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Are You A Machine?
The machine model has been the pervasive metaphor in science for 200 years - Why is this model so attractive and how does it feed our trans-human fantasies?
In chapter 12 of Iain McGilchrist’s book The Matter With Things, he elegantly debunks the myth that the living, organic world is anything like a machine. With many examples of totally un-machine like behaviour, McGilchrist completely dismantles the notion that organisms like ourselves, or single cells for that matter, are anything like a machine. The second half of the chapter he addresses the reasons why the machine model has been so pervasive in our perception of just about everything.
I think this is an important awareness for us as some strive for a transhuman future and try to convince us this is a good thing. The transhumanist agendaof marrying human to machine only makes sense if the human is seen as one type of ‘machine’ and computer/hardware another type of machine, that can seamlessly integrate. I have no doubt it can be of use in some cases - artificial limbs come to mind - but doubt its wisdom when attempting to ‘evolve’ the human race as a human/machine hybrid (a cyborg). The other part of the transhumanist dream is gene editing and the manipulation of our genome for ‘enhancement’, tackling disease, and longevity. They sound like noble pursuits but they conceptualise DNA like a computer program, and as we will explore, it’s way more different and complex than that.
But quite apart from transhumanism, using a model to conceptualise a reality that is very unlike the model is severely limiting and forces an unhealthy bias. Machines are designed from the bottom up for a purpose. Utility is fundamental. Output, productivity, service, is all foundational to the model. As we will see below, the world of the living, the organic, is quite unlike a utility, unlike a machine, and should be conceptualised in a completely different way. A human has more in common with a river than a robot.
How is biology not like a machine?
The left hemisphere has an affinity for the metaphor of the machine because machines are made of discrete parts, are non-living, have utility and can be manipulated and controlled - all aspects of the abstracted world that is prioritised by the left hemisphere. Using the model of the machine to explain the world has been very successful for 200 years or so and for good reason. This model has allowed the left hemisphere to dominate in the realms of science and has allowed us incredible powers of manipulation. We have been able to create technology and manipulate the world like never before because we’ve been able to conceptualise everything as machine-like and emulate or synthesise things from this understanding. This continues today as we emulate the machine-like aspects of the brain (or rather what we think are machine-like) in artificial neural networks to drive artificial intelligence or edit genes to improve biological ‘machines’ as one would upgrade an operating system on a computer. The metaphor is flawed, as we will discuss below, but nevertheless has been critical as an aid of conceptualising organic things for the sake of manipulation.
In the biological sciences the machine model has been the dominant paradigm throughout modernity, and even when physics dropped the machine model because of quantum ‘mechanics’, biology persisted with the metaphor of machines and mechanical processes (bits strung together in a cause and effect ‘mechanism’). In fact, the idea that living things are machines is so entrenched it feels rather odd to think that they could be anything else - such has been the dominance of the left hemispheres thinking in this area. Biology, it seems, has held onto the Newtonian mechanistic model ignoring the fact that physics has moved on. Cognitive scientist Donald Hoffman remarks,
Not only are they ignoring the progress in fundamental physics, they are often explicit about it. They’ll say openly that quantum physics is not relevant to the aspects of brain function that are causally involved in consciousness… They don’t avail themselves of the incredible insights and breakthroughs that physics has made. Those insights are out there for us to use, and yet my field says, ‘We’ll stick with Newton, thank you. We’ll stay 300 years behind in our physics.’… I don’t think we are machines… As a conscious realist, I am postulating conscious experiences as ontological primitives, the most basic ingredients of the world. I’m claiming that experiences are the real coin of the realm. The experiences of everyday life—my real feeling of a headache, my real taste of chocolate—that really is the ultimate nature of reality. (Hoffman, 2016)
The left hemisphere, if left on its own, wrongly equate the metaphor for reality - for everything to the left hemisphere is abstraction, theory, re-presentation, and not the actual thing or process. The metaphor may be useful to a degree, and indeed has been as we’ve said, but we find ourselves in error when it becomes dogmatic, when the metaphor is mistaken for reality - the observed world being forced into conformity with the metaphor for anything to make sense. When biology is about living machines and the biologist, akin to an engineer working with ‘codes’ and parts, thinks that understanding is through pulling it apart into bits, then we have lost the sense of the living, flowing, relational whole. Everything, it seems, in biology is explained as a ‘mechanism’ yet concurrently explaining the organism in language that is incompatible with mechanistic processes.
