Repeated patterns in the history of complex systems suggests that new systems of potential will become embedded in technological artefacts, begin interacting with each other, and begin a new evolution parallel to those of biological and semiotic systems. The reasoning behind this can be explained as follows.
The first occurrence of this pattern was the embedding of biological potential, DNA chemical systems, in cells of protein chemical systems, from which unicellular organisms emerged: first prokaryotes (bacteria), then eukaryotes. When biological potentials in different organisms began interacting, through sexual reproduction, the pace of evolutionary change in biological systems quickened. When multicellular organisms emerged as supervenient on collectives of unicellular eukaryotes, biological potential became, more specifically, developmental potential, and the development of multicellular organisms came to involve interactions between the potentials in different cells, by means of the proteins that expressed specific instances of those potentials. Again, the pace of evolutionary change in biological systems quickened.
The second occurrence of this pattern was the embedding of behavioural potential, neurological biological systems, in animal bodies that are the phenotypic expressions of developmental potential. This was the emergence of systems that linked recognition of the environment in which the organism was embedded to adaptive bodily movement in that environment. When behavioural potentials in different organisms began interacting, through social semiosis, the pace of evolutionary change in behavioural systems quickened.
Accordingly, a third occurrence of this pattern would be the embedding of a new type of potential in technological artefacts that are
the phenotypic expressions of behavioural potential.
[1] The following progression can be projected.
Firstly, analogous with the generation and selection of embedded “Darwinian” chemical systems (biological potential) and neurological systems (behavioural potential), embedded “Darwinian” technological systems would be generated and selected. Such systems, so-called brain-based devices, have already been generated and selected by the Neuroscience Institute, under the directorship of Gerald Edelman, though they have not yet been economically selected so as to become the most prolific of technological systems.
[2] Their purpose is to simulate the recognition-based behaviour of animals
[3] in order to test neuroscientific hypotheses, so they are still in the behavioural realm, but nevertheless on the threshold of a new order of complexity, just as the chemical systems at the transition to biological systems, and the neurological systems at the transition to behavioural systems, were on the threshold of a new order of complexity.
Secondly, analogous with the interactions between genomes, by protein expressions, during multicellular development, and with the interactions between organisms, by semiotic expressions, potentials embedded in different technological artefacts would interact with each other. Interaction involves the selection of potential, information content supervenient on a medium of information, in one artefact by the expressions, such as emissions of electromagnetic radiation, of potential in another artefact. With regard to the material substrate of such information potentials, the present-day foci of attention are on the development of quantum computers, on the one hand, and DNA computers, on the other.
With interaction between potentials, the pace of evolutionary change in technological systems would quicken. It would entail the evolution of potential in the lifetime of the artefact, ontogenesis, and the evolution of potential in interacting communities, phylogenesis. This would include the ontogenetic and phylogenetic differentiation of technological registers, according to context-of-use type, and the phylogenetic differentiation of regional technological dialects. This evolution of technological potential would, of course, become distinct from the evolution of semiotic potential from which it emerged, just as the evolution of semiotic potential became distinct from the evolution of biological potential from which it emerged.
[4]
Some possible functions of such systems can be projected on the basis of present-day concerns. These might include networks of localised solar, wind and water power generation, the continual tweaking of biospheric systems, through recognition (monitoring) and interactive behaviours, in ways that maintain the ecosystems embedded within them, the detection and redirection of earthbound asteroids and comets, and the exploration of the universe, which may include the creation of biospheric systems on suitable terrestrial planets for the embedding of biological systems within them. Such functions may entail the creation of new types of “artefacts” by such technological systems creating the possibility of the embedding of a newer type of evolving system within them. And so it goes…
Footnotes:
[1] The reader is invited to imagine fourth and subsequent occurrences of this pattern.
[2] This stage may accelerate if
mimetics, using ideas from nature for technological design, becomes a more widely selected design principle.
[3] The recognition systems of animals are not simulated by neural nets. Unlike neuronal groups, neural nets are instructed
what to do (though, like neuronal groups, not
how to do it). Recognition is formal and rule-bound, rather than contextual and meaningful (organismic).
