Chapter 11. Evo Devo Foresight: Unpredictable and Predictable Futures

The VCRIS Model of Natural Selection: Evolutionary Development of Adaptive Complexity

For an academic discussion of this model, please see my article: Evolutionary Development: A Universal Perspective, 2018.

Let’s look now at the VCRIS (“Vee-Kriss”) model of natural selection via evolutionary development. Virtually every interesting complex adaptive system we know of within our universe, including solar systems and their planets replicating in our universe, cyclic geophysical and atmospheric processes maintaining themselves on Earth, organisms replicating in our environment, ideas replicating in brains, and technological systems replicating in human culture, use mechanisms of Variation to generate experimental diversity, Convergence on a subset of future forms and function, and use the processes of ReplicationInheritance, and Selection to build their adaptive complexity and intelligence.

We can call this a VCRIS cycle. We can call it a cycle as it centrally includes replication, but these five processes are not sequential steps in a cycle, but instead occur in parallel simultaneously, often in different parts of the same system. For example, as you are maturing to an adult, parts of your body and mind are getting ready for or are already engaged in replication (of your genes, your ideas, your behaviors), parts of you are a product of your inheritance (genes, family conditions, ideas), and of environmental selection (on your thoughts, feelings, behaviors, and organism), parts of you varying (creating), driven to find things and information that is truly different and new, and parts you are converging on a variety of future structures, physical and mental, as you develop. Here is a graphical depiction of the model (picture right).

One of the unique benefits of the VCRIS model, and of evo devo thinking in general, is that it requires us to pay attention both to the things that are likely to change, cycle by cycle, and the things that are likely to stay the same. In the VCRIS model, physical and informational processes that change over time, to generate, maintain, and manage Variety, are in fundamental tension and opposition with physical and informational processes that do not change over time, and thus generate, maintain, and manage Convergence. I propose these two processes are the “root perspectives” in any model of infodynamic change in complex systems, and thus V and C are the first two terms in the VCRIS model.

Development, as any physicist might say, is the opposite of evolutionary process. It is convergent, diversity-reducing, and predictable, at least in principle. To treat development with the seriousness it deserves, we need a new term to understand the nature of selection, a term that juxtaposes these two fundamental binaries, those things that change, and those that stay the same. “Unpredictable predictable” is a term a physicist might favor, and evolutionary development (evo devo) is a good general term, in my view. Use of the evo devo term also communicates our humility and ignorance when we are asked whether evolutionary or developmental process are presently dominating in any system or environment. We usually don’t know which processes are most in control of either physical or informational dynamics, at first glance. Careful study, modeling, and data collection are often required to see where any complex system is presently headed, process by process.

The VRISC Model of Self-Organization (Evolutionary Development)

The VCRIS Model of Natural Selection via Evolutionary Development

Recall that standard evolutionary theory, as first described by Darwin, is often simplified to “Variation, Inheritance, and Selection” over long periods of Time, summarized as the VIST acronym. Historically, this approach treated all Inheritance as an evolutionary process. It took the emergence of evo-devo biologists in the 1990s to remind us that it is critical to recognize that certain types of inheritance (developmental genes and factors) vary far less in space and time than others (evolutionary genes and factors) with respect to the organism. The VIST model also ignores Convergence at the level of the environment, which is perhaps its most serious limitation. Standard evolutionary theory, applied to humans, or any other particularly complex, intelligent system, does not ask or recognize that processes of ecological, cultural and technological development are fundamental inputs to selection.

A developmental approach adds Convergence (to environmental optimality, and to allow future replication), to the process of Variation, offering us two equally fundamental ways to understand long-range change. We can also use the evo devo perspective to understand a long-used term in the complexity literature, self-organization. A self-organizing system is not only evolutionary, it is engaging in some form of development. It is the hidden developmental component of system change that make any system appear to be self-organizing. Cut up a virus in a petri dish, and it “self-organizes” back into virus. It does so because those molecules have engaged in many prior evo devo cycles. They’ve become tuned to use metastable features of the universal environment. All self-organization, or “order that apparently is free”, happens because a system, its seeds, and its environment have been involved in past replication.