It will no doubt be said by some that such language is just a façon de parler, such as when I say that my car engine ‘labours’, or ‘struggles’ to get up the hill in third gear. But that is not an adequate response to the sheer ubiquity, scope and inescapability of such language - or, more significantly, the nature of the phenomena it is called on to describe. (McGilchrist, 2021, p. 433)
McGilchrist goes on to suggest that there are six features of language used by biologists to describe what they see that is decidedly not coming from the metaphor of the machine. “References to (1) actively co-ordinated processes, expressing a sense of (2) wholeness, inextricably linked with (3) values, (4) meaning and (5) purpose - each leading separately and together, to the phenomenon of (6) self-realisation.” (McGilchrist, 2021, p. 434)
There is obviously something going on in biology that is beyond the machine model and the language just described gives it away. Neuropsychiatrist Dr Jon Lieff writes in his book, The Secret Language of Cells, about the incredible conversations and coordination that happens among cells that determine all aspects of biology. The adaptive and spontaneously creative responses of cells reveal a wisdom that is very unlike my ‘smart’ TV or my MacBook Pro for that matter. Cells like T-cells of the immune system can ‘think on their feet’, so to speak, in situations that require coordination of many other cells, including neurones, to manage an assault in an intelligent way - responding to novelty in a way that is seemingly not pre-programmed. As Dr Thomas Verny summarises in his discussion on cells, “we can conclude that the cells in our bodies are truly intelligent and as such, form an essential and necessary substrate of the embodied mind.” (Verny, 2021, p. 72)
Barbara McClintock, founder of cytogenetics, in her Nobel Prize acceptance speech in 1984 had similar things to say about the cellular world:
Some sensing mechanism must be present … to alert the cell to imminent danger … the conclusion seems inescapable that cells are able to sense the presence in their nuclei of ruptured ends of chromosomes and then to activate a mechanism that will bring together and then unite these ends, one with another … the sensing devices and the signals that initiate these adjustments are beyond our present ability to fathom. A goal for the future would be to determine the extent of knowledge the cell has of itself and how it utilises this knowledge in a ‘thoughtful’ manner when challenged … We know nothing, however, about how the cell senses danger and instigates responses to it that often are truly remarkable. (McClintock, 1984, pp. 749, 798, 801)
Nevertheless, the machine model persists and is instilled into children, the scientists, and the general public, in such a way that any other conception is simply heresy.
Organisms Are Not Machines
Richard Dawkins in his book The Selfish Gene, describes organisms as ‘survival machines - robot vehicles blindly programmed to preserve the selfish molecules known as genes.’ The computer metaphor for genetic ‘programming’ is ubiquitous in the fields of biology giving the impression that the genome contains the architectural master plan of the body. But this is not the case. Genes don’t ‘do’ a lot of things we assume they do:
Genes are said to be ‘self-replicating’, they engage in ‘gene action’, they ‘make’ proteins, they are ‘turned on’ or ‘turned off’ by ‘regulatory’ DNA. But none of this is true … DNA is among the most inert and nonreactive of organic molecules. (Lewontin, 2000, pp. xii-xiii)
Biological systems are not machines - McGilchrist details 8 points of interest.
…a machine is static until switched on, and may be switched off without ceasing to exist. Organisms… much like waterfalls or tornadoes, do not have an off switch. The very existence of an organism is, from beginning to end, one unceasing flow of matter and energy. For it to stop, even for an instant, would mean immediate death. (McGilchrist, 2021, p. 443)
Like all things that exist in flow, the dynamic nature of it, like fire, cannot be stopped and the entity continue to exist as it does. I wonder, as does McGilchrist, if what we do in anatomy, the cutting up of living forms into anatomical bits, belies the importance of the flow and relationships that constitute the living thing. In biology living entities are becoming due to their continuous activity. The machine, on the other hand has to be built before it is set in motion – the thing and its parts take priority over the process and therefore is a poor, if not completely misleading, metaphor for living entities.
