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We have seen similar theoretical advances in the previous century. When classical physics, as powerful as it is, came to be understood as a subset of general relativity, we gained a theoretical framework with far greater long-range explanatory and predictive value. As evo-devo life scientists point the way to a new, meta-Darwinian synthesis in biological systems, with (intrinsically unpredictable) macroevolutionary and (statistically predictable) macrodevelopmental processes operating over almost four billion years of life on Earth, we may also gain insights into the nature and extent of quasi-evolutionary and quasi-developmental process at the universal scale.
 
We have seen similar theoretical advances in the previous century. When classical physics, as powerful as it is, came to be understood as a subset of general relativity, we gained a theoretical framework with far greater long-range explanatory and predictive value. As evo-devo life scientists point the way to a new, meta-Darwinian synthesis in biological systems, with (intrinsically unpredictable) macroevolutionary and (statistically predictable) macrodevelopmental processes operating over almost four billion years of life on Earth, we may also gain insights into the nature and extent of quasi-evolutionary and quasi-developmental process at the universal scale.
  
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Finally, hypotheses of universal evolutionary development must seek to understand the role and emergence of information, computation, and intelligence within the universe. As one facet of this search, we must learn to reconcile the two most fundamental approaches to modeling human cognition, [http://en.wikipedia.org/wiki/Connectionism connectionism] and [http://en.wikipedia.org/wiki/Computational_theory_of_mind computationalism]. Connectionist (neural network, associative) processes ('''James L. McClelland''', '''David E. Rumelhart''') seem clearly evolutionary, selectionist, and adaptive. For example, using evolutionary and developmental genetic programming techniques to specify the expression of artificial neural networks ('''Daniel Rivero''', '''Julián Dorado'''), allows environmental selection on the genotype of the expressed physical phenotype, just as in living systems. By contrast, computationalist (symbolic/logical/Bayesian) processes ('''Alan Turing''', '''Jerry Fodor''') seem likely to be a specially restricted and emergent subset of connectionist systems, appearing strongly only in higher mammals and their current primitive computing machines. Learning how to unify these two approaches, as in the [http://www.neural-symbolic.org/ neural-symbolic integration] agenda ('''Barbara Hammer''', '''Pascal Hitzler''', '''Marco Gori''') seems a necessary goal of future theory. Advances in neuroscience, mathematics and nonlinear science, information theory and complexity (algorithmic, computational, informational, and physical), and of course planetwide empirical and commercial engineering efforts all seem likely to play a role. Perhaps, at the end of this process, we may come to understand the universe itself as a computational entity, a contention championed in various forms by an impressive array of physicists in recent generations ('''Konrad Zuse, John A. Wheeler, David Deutch, Gregory Chaitin, Ed Fredkin, Stephen Wolfram, Seth Lloyd''').  
+
Finally, hypotheses of universal evolutionary development must seek to understand the role and emergence of information, computation, and intelligence within the universe. As one facet of this search, we must learn to reconcile the two most fundamental approaches to modeling human cognition, [http://en.wikipedia.org/wiki/Connectionism connectionism] and [http://en.wikipedia.org/wiki/Computational_theory_of_mind computationalism]. Connectionist (neural network, associative) processes ('''James L. McClelland''', '''David E. Rumelhart''') seem clearly evolutionary, selectionist, and adaptive. For example, using evolutionary and developmental genetic programming techniques to specify the expression of artificial neural networks ('''Daniel Rivero''', '''Julián Dorado'''), allows environmental selection on the genotype of the expressed physical phenotype, just as in living systems. By contrast, computationalist (symbolic/logical/Bayesian) processes ('''Alan Turing''', '''Jerry Fodor''') seem likely to be a specially restricted and emergent subset of connectionist systems, appearing strongly only in higher mammals and their current primitive computing machines. Learning how to unify these two approaches, as in the [http://www.neural-symbolic.org/ neural-symbolic integration] agenda ('''Barbara Hammer''', '''Pascal Hitzler''', '''Marco Gori''') seems a necessary goal of future theory. Advances in neuroscience, mathematics and nonlinear science, information theory and complexity (algorithmic, computational, informational, and physical), and of course planetwide empirical and commercial engineering efforts all seem likely to play a role. Perhaps, at the end of this process, we may even come to understand the universe itself as a computational entity, a contention that has been championed in various forms by an impressive array of physicists in recent generations ('''Konrad Zuse, John A. Wheeler, David Deutch, Gregory Chaitin, Ed Fredkin, Stephen Wolfram, Seth Lloyd''').  
  
