evo devo models can be applied to the universe as a system, and to any of its replicating internal complex systems, including stars, molecules, organisms, behaviors, ideas, algorithms, and technologies. In an evo devo universe, our greatest moral responsibility lies both in foreseeing these predictable destinations (anticipation) and in creating (innovation) and choosing (management) good social, organizational, and personal paths among all the unpredictable futures in front of us.