For living beings – perhaps they should be called living ‘becomings’… they are what they do, and come into being through their very movement. In this they are like streams that flow. Their being, their form, their becoming, is their movement; and their movement is their being. (McGilchrist, 2021, p. 443)
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Motion vs stasis
A computer, sitting on your desk without power applied, is in a state close to dynamic equilibrium. When power is applied the otherwise static components are animated in certain ways, transmitting energy on in linear chains to other components, until the power is once again turned off and the static state is returned. An organism, however, is in a continual state of change with the exchange of matter during metabolism (from the Greek metabole, meaning ‘change’), the steady flow of molecules streaming through it, the continual electro-chemical activity. What needs to be explained is how does the organism remain stable given its flow nature. The human body has some 37.2 trillion cells, each performing many millions of reactions a second within complex feedback systems with other cells. This massive complex flow of activity is the organism.
Whatever else organisms may be, what cannot be denied at an ontological level is that they are stable metabolic flows of energy and matter. Machines may take part in various processes, but organisms are themselves processes. This inescapable fact must constitute the starting point for any theory of the organism. (Nicholson, 2018, p. 148)
McGilchrist cites a fascinating observation by biologist Craig Holdrege about the structure, or form, of organisms arising out of flow that is worth repeating here:
Before the heart has developed walls (septa) separating the four chambers from each other, the blood already flows in two distinct ‘currents’ through the heart. The blood flowing through the right and left sides of the heart do not mix, but stream and loop by each other, just as tow currents in a body of water. In the ‘still waster zone’ between the two currents, the septum dividing the two chambers forms. Thus the movement of the blood gives the parameters for the inner differentiation of the heart, just as the looping heart redirects the flow of blood. (Holdrege, 2002, p. 12)
Organisms are open systems in a continual process of exchanging energy and matter with their environment in order to maintain an equilibrium. Maintaining a low-entropic ‘steady state’ while performing these exchanges and metabolising, as organisms do, is the critical balance performed by all living beings to persist and even to proliferate.
Homeostasis, that process of maintaining equilibrium through change, may seem paradoxical to the left hemisphere but is at the core of biological life – two forces counteracting each other to produce stability. Even the functioning of the brain with a balance of the two hemispheres is an example of harmony through opposing tendencies.
In a classical mechanism there is a linear causal process – there is a predetermined and predictable sequence of events, each step predetermined by the previous one. Biological systems tend to flow in spirals with recursive loops, multiple causes with multiple effects, competing factors cross-regulating on another, all in a non-linear complex way we do not fully understand. Like a spiders web, tension on one part of the web will alter the tension on every other part of the web in different ways. Context is everything – something we’ve been saying for a long time, and biological systems cannot be accounted for via bottom-up processes only but also top-down and sideways processes need to be included. As an organism develops it is not a neat sequence of events but everything going on at the same time that cannot be simplified beyond simply describing what is there. To illustrate the absurd complexity of the simplest signalling pathways in cells, a group of researchers plotted the interactions between just four cascades and only to five steps. They found there were 760 positive and negative interactions and this did not take into account a multiplicity of other intermediate effects. And this not in steps but an indivisible flow. The specificity of any action within a cell is difficult if not impossible to define absolutely and the researches described the multitude of interactions as “everything does everything to everything” (“interlocking, reciprocal and interpenetrating processes on such a scale show chains of causation to provide limited insight into cell responses” – McGilchrist, 2021, p. 449) – not exactly the clear and linear description of a ‘machine’ that the left hemisphere is looking for.
Not one-way action – maybe not even interaction?
Organisms display action, interaction, and mutual construction in a reciprocal cause and effect dynamic. Unlike the machine model that suggests a direction of action, one thing acting on another in a linear progression. When an organism interacts with its environment, both change. For example the genome changes in response to conditions, and not just as a result of damage or accidents. DNA is highly malleable responding to cellular experience of the environment and making complex changes with disrupting the functional integrity of the organism. There is not ‘blind’ programming by a ‘selfish gene’, but rather a standing resource, as Evelyn Fox Keller writes,
Today’s biologists recognise that however crucial the role of DNA in development and evolution is, it does not do anything by itself. It does not make a trait; it doesn’t even include a ‘program’ for development. Rather, it is more accurate to think of a cell’s DNA as a standing resource on which a cell can draw for survival and reproduction … it is always and necessarily embedded in an immensely complex and entangled system of interacting resources that collectively are what give rise to the development of traits. (Keller, 2014, pp. 40-41)
The action of an enzyme, often described in the machine-like metaphor of ‘lock and key’, seems to work by two parts accommodating each other
In a dynamic negotiation: ‘in reality, the activated receptor looks less like a machine and more like a … probability cloud of an almost infinite number of possible states, each of which may differ in its biological activity’ (McGilchrist, 2021, p. 452). And further to the negotiation metaphor over the mechanical one, organisms are involved in many symbiotic relationships, as we know in ourselves and our gut microbiome. Organisms don’t so much react to an environment as they act with an environment – there is a vital interdependence. The causal effects are not all bottom up: DNA – cell – organism – environment. They are also top down: Environment – organism – cell – DNA. The environment plays a significant role on the DNA as does the DNA on the environment.