 
Of particular interest to our near-term cultural future are questions in information technology growth and evolution. Many classes of technology, such as transportation or steel production, demonstrate a pattern of punctuated equilibria in their evolutionary development, with long periods of relative stasis. In contrast, a select subset of information, computation, and nanotechnologies have shown constant, rapid and historically unprecedented exponential capacity development over long spans of cultural time. As '''Gordon Moore''', '''Hans Moravec''', '''Ray Kurzweil''', '''William D. Nordhaus''' and others note, digital computers have doubled their price-performance ratios every one-and-a-half to three years, at least since the 1930's, while simultaneously migrating across mechanical, electromechanical, vacuum tube, transistor, and integrated circuit manufacturing paradigms. Are [http://www.metaverseroadmap.org/inputs.html#constants  Moore's law and a collection of related exponential technology capacity growth laws] part of a universal developmental process arising from some interaction between the physical structure of our universe and the value of computation at the 'leading edge' of evolutionary developmental adaptation? Or are these processes random consequences of some law of large numbers?  
 
Of particular interest to our near-term cultural future are questions in information technology growth and evolution. Many classes of technology, such as transportation or steel production, demonstrate a pattern of punctuated equilibria in their evolutionary development, with long periods of relative stasis. In contrast, a select subset of information, computation, and nanotechnologies have shown constant, rapid and historically unprecedented exponential capacity development over long spans of cultural time. As '''Gordon Moore''', '''Hans Moravec''', '''Ray Kurzweil''', '''William D. Nordhaus''' and others note, digital computers have doubled their price-performance ratios every one-and-a-half to three years, at least since the 1930's, while simultaneously migrating across mechanical, electromechanical, vacuum tube, transistor, and integrated circuit manufacturing paradigms. Are [http://www.metaverseroadmap.org/inputs.html#constants  Moore's law and a collection of related exponential technology capacity growth laws] part of a universal developmental process arising from some interaction between the physical structure of our universe and the value of computation at the 'leading edge' of evolutionary developmental adaptation? Or are these processes random consequences of some law of large numbers?  

Revision as of 21:51, 28 January 2009

“If life follows from [primordial] soup with causal dependability, the laws of nature encode a hidden subtext, a cosmic imperative, which tells them: “Make life!” And, through life, its by-products: mind, knowledge, understanding. It means that the laws of the universe have engineered their own comprehension. This is a breathtaking vision of nature, magnificent and uplifting in its majestic sweep. I hope it is correct. It would be wonderful if it were correct. ...if it is, it represents a shift in the scientific world-view as profound as that initiated by Copernicus and Darwin put together.” -- Paul Davies, The Fifth Miracle, 1999, Simon and Schuster, p 246.
I am suggesting that there may come a time when physics will be willing to learn from biology as biology has been willing to learn from physics, a time when physics will accept the endless diversity of nature as one of its central themes, just as biology has accepted the unity of the genetic coding apparatus as one of its central dogmas. -- Freeman Dyson, Infinite in All Directions, 1988, Harper, p 47.

Summary

Situation. The underlying paradigm for cosmology is theoretical physics. It has helped us understand much about universal space, time, energy, and matter, but does not presently connect strongly to the emergence of information, computation, life and mind. Fortunately, recent developments in cosmology, theoretical and evolutionary developmental biology, and the complexity sciences are providing complementary yet isolated ways to understand our universe within a broader ‘meta-Darwinian’ framework in which selectionist evolutionary and replicative, hierarchical developmental processes appear to generate complexity at multiple scales. The rigor, relevancy, and limits of an ‘evolutionary developmental’ approach to universal complexity remains an open and understudied domain of scientific and philosophical inquiry.

