What is Post-Symbolic Scientific Intelligence?
Our symbolic intelligence is at least 50,000 years old. It began 50,000 years ago in a psycho-mythopoeic mode, a mode that continues to this day, but also evolved into scientific intelligence, which is symbolic intelligence in its most disciplined and constrained mode.
So scientific intelligence and understanding is a particular mode of our evolutionary, symbolic intelligence. Post-symbolic scientific intelligence isn't simply better scientific intelligence. Post-symbolic scientific intelligence is scientific intelligence that recognises consciousness as it is, rather than presuming it to be the result of causal structure in the objective material world.
This doesn't mean however, simply that it is symbolic intelligence that says, for example, quantum coherence, prior to decoherence into the objective material world, is consciousness. That's not the same thing at all. That's a collapse of registers. Consciousness as it is isn't a scientific concept, and isn't in the scientific register. But structure in conscious phenomenology, is.
Any structure can be part of scientific understanding, even structure in phenomenology. So when neuroscience speaks of "neural correlates of consciousness" what it is actually talking about is neural correlates of structure in conscious phenomenology. Just because there are neural correlates of conscious phenomenology doesn't mean that the brain organ is a thing that produces conscious phenomenology in a way that can be understood just by considering that individual brain.
In fact, no individual brain organ ever came into existence by itself, and similarly, the individual conscious phenomenology it gives rise to is not something that can be correctly considered as coming into being by itself.
The objectivity of the whole material world, together with the conscious phenomenology of the entire human race, are not things that just happen to have multiple parts that constitute the whole. Multiple brains and multiple instances of individual phenomenology, the fact that they are multiple, is part and parcel of the very means by which they come into being.
The principle we are talking about, understood in the scientific register, is redundancy. We already recognise now in the scientific understanding of quantum decoherence that the world's objectivity is the result of redundancy. That's the very beginning of post-symbolic scientific intelligence. Scientific intelligence has already replaced the old notion that the scientist (scientific intelligence) can be an "independent, objective observer" of the world on the basis that this intelligence is somehow fundamentally separate from what it is observing.
It is a step towards understanding the significant of the fact that our material world has the same origins as our own evolutionary intelligence, which of course, de facto, embodies our consciousness as a human being. And that the difference between consciousness and the "neural correlates of consciousness" in the brain is due to each being the result of a different trajectory from the common origin.
Science has to deal with what is scientifically observable, but since consciousness is not in any case a scientific observable, what is needed is a structure through which both evolution in the objective world and the evolution of conscious phenomenology, can be understood, in the scientific register. We don't have to have some theory that claims to reduce consciousness to scientific facts, in order to understand scientifically that our conscious phenomenology itself fits into the scientific picture of the evolution of the species. The VGF is precisely such a structure.
Redundancy
There are different kinds of redundancy, but all of them in the IIP-VGF framework constitute a stable attractor in the VGF:
1. Path redundancy
Several routes lead to the same result. Biological signalling pathways often have this form. Damage to one route does not necessarily eliminate the function.
2. Component redundancy
Several entities perform sufficiently similar roles. Two kidneys, duplicated genes, parallel servers, or multiple members of a species can preserve a function even though no two are perfectly identical.
3. Temporal redundancy
The same causal influence is repeated through time. A structure is not produced once and then simply left alone; it is continually regenerated or repaired.
A living organism, for example, persists because its organisation is repeatedly renewed through metabolism, gene expression, repair, and behavioural regulation.
4. Feedback redundancy
An outcome reinforces the conditions that reproduce it. The state is now supported not only by an initial cause but by a loop. A disturbance may be corrected because later stages feed back into earlier ones.
5. Multiscale redundancy
The same organisation is supported at several nested levels. An organism’s identity may be maintained through molecular regulation, cellular replacement, organ-level integration, nervous regulation, and interaction with its environment.
No single scale wholly contains the organism’s persistence.