The ‘parts’ are themselves changing
Unlike a machine the ‘parts’ of an organism are changing all the time depending on the context. A blood cell, a neuron, an epithelial cell, these all have the same genome yet arise as very different phenotypes with particular inheritances within a lineage. Furthermore, “there are far more proteins coded for by DNA than there are genes to make them: what those genes make depends on the context and what is required in it” (McGilchrist, 2021, p. 455)
Indeed all the molecules that make up your body change according to the context they find themselves in and on may levels producing a diversity of function and effects. The shapeshifting nature of proteins being but one example – the so called ‘intrinsically disordered’ proteins (being 30-50% of your proteins) with not fixed shape display a virtually unlimited field of possibilities. Genes also display a malleable process subservient to the needs of the organism. As philosopher of science Denis Walsh says,
The engineering of the genome by the organism is commonplace. Cells actively cut, transpose, copy and fix their genomes. They do so in highly sensitive, adaptive ways.
This is a vastly different perspective than seeing DNA as the script, the program, the blueprint, to which the organism is destined to become. There is way more indeterminacy, flow and creativity-along-the-way in these ‘antifragile’ systems of adaptation and flexibility. In many respects the fixity and solidity of organisms is a misperception.
Ultimately, even what we conceive to be the ‘solid’ parts of cells are actually flows. The living cell is mainly fluid, principally water. Even surfaces, cell membranes, the cytoskeleton, and the various fibre systems, that look relatively solid, are ‘subject to more of less continuous dissolution and reconstitution.’ We imagine the organism contains fixed structures because of the nature of the left hemispheric attention, which replaces flow with frozen slices removed from time: our static diagrams, or photomicrographs. (McGilchrist, 2021, p. 458)
The influence of the whole
Assuming for a moment that we can identify ‘parts’ of an organism. These ‘parts’ are not separate assembly pieces that are put together to form a whole but come about at the same time as the rest of the body to create a whole. As an organism grows more defined ‘parts’ emerge that don’t ‘make up the whole but derive from the existence of the whole’. The dynamic emergence of properties through the relationships, at different levels, with the ‘parts’ of an organism leads us back to what is an indivisible process and not an assembly of parts. The betweenness of everything within the process influences and shapes everything – the whole shaping the ‘parts’ the ‘parts’ shaping the whole. The organism is not an aggregate but a defining unity.
… at the phenomenological level we see this all the time. As molecules form new wholes, utterly new qualities, unpredictable from the apparent constituent parts, emerge: so a tasty white crystalline substance – table salt – emerges from the compound of sodium, a dullish grey, malleable metal, and chlorine, an evil-smelling, poisonous, greenish-yellow gas. (McGilchrist, 2021, p. 460)
Machines generally don’t adapt in response to parts wearing out or becoming defective, machines are not usually designed to invent a local solution on the fly to such problems to further, or even improve, the purpose of the machine. An organism, however, can respond in creative ways to heal themselves, and some even to regenerate entire body parts. The flatworm can regenerate it’s entire body, including its centralised brain, from a mere fragment of itself. Not only that but the regenerated flatworm, or flatworms if many bits regenerate, retain the memory of the original worm – i.e. remembering how to navigate a maze.
Cells, as well as the whole organism, display intelligence – that ability to deal constructively with the unforeseen – whereby the whole influences the ‘parts’ as much as the ‘parts’ influence the whole. The ‘parts’ access information about the whole and intelligently act in service of the whole.
If a cell is placed in a slightly acid medium, its mitochondria break up into small spherical beads. But, amazingly, on return of the cell to a normal medium, they merge again into strings, and eventually take on once more the appearance and internal structure of normal mitochondria. Further, let us suppose you cut a developing limb bud out of an amphibian embryo, shake the cells loose from each other, and then allow them to aggregate once more into a random lump. You then replace the random lump into the embryo. What happens? A normal leg develops. The form of the limb as a whole dictates … the rearrangement of the cells. (McGilchrist, 2021, p. 466)
The single cell is remarkably intelligent and, in the case of a predatory single-celled ciliated microorganism, can hunt and pounce on prey in what seems to be something akin to a cat hunting a mouse. The ciliate Spirostomum has memory and can be trained!