Course of Action. These results and hypotheses deserve to be explored, criticized, and analyzed by an international interdisciplinary research community ‘Evo Devo Universe (EDU)’. Where merited, they may lead to expanded conceptual framework that improves our understanding of both contingent evolutionary and convergent developmental complexity emergence in the universe.

Benefits/Results. If validated, such a framework promises to advance our understanding of both perennially chaotic and intrinsically predictable physical dynamics, and of evolutionary and developmental process at all scales, including the human scale. If falsified in any part, this endeavor will improve our critical thinking about the generation and regulation of complex systems, and the role and limits of biological analogies in understanding our universe.

Evolution and Development

Biological systems evolve, and they also develop. These two processes are quite different, but they are both necessary for life and intelligence to exist. While evolution (“evo”) is famously unpredictable, many aspects of development (“devo”) are quite predictable, with the right theoretical or empirical aids. For example, if you have a sense of what stage a developing system is at in its ‘replication’ cycle (birth, growth, reproduction, aging, or recycling), you have a basis to expect what stage is coming next.

Organic molecules also evolve and replicate/develop. So do stars, and their dependent planets. In fact, that’s how our own life-generating solar system came to exist, through a long process of stellar “evolutionary development” (reproduction of progressively more chemically complex solar systems) in our galaxy. Ideas or ‘memes,’ which replicate between human brains, also evolve and develop, according to some scholars. So do technologies, which undergo selection, replicate as dependents on human cultures, and exhibit long-term complexification. Some scholars suspect that even our universe itself may replicate, evolve, and develop, though this concept is quite speculative today.

The idea that the universe and its physical laws may be fine-tuned to have the precise values that make life and intelligence emerge as a developmental process has been championed for decades by scholars of the anthropic principle, a topic that some scientists, including Lee Smolin (Scientific alternatives to the anthropic principle, 2004), contend cannot presently yield any falsifiable predictions, and thus must remain the realm of philosophy, not science, at least in our present state of cosmology and astrophysics.

Nevertheless, there is today a striving by a growing number of disciplinary and interdisciplinary researchers to articulate a 'meta-Darwinian' theory of universal change that predicts certain systemic aspects of complexity's hierarchical emergence as statistically probable, arising from the unique parameters (laws, constants, conditions) of our particular universe, and which reconciles such a developmental hypothesis with the primarily contingent Darwinian mechanisms of emergence in living systems, and stochastic mechanisms of emergence in nonliving systems at multiple scales. The scientific need to organize, make accessible, and critique the literature, evidence, models and arguments of those proposing such articulation and reconciliation is great. So also is the need to identify promising research topics within this domain on an annual basis, and to promote productive collaboration among investigators and students in those research topic areas.

Modern evolutionary theory is more useful and validated than ever, yet with its gene-reductionist and individual-selectionist emphasis it is very unlikely to be a complete description of dynamics in biological systems. A growing community of evo-devo, ecological, and theoretical biologists propose that natural selection, while dominant, is not the only long-range influence on biological change. Developmental process and structure, and the unique physical features of our universal environment (its fundamental parameters and laws) are among a handful of 'non-adaptive' processes that are likely to constrain and direct long-range evolutionary change in still-poorly-understood ways (Müller and Newman 2003).

Fortunately, recent developments in cosmology, evolutionary developmental ('evo-devo') biology, astrobiology, and philosophy of science have provided promising new avenues of research for meta-Darwinian investigations. Consider the following insight from evo-devo biology: two genetically identical twins are unpredictably unique in their stochastically-determined dynamics and structure (organogenesis, fingerprints, neural connectivity, etc.) yet predictably similar in a range of systemically convergent emergent aspects (gross physical appearance, key psychological attributes, lifespan, etc.). A number of nonbiological processes, such as snowflake formation, and biological ones, such as brain emergence, can be modeled as both replicative on a variable, adaptive and environmentally-heritable template (e.g., 'evolutionary') while having aspects that are directional, cyclic, and statistically predictable (e.g., 'developmental').

