Meta Evolution: fitness beyond reproduction

In the most general sense, evolution is any complex process that has some definable direction. There are three such trends on the highest ontological level: entropic equalization in physics, improving quality of reproduction in biology, and increasing predictive power in cognitive (psycho-social) systems. They are statistically irreversible within corresponding domain or system, and lower trends also apply in higher domains. I think these trends can be generalized into a meta-trend, defining transition or metaevolution from lower- to higher- complexity domains.

Many other observers (such as Ray Kurzweil) also see matter, life, and intelligence as phases in the evolution of the universe. But they use scale and complexity as a measure of progress. That presents a problem: galaxies are bigger than brains and nothing is more complex than random noise. Of course, they mean functional complexity, but neglect to clearly define what that function is.

Any system is defined by some relatively conserved core, such as genotype in biology. Propagation of that core is effective function of a system, which serves as a relatively fluid or adaptive “phenotype”. To be more effective, such phenotypes grow and functionally sub-differentiate, while the core becomes relatively smaller, isolated from environment, and less direct in controlling the system. Since only the core is ultimately conserved, I propose that direction in metaevolution is defined by the second trend.

In effect, environment or ecosystem differentiates into increasingly deep “conservation food chain”, with growing disparity between the most conserved cores and the fastest-adapting peripheral systems.
Competition between cores favors more broadly instrumental elements within each. This leads to evolution of more “abstract” cores, that define lesser proportion of their more “bottom-up” phenotypes.

For example, initial conserved cores in biology were autocatalyzing proteins and RNAs, later displaced by DNA genes, more flexible and coding for multiple and changing during phylogeny RNAs & proteins.

Superficially similar to my interpretation are The Major Transitions in Evolution and Meta-Systems Transition Theory. From John Stewart’s (hopelessly utopian) Evolution’s Arrow: “Two attributes that increase as evolution proceeds are the scale of cooperative organization and evolvability through the discovery of effective adaptations“. But pure cooperation is a product of group selection: a notoriously inefficient mechanism. In terms of conserved traits, what’s far more likely is preferential selection of a some common subset, while individual specifics become dispensable.

Hence, I focus on the evolution of increasingly refined/ abstracted conserved traits, though they do depend on correspondingly complex phenotypes. The later however is a cost, while core propagation is a benefit (net result) of this trend. These propositions are mostly tautological, but so are the concepts of thermodynamics, survival of the fittest, and algorithmic complexity theory, not to mention all of math.

My core types are conceptual and the transition between phases is gradual, with expanding overlaps:

Entropy growth: equalization and stabilization of matter and energy distribution across space-time for all interacting entities. Maximized fitness here is equality of distribution or continuous recurrence.
Biological evolution: restoration and reproduction of genomes by selective acquisition of their constituents. The fitness here is discontinuous recurrence: mediated by differentiated phenotype.
Cognitive exploration: recognition and projection of correspondence between inputs and predictions. The fitness is hierarchically projected match between environment and a model: cognitive phenotype.

Living organisms metabolize matter and energy to propagate their pattern (information), while cognitive systems “metabolize” patterns: learn and forget information, to increase their predictive power.  

Other posts here elaborate on each phase of core abstraction during “history of time".