McGilchrist cites examples of experiments where critical genes were knocked out of the DNA yet the organisms would regain those functions even in the absence of the gene. DNA adaptation, or the influence of the organism on its own DNA, is not the result of mere accidents. As McGilchrist summarises, “organisms don’t just passively wait, then, for a luck accident or resign themselves to dying out, but actively remodel themselves in response to change in their environments.”
The boundaries of a machine are clearly defined, the boundaries of natural systems are not so. Living things are processes, as we have established previously, and processes are not so much defined by where they are as by what they do. Just as the brain is continuous with the rest of the body, the symbiotic gut microbiome is essentially integrated with the rest of the body and is vitally connected with the environment. The closer we look at organisms the less delineated are individual entities and the more complexly nested and networked are they all. It becomes a vast web of interconnected, cooperative, symbiotic, co-regulating mass of life.
In the case of a machine, the instructions for making the machine cannot themselves be the product of the very machine they are designed to make. Even in a computer, the software is separate from the hardware: the hardware has to be finished, before the software can be extrinsically inserted into it. The code for making the machine is not being simultaneously written by the machine in the very process of beginning to form itself as a computer. (McGilchrist, 2021, p. 471)
However, organisms do generate information in the process of development, through feedback of current states, to further influence development. This is very unlike machines, even sophisticated artificially intelligence software has to have the intelligent input from a programmer first, where as there are cellular processes in which we cannot account for any such “pre-programming”.
Why do we like this machine model?
We understand machines, they can be broken down, the parts understood, and put back together to make a functional, productive thing. For the most part they are simple - at least simple in contrast to living things - and we like simple. We can grasp chains of cause and effect, we can manipulate the chain, we can have control over a machine. It is natural that we then extrapolate our understanding of machines to other animated things. They have the illusion of comprehensibility if they are machine-like. We abstract cause and event chains, as in molecular biology, and interpret the system as broadly mechanical in nature. We identify a reliably repeatable process in an organism and immediately assume is demonstrates mechanism and determinism.
However, random events can produce broadly predictable outcomes - the random falling of rain ends up in predictable flows of streams and rivers, the random accidental deaths of any particular type remain relatively regular and predictable. Christopher Hallpike uses Monopoly as a metaphor:
the players are all different and the throws of the dice produce a completely different game each time, yet the underlying constraints produce essentially the same result - a single player who owns everything and has driven all the others into bankruptcy. This is a good illustration that unique events, even randomness, and free will, are quite compatible with broadly predictable outcomes.
Living things may have the appearance of reliability and stability we associate with machines yet are less stable and more reliable than machines. As much as the machine metaphor has been useful it does not mean that it is true. The problem with a useful, but not true, metaphor is you cannot extrapolate it out as we have done to the living world. It starts to become a limiting factor if not a serious handicap. Besides the fact that an erroneous metaphor can be limiting in a utilitarian sense, it is also damaging to the noble scientific pursuit of understanding who we are.
McGilchrist suggests that beyond simplicity, familiarity and utility there is a more impassioned reason to hold onto the machine model - “I am inclined to think that one element in the model’s popularity is that it encourages the sense that we can easily understand what life is and learn to control it…” That left hemisphere desire to manipulate and control, while denying the obvious evidence that organisms are not machines and insisting on its mechanistic view of things. “Metaphorically speaking, it is as though many biologists now reside in the left hemisphere’s hall of mirrors, and not only cannot find the way out, but have stopped being aware there is a world outside to attain,” laments McGilchrist.
To accept and comprehend living things as a process, constantly flowing, becoming, changing, and complexly enmeshed within its context and environment is difficult, if not impossible for the left hemisphere. For the left hemisphere process has to be translated into things, non-linear complexity (including reciprocal interactivity and co-creation) has to be translated into simplistic linear cause and effect. The left hemisphere
understands a whole as simply the assemblage of parts, and causation as from bottom up only, not from many directions at once within the whole. It is at home when it can follow procedures; less so when it comes to recognising new forms, or fields, at work. It prefers what is clearly defined, to what has imprecise boundaries. It doesn’t see Gestalten, of which life provides the pre-eminent examples.