By analogy, to what degree might we model our universe as another evolutionary and developmental nonlinear complex adaptive system? Would two initially parametrically identical universes each exhibit unpredictably unique and creative evolutionary differentiation over their lifespan, and at the same time, a broad set of predictable developmental milestones and shared structure and function between them? Such investigations may yield insights into evolutionary and developmental processes operating at multiple levels in complex systems.

Consider how many universal processes involve replication, variation, selection, and adaptation, and may be described by unpredictable (in most instances) stochastic, selectionist, evolution-like dynamics. Consider how a subset of other processes, such as entropy increase, dark energy, and apparent accelerating change, may be described by statistically predictable long-range, development-like dynamics. Can future science develop a common framework for relating universal evolutionary and developmental process by better understanding the interplay between evolutionary and developmental process in living systems? Can we come to understand evolution and development as hierarchy-creating processes generic to all complex systems?

We can today find tentative evidence and hypotheses for both evolutionary and developmental process in complex systems at all levels of universal scale, in the development of spacetime to create our quantum-relativistic universe (Jan Ambjørn and Causal Dynamical Triangulation), in the selectionist emergence of classical from quantum physics (Wojciech Zurek and Quantum Darwinism) in stellar nucleosynthesis (Donald D. Clayton, George Wallerstein and others), in models of RNA complexification and cellular biogenesis (D. Eric Smith, Eörs Szathmáry and others), in brain development (Gerald Edelman and Neural Darwinism and others), in cognitive selection in cognition and consciousness (William Calvin, Donald T. Campbell, Daniel Dennett, John McCrone and others), in evolutionary psychology (Jerome Barkow, Leda Cosmides, Michael Ghiselin, John Tooby and others), in cultural or 'memetic' selection (Robert Aunger, Susan Blackmore, Richard Dawkins and others), in evolutionary economics (Kurt Dopfer, Samuel Bowles, Geoffrey M. Hodgson), in evolutionary computation and 'artificial life' (Chris Adami, Mark Bedau, John Holland, John Koza, Chris Langton, and others), in ecological and human cultural hierarchy and scale (John Bonner, Geoffrey West, and others), in flow maximization in living and technological systems (Adrian Bejan and constructal theory), and in general technological evolutionary development (David Brin, Kevin Kelly, Ray Kurzweil and others). In each case, tentative models of both evolutionary and developmental process and their interactions may be usefully defined and discussed.

There are also a number of hypotheses for potentially evolutionary and developmental architecture and process in our universe as a system, including scale relativity (Laurent Nottale, Jean Chaline and others), self-similar hierarchy (Robert L. Oldershaw and others), free energy rate density and cosmic expansion (Eric Chaisson), complexity emergence acceleration (Carl Sagan, Richard Coren, Laurent Nottale, Jean Chaline, Pierre Grou, Theodore Modis, Philip Tobias, Anders Johansen, Richard Aunger), entropy production and infodynamics (Roderick Dewar, Stanley Salthe, and others), the fine-tuning problem in cosmology (John D. Barrow, Paul Davies, Lawrence M. Krauss, Martin J. Rees, and others), and the evolutionary development of the universe itself (Lee Smolin and Cosmological Natural Selection (CNS), James N. Gardner and early hypotheses of 'CNS with Intelligence' (CNS-I)).

Many mathematical and process models of long-proven use in biological systems, such as logistic growth curves, normal and power laws, representative maps, connectionist and hierarchical networks, and sophisticated models of ecological dynamics, such as panarchy (Lance H. Gunderson, Crawford S. Holling), developmental ascendancy (James A. Coffman, Robert Ulanowicz), and the interaction of cybernetic systems and evolution to produce self-organization (Carlos Gershenson, Francis Heylighen and others) are beginning to be applied more rigorously to prebiological, biological, cultural, and technological systems, and deserve much wider analysis and attention.