At the level of the environment, this convergence process is called convergent evolution by Darwinists, but it is better understood as ecosystem development, biogeographic development, cultural development, technological development, planetary development, and in the broadest analysis, universal development, as we have described.

In an evo devo universe both universal evolution and universal development are simultaneously occurring. Darwin’s Inheritance factor (the Seed) is split in the EDU model between varying inherited characteristics (the vast majority of genes, in the 95/5 rule of genetics), which we consider under Variation, and stable inherited characteristics (developmental genes and factors) which we consider under Convergence. Both are inputs to Replication (Organism form and life cycle).

Environmental Selection, in turn, is also both an evolutionary and developmental process, and we color it purple to indicate that it is a hybrid of both evo and devo processes, along with the Replicator (Organism) and its mechanisms of Inheritance (Seed). Evolutionary selection creates unpredictable variation (divergence), replicators running adaptive experiments, while developmental selection converges predictably on future form and function that will protect the replicator and the replication process. Both kinds of natural selection are necessary for survival of the replicator in a complex and often hostile world.

A Meta-Darwinian Model

The evo devo model is a meta-Darwinian hypothesis of the dynamics that drive selection, and determine the nature of adapted complexity. It begins with Neo-Darwinism as an acknowledged base, and attempts to make an extended evolutionary synthesis, incorporating the rest of the six schools. Thus it incorporates yet goes beyond our modern evolutionary synthesis (popularly called Darwinism) in considering the future of living systems. It applies evolutionary, developmental, and adaptive thinking to other replicating systems that we don’t traditionally think of as acting similarly to organisms, including chemical systems, societies, technologies, and the universe itself.

As it is a meta-Darwinian model, the evo devo model redefines the words evolution, development, and adaptation in ways that differ just a bit from standard evolutionary theory, as follows:

  1. In standard evolutionary theory, evolution is a word used to describe all biological change, including inheritance, variation, selection, and adaptation. In our evo devo model, evolution is the processes of variation of parameters (novelty creation) and the interaction and selection that occurs between complex systems in the environment. But it is primarily unpredictable variation, diversification, and experimentation that represent evolutionary process. Selection, as we will see, is an evo devo process, a mix of both.
  2. In standard evolutionary theory, development is a word used only to describe inheritance and replication in individual organisms. It is rarely applied to ecosystems, and never to life as a system, or to the universe as a system. In the evo devo model, development includes inheritance, replication, and the predictably convergent and hierarchical life cycle. Development is the set of all processes that have high probability of occurring in any replicating system, based on the historically stable conditions and constraints of the environment, and system’s own inherited complexity. These Converging processes act in opposition to the diversity-generating Variation of evolutionary process.
  3. In standard evolutionary theory, natural selection (adaptation) is an intrinsically contingent and unpredictable evolutionary process. In an evo devo model, natural selection (adaption, evolutionary development) is a blend of both evolutionary novelty and variety and developmental convergence and conservation. Adaptation is thus a partially unpredictable and partially predictable “evo devo” process in replicating systems at all scales. Thus we color it purple, to make clear that it is a mix of both.
  4. In standard evolutionary theory, theorists talk about “selection for replication.” The selfish gene/selfish replicator is the standard model. In an evo devo model, this is an incorrect framework. Evolutionary variation and developmental replication are both working “for” something else—adaptive information, computation, order, complexity, or intelligence. In other words, conventional Darwinism is still missing an adaptive information theory. Consider how many different ways the universe uses replication. There are developmental genes, which are high-fidelity replicated, to conserve the information that has been accumulated, and protect the life cycle. In tension with these are a much larger set of evolutionary genes, constantly reassorting and mutating, to create new information, and generate variety. There is also a vast range in the timescale of replicators, from bacteria to Cicadas (which hide out for 13 years between replications) all the way up to the universe itself as a replicator. There are also a large number of different selection processes operating simultaneously, including natural, sexual, kin, group, developmental, and other forms. There are also a great variety of variation-producing mechanisms. Thus it seems more accurate to say that variation, replication, and selection are fundamental informational-computational mechanisms in service to something else. Not in service to replication, but to the production of adapted information, computation, order, complexity, or intelligence. We need an intelligence-centric view of our universe, the ability to understand how selection, under the right conditions, generates intelligence, a model we refer to as evo devo CNS-I, if we seek to understand how our universe really works.