[4] technological potentials : semiotic potentials :: semiotic potentials : biological potentials
ChatGPT revised:
Repeated patterns in the history of complex systems suggest that new systems of potential will become embedded in technological artefacts, begin interacting with each other, and initiate a new evolutionary trajectory, parallel to those of biological and semiotic systems. The reasoning behind this can be elaborated as follows.
The first occurrence of this pattern was the embedding of biological potential — DNA chemical systems — in cells composed of protein chemical systems, from which unicellular organisms emerged: first prokaryotes (bacteria), then eukaryotes. When biological potentials in different organisms began to interact, through sexual reproduction, the pace of biological evolution accelerated. With the emergence of multicellular organisms — supervenient on collectives of unicellular eukaryotes — biological potential became more specifically developmental potential. Multicellular development came to involve interactions between potentials in different cells, mediated by proteins that expressed particular instances of those potentials. Again, the evolutionary pace quickened.
The second occurrence was the embedding of behavioural potential — neurological biological systems — in animal bodies that are phenotypic expressions of developmental potential. This marked the emergence of systems that linked environmental recognition to adaptive bodily movement. When behavioural potentials in different organisms began to interact through social semiosis, behavioural evolution also accelerated.
A third occurrence of this pattern would be the embedding of a new kind of potential in technological artefacts — artefacts which are, themselves, phenotypic expressions of behavioural potential.[1] The following progression can be projected.
First, analogous to the generation and selection of embedded “Darwinian” chemical systems (biological potential) and neurological systems (behavioural potential), embedded “Darwinian” technological systems would be generated and selected. Such systems — brain-based devices — have already been developed at the Neurosciences Institute under the direction of Gerald Edelman. Though not yet economically selected into wide proliferation, they represent an important prototype. Their function is to simulate animal-like, recognition-based behaviour in order to test neuroscientific hypotheses. They remain within the behavioural domain, but are positioned on the threshold of a new order of complexity — just as chemical systems at the transition to biological systems, and neurological systems at the transition to behavioural systems, were on the threshold of theirs.
Second, and again by analogy: just as genomes interact through protein expression in multicellular development, and just as organisms interact through semiotic expression in social life, the potentials embedded in different technological artefacts may begin to interact. Here, interaction involves the selection of potential — the information content supervenient on a medium — in one artefact, by the expressions (such as electromagnetic emissions) of potential in another. Current foci for the development of such information potentials include quantum computers and DNA-based computing.
With such interaction, the pace of technological evolution would accelerate. This would entail both ontogenesis — the evolution of potential in the lifetime of an artefact — and phylogenesis — the evolution of potential within communities of artefacts. These would include the ontogenetic and phylogenetic differentiation of technological registers, based on context-of-use types, and the phylogenetic differentiation of regional technological dialects. Over time, the evolution of technological potential would diverge from the evolution of semiotic potential from which it arose, just as the evolution of semiotic potential diverged from the biological evolution it emerged from.[4]
Some projected functions of such systems can be extrapolated from present-day concerns. These might include decentralised networks of solar, wind, and water power generation; ongoing adjustment of biospheric systems through recognition and interaction to preserve ecological balance; the detection and redirection of earthbound asteroids and comets; and interstellar exploration, including the creation of biospheres on terrestrial planets suitable for embedding biological systems. Such functions may entail the creation of new classes of artefacts — opening the possibility for the emergence of yet another kind of evolving system embedded within them. And so it goes...
Footnotes:
[1] The reader is invited to imagine fourth and subsequent occurrences of this pattern.
[2] This stage may accelerate if mimetics — technological design inspired by natural systems — becomes a more widely selected principle.
[3] The recognition systems of animals are not simulated by neural nets. Unlike neuronal groups, neural nets are instructed what to do (though, like neuronal groups, not how to do it). Recognition in animals is formal and rule-bound, but also contextual and organismic — meaningful in ways neural nets are not.
[4] Technological potentials : semiotic potentials :: semiotic potentials : biological potentials.