In the biological sciences, innovative scholars in the fields of genetic-cellular self-organization (Stewart A. Newman and dynamical patterning modules (DPMs)), in evo-devo and theoretical biology (Werner Callebaut, Sean B. Carroll, Christian de Duve, Gerd B. Müller, Massimo Pigliucci, Richard Reid, Stanley Salthe, Günter P. Wagner and others), in epigenetics (Eva Jablonka and others), in niche construction and stigmergy (Benjamin Kerr, Kevin N. Laland, John Odling-Smee) in evolutionary convergence (Simon Conway Morris and others), in evolutionary transitions (Eörs Szathmary) and evolutionary escalation (Geerat Vermeij) are pointing the way toward an "extended evolutionary synthesis", one that situates gene-centric neo-Darwinian natural selection within a more complex and long-range explanatory and predictive evolutionary and developmental paradigm.

We have seen similar theoretical advances in the previous century. When classical physics, as powerful as it is, came to be understood as a subset of general relativity, we gained a theoretical framework with far greater long-range explanatory and predictive value. As evo-devo life scientists point the way to a new, meta-Darwinian synthesis in biological systems, with (intrinsically unpredictable) macroevolutionary and (statistically predictable) macrodevelopmental processes operating over almost four billion years of life on Earth, we may also gain insights into the nature and extent of quasi-evolutionary and quasi-developmental process at the universal scale.

Finally, hypotheses of universal evolutionary development must seek to understand the role and emergence of information, computation, and intelligence within the universe. As one facet of this search, we must learn to reconcile the two most fundamental approaches to modeling human cognition, connectionism and computationalism. Connectionist (neural network, associative) processes (James L. McClelland, David E. Rumelhart) seem clearly evolutionary, selectionist, and adaptive. For example, using evolutionary and developmental genetic programming techniques to specify the expression of artificial neural networks (Daniel Rivero, Julián Dorado), allows environmental selection on the genotype of the expressed physical phenotype, just as in living systems. By contrast, computationalist (symbolic/logical/Bayesian) processes (Alan Turing, Jerry Fodor) seem likely to be a specially restricted and emergent subset of connectionist systems, appearing strongly only in higher mammals and their current primitive computing machines. Learning how to unify these two approaches, as in the neural-symbolic integration agenda (Barbara Hammer, Pascal Hitzler, Marco Gori) seems a necessary goal of future theory. Advances in neuroscience, mathematics and nonlinear science, information theory and complexity (algorithmic, computational, informational, and physical), and of course planetwide empirical and commercial engineering efforts all seem likely to play a role. Perhaps, at the end of this process, we may even come to understand the universe itself as a computational entity, a contention that has been championed in various forms by an impressive array of physicists in recent generations (Konrad Zuse, John A. Wheeler, David Deutch, Gregory Chaitin, Ed Fredkin, Stephen Wolfram, Seth Lloyd).

Of particular interest to our near-term cultural future are questions in information technology growth and evolution. Many classes of technology, such as transportation or steel production, demonstrate a pattern of punctuated equilibria in their evolutionary development, with long periods of relative stasis. In contrast, a select subset of information, computation, and nanotechnologies have shown constant, rapid and historically unprecedented exponential capacity development over long spans of cultural time. As Gordon Moore, Hans Moravec, Ray Kurzweil, William D. Nordhaus and others note, digital computers have doubled their price-performance ratios every one-and-a-half to three years, at least since the 1930's, while simultaneously migrating across mechanical, electromechanical, vacuum tube, transistor, and integrated circuit manufacturing paradigms. Are Moore's law and a collection of related exponential technology capacity growth laws part of a universal developmental process arising from some interaction between the physical structure of our universe and the value of computation at the 'leading edge' of evolutionary developmental adaptation? Or are these processes random consequences of some law of large numbers?

In a complex universe, a few physical processes must occasionally show powerful growth, for astronomically insignificant periods of time (eg., early-universe inflation, supernovas). Is our recent history of stunning informational, computational, and nanotechnological acceleration here on Earth part of a critical, central process of cosmic evolution and development, or is it an isolated statistical outlier, with little impact on future universal dynamics? Scholars are beginning to address such humbling yet fundamentally important questions.