Redundancy does not require exact duplication Redundancy is not simply the repetition of identical objects. Two causal pathways may differ considerably while preserving the same higher-level result. Indeed, imperfect redundancy is often more robust than exact duplication, because differently structured pathways do not necessarily fail under the same conditions.
Thus a species is redundant not because its members are identical, but because many non-identical organisms carry overlapping genetic, developmental, and behavioural possibilities. Variation allows the closure represented by the species to survive conditions that might eliminate one particular form.
In VGF terms
In the IIP-VGF framework a network is approached from the point of view of the fact that it is the internal structure of a closure of infinite iteration in the VGF. A network and a nested hierarchy of coupled closures may not be literally the same mathematical object, but one can often be represented as the other. They are two complementary descriptions of the same underlying relational structure. In terms of the VGF:
Initially there is open iterative generativity.
A nested hierarchy of coupled closures is the multiscale coarse-graining of an underlying causal network. Conversely, a causal network can be viewed as the fine-grained expansion of a hierarchy of coupled closures.
In the VGF, redundancy arises when an emerging β-configuration is instantiated repeatedly enough that its dependence on any singular generative event is reduced. Initially, a pattern may be fragile. The β pathways are not necessarily identical. They are different realisations that converge upon or preserve the same γ-stabilisation.
Redundancy is therefore the mechanism by which a causal pattern becomes a closure. The network has crossed an important threshold when the outcome is no longer merely caused, but is causally overdetermined: enough of the network points toward the same stable organisation that local variations cease to undo it.
In fact, redundancy is present when the network preserves its causal identity through more than one possible internal history. Once multiple pathways converge on the same result, the network also begins to embody a form of memory. The past events need not remain present in their original form. Their effect has become distributed among the network’s current relationships.
The Stability–Fidelity Law
Increasing redundancy makes a causal outcome more stable. But the network becomes less dependent upon, and therefore less faithful to, the exact causal history that first produced it. The mature closure remembers what must be preserved, not every detail of how it first arose. So the causal network fully embodies redundancy when causation ceases to be merely a linear transmission from past to future and becomes the distributed, recurrent maintenance of a form.
So scientific intelligence and understanding is a particular mode of our evolutionary, symbolic intelligence. Post-symbolic scientific intelligence isn't simply better scientific intelligence. Post-symbolic scientific intelligence is scientific intelligence that recognises consciousness as it is, rather than presuming it to be the result of causal structure in the objective material world.
This doesn't mean however, simply that it is symbolic intelligence that says, for example, quantum coherence, prior to decoherence into the objective material world, is consciousness. That's not the same thing at all. That's a collapse of registers. Consciousness as it is isn't a scientific concept, and isn't in the scientific register. But structure in conscious phenomenology, is.
Any structure can be part of scientific understanding, even structure in phenomenology. So when neuroscience speaks of "neural correlates of consciousness" what it is actually talking about is neural correlates of structure in conscious phenomenology. Just because there are neural correlates of conscious phenomenology doesn't mean that the brain organ is a thing that produces conscious phenomenology in a way that can be understood just by considering that individual brain.
In fact, no individual brain organ ever came into existence by itself, and similarly, the individual conscious phenomenology it gives rise to is not something that can be correctly considered as coming into being by itself.
The objectivity of the whole material world, together with the conscious phenomenology of the entire human race, are not things that just happen to have multiple parts that constitute the whole. Multiple brains and multiple instances of individual phenomenology, the fact that they are multiple, is part and parcel of the very means by which they come into being.
The principle we are talking about, understood in the scientific register, is redundancy. We already recognise now in the scientific understanding of quantum decoherence that the world's objectivity is the result of redundancy. That's the very beginning of post-symbolic scientific intelligence. Scientific intelligence has already replaced the old notion that the scientist (scientific intelligence) can be an "independent, objective observer" of the world on the basis that this intelligence is somehow fundamentally separate from what it is observing.
It is a step towards understanding the significant of the fact that our material world has the same origins as our own evolutionary intelligence, which of course, de facto, embodies our consciousness as a human being. And that the difference between consciousness and the "neural correlates of consciousness" in the brain is due to each being the result of a different trajectory from the common origin.