Many biologists today would argue that evolutionary process is a primarily contingent, diversity generating, and increasingly contingent and unpredictable process. So it is a small change in definition for us to restrict the term evolution to only such processes, in living and nonliving systems. Many evolutionary biologists might not like that restriction, but from my perspective, evolutionary biology today offers a view of life and selection that is dangerously incomplete. It has long neglected the physical and informational roles of development, particularly with respect to the selective environment. Fortunately, evo-devo biology is helping to rehabilitate development as a process in living systems, but to understand selection, we must also consider development at universal scales. Nowhere is this more obvious than in human civilization, which has many poorly characterized developmental processes, some of which we discuss in this chapter and in our chapter on acceleration, which in turn must broadly influence selection.

In complex systems, we can clearly see both evolutionary selection (what Darwinists call “natural selection”) and developmental selection (guiding complex systems through developmental processes) operating in all biological organisms. Developmental selection is conservative, funneling and optimizing. Evolutionary selection is experimental, diversifying, and contingent, as we have defined. These are two very different types of selection, and both are “natural” inside replicating organisms.

Thus, using our own slightly altered definitions of evolution and development offered in A Meta-Darwinian Model, we can identify evolutionary, developmental, and evo devo features in replicating complex systems at virtually every scale.

A few of countless examples of varying, converging, replicating, inheriting, and selecting,  (VCRIS) complex systems include:

  • Stars, which have advanced from the primitive Population III stars to the far more complex Population I solar systems, like our Sun and its complex rocky planets, over galactic time.
  • Cyclic geophysical and geoatmospheric processes, like plate tectonics, carbon and nitrogen cycles, and weather, maintaining a stable distribution of environmental conditions.
  • Prebiotic chemicals, which have built up their complexity in these special solar and geophysical systems to create cells, over billions of years.
  • Cells, which created multicellular life with nervous systems, again over billions of years.
  • Biogeohomeostatic processes in which Earth’s life self-regulates its environment maintain environmental conditions conducive to life (eg., some rigorous subset of the Gaia hypothesis)
  • Nervous systems, which went from the Cambrian explosion to hominids, over roughly 500 million years.
  • Languages, ideas, and behaviors in hominid brains which birthed nonbiological computing systems, over roughly 5 million years.
  • Computing and robotics systems, whose replication is presently aided by human culture, may soon (within the next few decades, it seems) be able to replicate, evolve, and develop autonomously, bringing an even more complex adaptive system to “life”.

Identifying the VCRIS life cycle of any replicative system, whether it be chemicals in a dish, stars in the universe, species on Earth, ideas and behaviors in brains and bodies, or technologies in societies, can tell us quite a lot about its future, independent of its adaptive environment.

This replication-centric view of the universe doesn’t fit every complex adaptive system. For example critics have pointed out that Galaxies, and the Universe itself, have not replicated over the last 13 billion years. That is an important point.

But since it is easy to argue that nearly every other interesting complex system in the universe has undergone some form of variation, replication, inheritance, selection, and convergence to build their complexity, it is parsimonious (conceptually the simplest theoretical model) to suspect this is how both galaxies and the universe built up their own adaptive internal complexity as well, via a long chain of prior replications in a hypothetical environment that physicists call the multiverse.

We can also ask another question: adaptation for what purpose? To what extent can we understand adaptation in biological evo devo as a teleological process (driven by evolutionary and developmental “goals” or “ends”) and apply this insight to our universe as a potentially evo devo system?

Like living organisms, our universe may have a developmental life cycle.

Like living organisms, our universe may have a developmental life cycle.