In 1956, John McCarthy, Marvin Minsky, Nathan Rochester, and Claude Shannon convened a small and very interdisciplinary group to "proceed on the basis of a conjecture" that computers can be designed to simulate biological learning and intelligence. Their Dartmouth Summer Research Conference on Artificial Intelligence is considered the beginning of the "artificial intelligence" research community. In 1987, Christopher Langton convened the first interdisciplinary conference on "artificial life", a research community that proceeds on the basis of the conjecture that useful computer simulations of living systems, and perhaps even autonomous intelligent systems themselves, may be developed by biologically-inspired computing strategies. In the same vein, the EDU community convened in 2008 to proceed on the basis of a conjecture that informational, computational, and physical analogs to the complexity-constructing and conserving biological processes of evolution and replicative development may also help explain universal complexity emergence and dynamics.

There is no a priori supposition that our universe is “alive” or “computational” in these investigations. Vitalistic and technologic analogies in complexity science may be useful cognitive tools, but only to a point. Likewise, there may be sharp limits to the generalizability of evolution and development as processes of change operating at multiple scales, and in representations possible in current nonlinear science. Nevertheless, humanity is very early in these investigations and we see much potential ahead.

Major Transitions in Evolutionary Development

Theoretical biologists Smith and Szathmáry (1995) identify eight major transitions of evolutionary developmental emergence of biological complexity in universal history to date:

1. Replicating molecules to compartmentalized replicator populations (microspheres, etc.)
2. Independent nucleic acid replicators to chromosomes (linked replicators)
3. RNA as replicator template and enzymes to DNA as template and protein as enzymes
4. Prokaryotes to eukaryotes (with captured mitochondria and chloroplasts)
5. Asexual eukaryotic clones to sexual populations
6. Single-celled sexual protists to multicellular organisms
7. Solitary multicellular individuals to societies
8. Primate societies to human societies with language

Each of these may be considered a metasystem transition (Turchin 1977; Heylighen and Campbell 1996), the evolutionary emergence of a more complex and global (by some metrics) level of organization and control, and a system with greater internal diversity, both structural and behavioral. Promising mathematical and complexity models for several of these transitions also exist (Fontana and Schuster 1998; Nowak 2006). These and other transitions may form a specification hierarchy (Salthe 1993), may be quantitatively periodized (Nottale et. al. 2000; Aunger 2007), and have been proposed to form an evolutionary developmental arrow of complexity (Bedau 1998; Stewart 2000) for our universe.

Strictly speaking, transitions 1 and 2 above are prebiological (chemical evo devo). Other prebiological evolutionary developmental transitions may include:

1. Replicating black holes generating 'fecund' complex universes in cosmology (Smolin 2004)
2. Evolving space-time generating the quantum-relativistic world in cosmology (Ambjørn 2006)
3. Quantum einselectionism leading to emergence of the classical universe (Zurek 2003)
4. Replicating stellar nucleosynthesis generating complex pre-organic elements (Clayton 1968)
5. Interstellar and planetary environments generating complex organic molecules (Ehrenfreund and Spaans 2007)

Smith and Szathmáry's transition 8, to oral/written language, may be partly 'postbiological' (cultural evo devo). Scholars have proposed additional postbiological transitions, such as:

14. 'Memes' (replicating ideas and algorithms, in brains) to 'temes' (replicating technology, in culture) (Blackmore 1999).
15. Technological singularity (autonomous machine intelligence) to human-machine symbionts (Kurzweil 1999, Clark 2003)
16. Human-machine symbiosis to a global superorganism (Miller 1978; Stock 1993) with 'symbolic immortality' (Lifton 2004)
17. Postbiological intelligence eventually replicating its universe (Crane 1994, Harrison 1995)

Research Questions

  • Which of these transitions (and others) may we understand, from a universal perspective, as ‘evolutionary’ processes that generate ‘developmental’ emergence?
  • How do our tentative models of evolutionary and developmental process differ between these transitions? What features do they share in common?
  • At which levels can we identify evolutionary processes of natural selection, adaptation, creativity, divergence, contingency and/or unpredictability?
  • At which levels can we identify developmental processes that are directional, convergent, conservative, cyclic, and statistically predictable?
  • How do cosmology, astrophysics and astrobiology, evo-devo and theoretical biology, and the complexity and information sciences inform our thinking about evolutionary and developmental processes across these transitions and in the universe as a system?