In contemporary biology this allegiance to the utilitarian bent of manipulating the world by the left hemisphere is good reason why we should pause and consider its claims to truth. We had been told it was the ‘selfish gene’ that, for purely survival reasons, was the ‘blind’ driver and indeed the mechanism for evolution. But we now know that the organism as a whole influences its DNA as much as its DNA influences the whole and rather than survival of the fittest, it’s more like thriving of the cooperative - cooperation within and with the environment in a reciprocal co-creative way.
But the left hemisphere, the hemisphere we seem to be biased toward in this early 21st Century, has difficulty dealing with living things and rather sees living beings as dead, zombies, machines. The flow of living things, for the left hemisphere, is to be stopped, and only then can the static representation of the dead slices or bits be understood, or rather manipulated and controlled. Also the idea that something, like a human being, has intrinsic purpose or value is not accepted by the left hemisphere. In its world everything of value must have an extrinsic purpose - i.e. it must be useful as much as usefulness is defined by the left hemisphere. Of course there are teleologicalquestions, the ‘what for?’ questions of ‘reasons for the design’ when it comes to biology. But the teleology of living things does not necessitate determinism but rather tendencies and tendencies that are often not extrinsically utilitarian or exploitative as the left hemisphere imagines. Form plays a crucial role in tendency of processes toward a certain form, an intrinsic potential as process unfolds…
‘Latent within the polymeric sequence of amino acids that constitutes the enzyme’s primary structure’, writes Stein, ‘is directionality and potential for its correct folding into a catalyst of remarkable power and selectivity’. The forms that are required in the enzyme, in the cell, in the tree, may not be achieved by pushing from behind, but by drawing from in front, towards certain ends, certain conformations, certain attractors, much as a valley ‘draws’ water that falls evenly on the surrounding hills to one clear end: the mouth of just one river. There is stored attractive energy in the formation of the landscape. (McGilchrist, 2021, p. 479)
So an organism, unlike a machine, can have a multitude of random events happening within and without, indeterminate, unpredictable, yet display purposeful behaviour. You would not put much faith in a motor vehicle that was described as a mass of randomly flowing molecules that flow like a river yet will eventually get you to your destination. Nor should we put a lot of faith in a human described as a fixed, predetermined, predictable mechanism - that maybe a good description of an android but not of your partner or child.
Nevertheless most orthodox biologist want to cling onto the machine model despite this intrinsic purpose in biology. To state it another way, machines are designed by an external intelligence (even if the machine is made by another machine, the first machine has been purposed by human intelligence). Their purpose is extrinsic, made for a purpose to serve the intelligence that designed it. The machine is a representation and execution of the will of (primarily) the human left hemisphere. Machines do not make themselves from an intrinsic volition and purpose like organisms do. And so for the left hemisphere to make sense of the organic world it turns to the thing it knows best, mechanism.
Dawkins, in an attempt to save the machine model of biology, talks of The Blind Watchmaker, which is all good and fine except that organisms are nothing like watches and evolution, blind or not, doesn’t proceed like a watchmaker. Of course Dawkins was attempting to refute intelligent design with a process of design without intelligence. It is a difficult subject because it forces us back to the primal question of a divine designer.
Turner writes: ‘To honestly deal with the question at hand here - where does design come from? - there is no way of avoiding the problem of intentionality: it is the 800-pound gorilla sitting in the corner’. This is surely wrong: the gorilla is sitting, not in the corner, but in the middle of the room. ‘The living world is not only a designed place’, he concludes, ‘it is, in its peculiar way, an intentionally designed place … a living phenomenon replete with the purposefulness and intentionality that is the fundamental attribute of life itself. Let me say, before the howls begin, that neither he nor I are arguing for an engineering God. What we have to explain is how there is order, complexity, beauty and purpose, while at the same time accepting that what we are dealing with is not a machine, and it has no extrinsic purpose, such as a machine has - it does not fulfil, in what would have to be an instrumental fashion, the purposes of something external to it. (McGilchrist, 2021, p. 486)
The Stream of Life - A Better Model?