This brings us to the work of physicists like Lee Smolin, who presents evidence and argument in The Life of the Cosmos (1999) that our universe may be chained to a developmental life cycle, engaged in a process he calls Cosmological Natural Selection, with black holes acting as the replication environments. Smolin’s model has stood up to a number of criticisms since. But whether Smolin’s or other cyclic models in cosmology are ultimately validated is perhaps less important, at this stage in our science, than the observation that our universe looks like it is engaged in a VCRIS life cycle, like all the other interesting complex systems within it.

We now think our universe had a definite birth (a Big Bang, 13.7 billion years ago) and it has passed through several developmental stages of growth, one of which may well be, according to astrobiologists, the development of life throughout the universe, with high probability. See Darling’s Life Everywhere (2007) for some estimates of how broadly life may exist in our universe. A growing number of scientists now propose that the creation of intelligent life is another of these developmental stages, either highly probable or inevitable on Earth-like planets.

We’ve also known for roughly 160 years that our universe must eventually die a “heat death”. The second law of thermodynamics, on which the heat death concept is based, is one of the most fundamental and widely validated laws of physics. See Adams’ The Five Ages of the Universe (2000) for a variety of speculations on how our universe will die. As our universe grows islands of accelerating local order and intelligence in a sea of ever-increasing entropy, thermodynamics tells us this process cannot continue forever. The universe’s “body” is aging, and will end in heat death, or perhaps even earlier in a big rip, or some similar fate. But if our universe is also a replicating complex adaptive system that engages in both evolution and development, as it grows older it must package its intelligence into some kind of reproductive system, a key feature of development, so that its complexity can survive its inevitable systemic death and begin again.

Perhaps the process that remains most obscure at present is how the universe converges on Replication, and what role intelligence, and future human civilizations, might play in that replication. Complexity scholar James Gardner offers one hypothetical model for that in his book Biocosm (2003). I offer another in Evo Devo Universe? (2008). While it is too early to know which if any of these models are more likely, the idea that the universe is a replicating system, and that its past replication explains a good deal of its internal complexity, and that one key role of intelligence is to have a positive influence on the replication of the universe are all increasingly popular ideas that need better scientific exploration.

This brings us to the concept of self-organization, which can be defined as a process of development that happens to complex systems and their environment as they go through multiple replicating cycles to build up adaptive information. In evo-devo biology, and in an evo devo universe, any physical system that has both evolutionary (variation, experimentation) and developmental (replication, convergence) features, and operates in a selective environment, will self-organize its own adaptive complexity as its replication proceeds.

A textbook example of self-organization is what happens to the molecules of a virus, or many supramolecular assemblies taken from inside cells, when you cut them up and place them in a petri dish. We are surprised to see these molecules partly self-assemble again “on their own” (or “by themselves”), with “no apparent help” from us. This self-organization happens only because the shapes and charges of these disaggregated molecules exploit the persistent physical laws of their environment to re-assemble historical form and function, which is encoded in the information of their present structure. They learned and internalized this evolutionary developmental information, as special shape-charge relationships, over countless past VCRIS cycles. They also tuned a lot of that information into their genes, which express that information as three dimensional proteins in the cell, in a way that is developmentally robust to the noisy and chaotic conditions in typical cellular aqueous environments.

In exactly the same manner, if we live in an evo devo universe, certain physical and informational processes happening around us will not just evolve, they will self-organize, or engage in evolutionary development. Because of many past cyclings of our universe in a multiverse, certain ordering processes are implicit in our universe’s “genes” (fundamental parameters and other initial conditions, symmetries, and boundary conditions) and the surrounding metastable multiversal environment, so these processes don’t just evolve, they also develop.

Is this model at least very roughly correct? Do these three categories—evolution, development, and adaptation as we have defined them—usefully “carve nature at its joints”, as Plato said all good models must do? Time will tell. If our universe uses evolution and development as basic ways of creating adaptation in all replicative systems, this will be verified by our future science and simulation abilities, which are fortunately growing at rapid exponential rates.