Please see Themes and Questions for a more extensive list of research themes and questions being considered by the EDU community.

EDU Community and Conferences

Promoting interdisciplinary research into the arguments, evidence, and models for evolutionary and developmental processes that may operate in our universe is the unifying theme of the EDU Community. We seek to ground this inquiry in partnership with scientific disciplinarians from each of the proposed transitions listed above. Research topics are chosen roughly proportionately across five disciplinary academic domains: physics, chemistry, biology, society, and technology. In addition, we seek to emphasize three primary interdisciplinary approaches: complexity research, philosophy, and systems theory. Please see EDU SIGs for more on the Special Interest Groups we are seeking to develop in our community.

Ten to twenty specific research themes are typically selected for presentation and collaboration at each EDU conference or workshop, two to four per academic domain. Conference presentations are recorded and posted to a scholars discussion group, EDU Talk, along with presenters slides and papers. Presented papers are subject to open peer commentary and selected peer-reviewed papers are published in an academic journal.

Universal Evolutionary Development vs. Universal Darwinism ('Universal Evolution')

Investigations in universal evolutionary development include hypotheses of universal selection, also called universal Darwinism, but go importantly beyond this to also ask fundamental questions with respect to directional, hierarchical, and perhaps cyclical processes of universal development that are likely to coexist and interact with evolutionary process. Such questions must be asked if we suspect our universe is not only evolving but also developing, perhaps even in the manner that a biological system develops from seed, to organism, to reproduction, aging, and ultimately death/recycling. Early 'grand synthetic' models of this type were pioneered by Pierre Teilhard de Chardin, Thomas Huxley, Vladimir Vernadsky, Ludwig Von Bertalanffy, Alfred North Whitehead, and other twentieth-century scientists and philosophers. There are today notable successors to these theorists (Ervin Laszlo and others), yet many of our synthetic models remain less well-grounded than modern science demands.

Such models are often called hypotheses of 'universal evolution'. This is a misnomer. They are actually hypotheses of universal evolutionary development, as they are efforts to describe both evolutionary and developmental process at the universal scale. Though the distinction between these two processes was and still is rarely made sufficiently clearly or rigorously, both terms - evolution and development - are used extensively by these theorists and their successors to describe universal change.

Models of universal Darwinism do not, as a rule, admit to any inherent melioristic or orthogenetic (improving, complexifying) trajectory to processes of universal change, other than the traditional features of evolutionary process in biology (increasing variation, increasing specialization, etc.). As such they fail to address such apparently developmental features as the accelerating emergence of hierarchy in the universal, biological, and human-historical record, or the accelerating universal adaptability and computational complexity at the leading edge of evolutionary change over cosmic time. Models of universal evolutionary development can and do address such features.

As in evo-devo biology, modern hypotheses of universal evolutionary development must attempt to investigate and describe the broad evidence of multi-level selection operating not just in biological systems (e.g., genetic, kin, sexual, and cultural selection in human beings), but also in pre- and postbiological systems. But at the same time, they must seek to describe the many ways evolutionary processes are likely to be constrained and conserved by an equally fundamental set of processes of universal development, just as evolutionary processes appear to be constrained and conserved by developmental architecture and process in all biological systems.

In conclusion, evo devo universe investigations are an attempt at describing the state of hypotheses in universal evolutionary development, as a tentative 'next step' beyond the useful but incomplete hypothesis of universal Darwinism toward a meta-Darwinian theory of universal change. Thank you for adding your insight and critique to our community.

References

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