Science has to deal with what is scientifically observable, but since consciousness is not in any case a scientific observable, what is needed is a structure through which both evolution in the objective world and the evolution of conscious phenomenology, can be understood, in the scientific register. We don't have to have some theory that claims to reduce consciousness to scientific facts, in order to understand scientifically that our conscious phenomenology itself fits into the scientific picture of the evolution of the species. The VGF is precisely such a structure.
Redundancy
There are different kinds of redundancy, but all of them in the IIP-VGF framework constitute a stable attractor in the VGF:
1. Path redundancy
Several routes lead to the same result. Biological signalling pathways often have this form. Damage to one route does not necessarily eliminate the function.
2. Component redundancy
Several entities perform sufficiently similar roles. Two kidneys, duplicated genes, parallel servers, or multiple members of a species can preserve a function even though no two are perfectly identical.
3. Temporal redundancy
The same causal influence is repeated through time. A structure is not produced once and then simply left alone; it is continually regenerated or repaired.
A living organism, for example, persists because its organisation is repeatedly renewed through metabolism, gene expression, repair, and behavioural regulation.
4. Feedback redundancy
An outcome reinforces the conditions that reproduce it. The state is now supported not only by an initial cause but by a loop. A disturbance may be corrected because later stages feed back into earlier ones.
5. Multiscale redundancy
The same organisation is supported at several nested levels. An organism’s identity may be maintained through molecular regulation, cellular replacement, organ-level integration, nervous regulation, and interaction with its environment.
No single scale wholly contains the organism’s persistence.
Redundancy does not require exact duplication Redundancy is not simply the repetition of identical objects. Two causal pathways may differ considerably while preserving the same higher-level result. Indeed, imperfect redundancy is often more robust than exact duplication, because differently structured pathways do not necessarily fail under the same conditions.
Thus a species is redundant not because its members are identical, but because many non-identical organisms carry overlapping genetic, developmental, and behavioural possibilities. Variation allows the closure represented by the species to survive conditions that might eliminate one particular form.
In VGF terms
In the IIP-VGF framework a network is approached from the point of view of the fact that it is the internal structure of a closure of infinite iteration in the VGF. A network and a nested hierarchy of coupled closures may not be literally the same mathematical object, but one can often be represented as the other. They are two complementary descriptions of the same underlying relational structure. In terms of the VGF:
Initially there is open iterative generativity.
- Repeated iteration creates a causal network.
- Certain regions become self-reinforcing.
- Those become closures.
- Those closures then interact.
- Their interactions form another network.
- That network again develops stable closures.
- The distinction between "network" and "closure hierarchy" therefore becomes one of perspective rather than ontology.
A nested hierarchy of coupled closures is the multiscale coarse-graining of an underlying causal network. Conversely, a causal network can be viewed as the fine-grained expansion of a hierarchy of coupled closures.
In the VGF, redundancy arises when an emerging β-configuration is instantiated repeatedly enough that its dependence on any singular generative event is reduced. Initially, a pattern may be fragile. The β pathways are not necessarily identical. They are different realisations that converge upon or preserve the same γ-stabilisation.
Redundancy is therefore the mechanism by which a causal pattern becomes a closure. The network has crossed an important threshold when the outcome is no longer merely caused, but is causally overdetermined: enough of the network points toward the same stable organisation that local variations cease to undo it.
In fact, redundancy is present when the network preserves its causal identity through more than one possible internal history. Once multiple pathways converge on the same result, the network also begins to embody a form of memory. The past events need not remain present in their original form. Their effect has become distributed among the network’s current relationships.
The Stability–Fidelity Law
Increasing redundancy makes a causal outcome more stable. But the network becomes less dependent upon, and therefore less faithful to, the exact causal history that first produced it. The mature closure remembers what must be preserved, not every detail of how it first arose. So the causal network fully embodies redundancy when causation ceases to be merely a linear transmission from past to future and becomes the distributed, recurrent maintenance of a form.