The Principle of Parsimony: Occam’s Razor

Some will say “The evo devo model is not parsimonious,”, meaning that it is not based on as few assumptions as are necessary to explain universal events. They may say it assumes more about how the universe operates than is needed, unlike standard evolutionary theory.” Here I must disagree.image023

Yes, the model is more complex and constraining than standard evolutionary theory, but this additional complexity allows us to understand important things that are otherwise unexplainable, such as the regularity of accelerating change, the fine tuning problem, convergence, hierarchy, and why the universe is so homogeneous not only in lower but also in its higher hierarchies of complexity.

We now have evidence that not only living things, but stars, prebiotic chemistry, behaviors and ideas in brains, technologies and algorithms in society, and even the universe itself appear to be replicative systems, engaged in a life cycle. To a systems theorist, who sees both evolutionary and developmental features in all known replicative complex adaptive systems, it is most parsimonious to assume that the universe itself is such a system.

As living systems appear to have generated their vast adapted complexity via a long chain of evo devo replications, I find it extraordinary to claim that the universe was capable of generating its own internal adaptive complexity via any other mechanism than evo devo replication. So the question of parsimony depends on what frame we use to define simplicity, and what features of the universe we think our theories of change must minimally be able to explain.

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Table of Contents


Chapter 2. Personal Foresight – Becoming an Effective Self-Leader

Chapter 2: Personal Foresight

Becoming an Effective Self-Leader

Chapter 4. Models – Foundations for Organizational Foresight

Chapter 4: Models

Foundations for Organizational Foresight

Chapter 7. Acceleration – Guiding Our Extraordinary Future

Chapter 7: Acceleration

Guiding Our Extraordinary Future (In Process)

II. Global Progress: 5 Goals, 10 Values, Many Trends

Innovation: Our Abundant Future
Intelligence: Our Augmented Future
Interdependence: Our Civil Future
Immunity: Our Protected Future
Sustainability: Our Rebalanced Future

III. Universal Accelerating Change

Great Race to Inner Space: Our Surprising Future
Entropy&Information: We’re Running Down & Up
The Puzzle of Meaning: We Have No Einstein Yet
Trees, Funnels & Landscapes: Intro to Evo Devo
Big Picture Change: Five Scales of Accelerating ED
Transcension Hypothesis: Where Acceleratn Ends?
IDABDAK: Social Response to Accel & Developmnt
We’re On a Runaway Train: Being Accelaware

IV. Evo Devo and Exponential Foresight

Seeing It All: Accel., Diverg, Adapt, Convrg, Decel.
Natural (I4S) Innovation: The Evolutionary Drive
Natural (I4S) Intelligence: The Human-AI Partnership
Natural (I4S) Morality: Why Empathy and Ethics Rule
Natural (I4S) Security: Strength from Disruption
Natural (I4S) Sustainability: The Developmental Drive
S-Curves: Managing the Four Constituencies
Pain to Gain: Traversing the Three Kuznets Phases
Hype to Reality: Beyond Hype Cycles to Reality Checks
Exponentials Database: Measuring Accelerations
TINA Trends: Societal Evolutionary Development
Managing Change: STEEPCOP Events, Probs, Ideas
A Great Shift: A Survival to a Sentient Economy

V. Evo Devo and Exponential Activism

Building Protopias: Five Goals of Social Progress
Normative Foresight: Ten Values of Society
Top & STEEPCOP Acceleratns: Positive & Negative
Dystopias, Risks, and Failure States
Three Levels of Activism: People, Tech & Universe
A Great Opportunity: Exponential Empowerment


Chapter 8. Your Digital Self – The Human Face of the Coming Singularity

Chapter 8: Your Digital Self

The Human Face of the Coming Singularity (In Process)

I. Your Personal AI (PAI): Your Digital Self

Digital Society: Data, Mediation, and Agents
Personal AIs: Advancing the Five Goals
PAI Innovation: Abundance and Diversity
PAI Intelligence: Bio-Inspired AI
PAI Morality: Selection and Groupnets
PAI Security: Safe Learning Agents
PAI Sustainability: Science and Balance
The Human Face of the Coming Singularity

