Chapter 3. Evo Devo Foresight: Unpredictable and Predictable Futures

A Meta-Darwinian Model

The evo devo model is a meta-Darwinian hypothesis of universal change. 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 contingent and intelligent interaction that occurs between complex systems in the environment. In the RVISC mnemonic, evolutionary process is best understood as both random Variation and contingent Interaction, both preconditions for selection, and we color it green.  Selection in the evo devo model is predominantly evolutionary selection, (recall the 95/5 rule), but there is always also a small amount of developmental selection, steering adaptive systems toward future replication. Unlike unpredictable and divergent evolutionary selection, developmental selection works in a convergent and predictable manner. Both types of selection appear equally important to protecting adaptive systems. As selection is both an evolutionary and a developmental process, we color it purple, to make clear that it is 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. Developmental process is represented as Replication and Convergence in the RVISC mnemonic). 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. Development in living systems is a small subset of Converging and Replication-protecting processes (recall the 95/5 rule), which 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.
  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 to replication, but to the production of adapted information, computation, order, complexity, or intelligence. We need an intelligence-centric view of our universe, something at least partly like evo devo CNS-I, if we are going to understand how our universe really works.

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.

In this meta-Darwinian model, Darwinian evolution is the best approximate base from which to construct better models of universal complexity. This perspective is often called universal Darwinism. As the extensive Wikipedia page on universal Darwinism shows, a number of scholars have extended Darwinian thinking beyond biology to psychology, culture, economics, and the evolution of sciences and technology.

As we’ve proposed in the 95/5 rule, the Darwinian perspective of variation, selection, and inheritance will in general explain 95% of what we see. But if we are in an evo devo universe, the developmental 5%, which is harder to model and uncover, will turn out to be roughly equally as important to understanding the future, as development is a framework that opposes and constrains all evolutionary process. Development guides us to predictable, future-specific form and function.

If we live in an evo devo universe, here are two equivalent cartoon equations to keep in mind:

Universal Darwinism = Universal Evolution (95%) + Universal Development (5%)

Natural Selection = Evolutionary Selection (95%) + Developmental Selection (5%).

The vast majority of Universal Darwinists all see the idea of multiscale, multisystem evolution (in the Darwinian sense of this word), but most presently do not see, or admit, the idea of multiscale, multisystem development. Thus they need to see developmental selection operating in psychology, culture, technology, and apparently, the universe itself. This is a great are where they can improve their models in coming years.

For example, Henry Plotkin’s excellent and pioneering Darwin Machines and the Nature of Knowledge (1997) on evolutionary psychology, describes how all of human and animal culture, from animal instinct to the emergence of higher intellect can be understood as a selective Darwinian process. Plotkin uses the idea of a Darwin machine, a term coined in 1987 by neuroscientist William H. Calvin in The brain as a Darwin machine. Nature 330:33-34, to describe any machine that, like a Turing machine, runs a replicative, iterative process to compute, but rather than using logic as in Turing machines, Darwin machines use rounds of variation, selection, and inheritance, or, as we would say in evo devo language, an RVISC cycle. Plotkin’s update, Evolutionary Worlds Without End (2010) is also a good read on cultural evolution, but not as clear his original. Plotkin doesn’t cover universal, physical chemical, and technical evolution, so perhaps he isn’t a universal Darwinist. But by extending Darwinian selection to include knowledge and gene-culture coevolution, he is among those who have made a major contribution.

In my opinion, Darwin machines, in their evo devo form, are a far more physically and informationally grounded models of how complexity emerges in our universe than Turing machines. Turing machines have been very helpful for advancing our theory of machine computation, which until the recent rise of deep learning and other connectionist algorithms, was entirely based on sequential logic and true/false Boolean algebra. But nature uses far more kinds of logic than this. There is a logic to all systems, and some of that logic is so simple it can be formalized by maths comprehensible to human minds, but the logic of evo devo systems, like its algorithms, often does not reduce to simple equations or rules that humans can easily understand. It is highly connectionist, iterative, hierarchical, informationally abstract, and approximate. See Valiant’s Probably, Approximately Correct (2014) for some of our current thinking on the kinds of algorithms and logic that nature uses.

Books like Plotkin’s, and Gary Cziko’s Without Miracles: Universal Selection Theory and the 2nd Darwinian Revolution (1997) do an excellent job showing that mostly-random selection operates at every scale and in every complex system we know. But they focus on the 95%, and deny the 5% of directional, developmental change. Cziko, for example, denies the existence of directional selection in bacteria, seeing 100% contingency and randomness. In the language of evo devo, Cziko is a “universal evolutionist”. This helps us see the central role of selection in making every complex thing adaptive, but it remains an incomplete model.

No one has yet written, to my knowledge, a scholarly work that shows the perennial balance between unpredictable and predictable adaptive change all replicating complex adaptive systems. Books like Peter Kinnon’s The Intricacy Generator (2014) are a nice start in that direction, but we’ll need much more scholarship along those lines before universal Darwinism, in its evo devo form, becomes widely understood and accepted.

We started the Evo Devo Universe research and discussion community in 2008 to try to rectify this problem. Among other goals, we hope to help Universal Darwinists to engage with both evolutionary and developmental aspects of the universal Darwin machine, in all replicating complex systems.

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.

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