II. PAI Protopias & Dystopias in 8 Domains

1. Personal Agents: News, Ent., Education
2. Social Agents: Relat. and Social Justice
3. Political Agents :  Activism & Represent.
4. Economic Agents:  Retail, Finance, Entrep
5. Builder Agents :  Work, Innov. & Science
6. Environ. Agents : Pop. and Sustainability
7. Health Agents :  Health, Wellness, Death
8. Security Agents :  Def., Crime, Corrections

III. PAI Activism & Exponential Empowerment

Next Government: PAIs, Groupnets, Democ.
Next Economy: Creat. Destr. & Basic Income
Next Society: PAI Ent., Mortality & Uploading
What Will Your PAI Contribution Be?

Chapter 10. Startup Ideas – Great Product & Service Challenges for Entrepreneurs

Chapter 10: Startup Ideas

Great Product and Service Challenges for Entrepreneurs (In Process)

I. 4U’s Idea Hub: Building Better Futures

Air Deliveries and Air Taxis: Finally Solving Urban Gridlock
Ballistic Shields and Gun Control: Protecting Us All from Lone Shooters
Bioinspiration Wiki: Biomimetics and Bio-Inspired Design
Brain Preservation Services: Memory and Mortality Redefined
Carcams: Document Thieves, Bad Driving, and Bad Behavior
Competition in Govt Services: Less Corruption, More Innovation
Computer Adaptive Education (CAE): Better Learning and Training
Conversational Deep Learning Devsuites: Millions of AI Coders
Digital Tables: Telepresence, Games, Entertainment & Education
Dynaships: Sustainable Low-Speed Cargo Shipping
Electromagnetic Suspension: Nausea-Free Working & Reading in Cars
Epigenetic Health Tests: Cellular Aging, Bad Diet, Body Abuse Feedback
Fireline Explosives and Ember Drones: Next-Gen Fire Control
Global English: Empowering the Next Generation of Global Youth
Greenbots: Drone Seeders and Robotic Waterers for Mass Regreening
High-Density Housing and Zoning: Making Our Cities Affordable Again
Highway Enclosures and Trail Networks: Green and Quiet Urban Space
Inflatable Packaging: Faster and Greener Shipping and Returns
Internet of Families: Connecting People Over Things
Kidcams: Next-Gen Security for Child Safety and Empowerment
Kidpods: Indoor & Outdoor Parent-Assistive Toyboxes
Microdesalination: Democratizing Sustainable Fresh Water Production
Noise Monitors: Documenting and Reducing Noise Pollution
Oceanside Baths: Sustainable Year Round Beach Enjoyment
Open Blood Scanners: DIY Citizen Health Care Sensor Tech
Open Streaming Radio: User-Centered Audio Creation and Rating
Open Streaming Video: User-Centered Video Creation and Rating
Open Values Filters: Social Rankers, Arg. Mappers, and Consensus Finders
Personal AIs: Your Private Advisor, Activist, and Interface to the World
Pet Empowerment: Next-Gen Rights and Abilities for Our Domestic Animals
Safe Closets: Fire-, Earthquake-, and Intruder-Proof Retreat Spaces
Safe Cars: Reducing Our Insane 1.3M Annual Auto Deaths Today
Safe Motorcycles: Lane Splitting in Gridlock Without Risk of Death
Shared Value Insurance: User-Centered Risk Reduction Services
Sleeperbuses and Microhotels: Demonetized Intercity Travel
Space-Based Solar Power: Stratellite Powering and Weather Management
Stratellites: Next-Gen Urban Broadband, Transparency, and Security
Touch DNA: Next-Gen Home Security and Crime Deterrence
View Towers: Improving Urban Walkability, Inspiration, and Community

Chapter 11. Evo Devo Foresight – Unpredictable and Predictable Futures

Chapter 11: Evo Devo Foresight

Unpredictable and Predictable Futures

Appendix 1. Peer Advice – Building a Successful Foresight Practice