The words for Nature in Chinese, tzu-jan, and Japanese, shizen, mean whatever is ‘of itself’, exists ‘spontaneously’, is ‘just what it is’. They are, in origin, adverbs, not nouns - ways of being, not things. If there is anything in this ancient perception, and I believe there is great wisdom in it, a vision of the natural world as a thing, and a mechanical one at that, is bound to restrict our understanding of what we are dealing with to a certain rather alienating perspective. A machine implies existence of an external creating force with its own purpose: Nature delights in her own. (McGilchrist, 2021, p. 488)
The problem of modelling life, suggests McGilchrist, is that we start from things as the important underlying elements. But it is not discrete things that underpin living organisms but processes. It seems physics has arrived at this realisation way before biology - patterns of flowing energy and force fields, constantly in flux, are the underpinning elements of the material world. Everything is a manifestation of energy, of vibration, if you like, not static, but in a constant state of flow. On the quantum level, what we thought were particles turn out to be quantised excitations of particular fields - statistical patterns of stability waves in a sea of background activity. Thingness, and things static, is just a shorthand representation of reality we use to ‘grasp’ what is. As a metaphor, a stream, a river, a waterfall, the ocean, convey a closer relationship to organisms than a machine.
Stasis is an illusion. An illusion of time and space. The world at the molecular, atomic, and sub-atomic levels move very fast - the motion of waves a blur of activity. On the macro scale things seem to be more static, more solid, yet if you were to see a timelapse of a particular landscape over millions of years you would see the ebbing and flowing movement of matter on a grand scale. The qualities of things change with scale but overall the material universe flows like a river of life. Nevertheless, the stream is still yet a metaphor - never to be confused with reality as we might get hypnotised in a hyper-realistic virtual world - it is still a representation. We need to keep this in mind. But, we can have more accurate metaphors for the living than the machine (as much as the machine metaphor has been useful).
The left hemisphere, that side of the brain I argue is obsessed with the idea of transhumanism, has a narrow, piecemeal scope and desires precision upon a frozen object in a slice of time. This narrow perspective of time and space belies the depth and flow of the whole and indeed something very important is missing from the left hemisphere’s picture of the world.
Once the left hemisphere has frozen its object in time, and decontextualised it in space, it is left with fixed, clear, distinct but inert parts, which then have to be reconnected and reanimated; the building blocks have to be put together again, and the power, as it were, switched on. To the right hemisphere these ‘objects’ are already connected, animate and in motion: the power was never switched off. (McGilchrist, 2021, p. 493)
I think we can start to appreciate the difficulties, if not outright catastrophes, that could present themselves when attempting to enmesh biology with machines or manipulate DNA as if it were simply a computer code. The left hemisphere is making the incorrect assumption that it is joining one type of machine to another, or being a ‘genetic engineer’, when in fact the thing-nature of the machine and the flow/process stream of the organism are fundamentally different, and I would suggest incompatible. Nature is continuous, emergent, flowing…
At a fundamental level is nature discrete or continuous? I see no evidence whatever for discreteness. All the discreetness we see in the world is something which emerges from an underlying continuum … Quanta are emergent … they are not built into the heart of Nature. (Tong, 2016)
There is no doubt that machines are good at manipulating biology - the surveillance state is testimony to the utility of modern technology to control thoughts and behaviour through technocratic governance. But to truly integrate the man and the machine is a different matter entirely.
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Verney, T. R. (2021). The embodied mind: Understanding the mysteries of cellular memory, consciousness, and our bodies. New York, NY: Pegasus Books.
Nicholson, D. J. (2018), ‘Reconceptualizing the organism: from complex machine to flowing stream’, in D. J. Nicholson & J. Dupré (eds), Everything Flows: Towards a Processual Philosophy of Biology, Oxford University Press, 139-166.
Cover image taken from CueStack - Transhuman Generation (Official Music Video)
The transhuman [iv] is a biological-technological organism, a transformation of the human species that continues to evolve with technology. This evolution is understood within the fields of paleontology, archaeology, evolutionary biology, and anthropology. It is further studied and understood in philosophical discourse and social and cultural studies. It is made aware and realized through advances in technology that bring about human-computer interaction, wearable devices, and computerized communication infrastructures. It is evidenced in medical science and scientific breakthroughs that identify genetic mutation and target disease as well as research and development of gene therapies that aim to reverse and restore cellular damage of biological system. On an environmental level, it is experienced in spaceflight by astronauts adapting to environments beyond earth. On an interactive level, it is experienced in the personalized avatar and character usage of virtual reality, augmented reality, video games, and other artificial environments. https://www.humanityplus.org/the-transhumanist-manifesto
The technology for transhuman transformation emerges from cybernetics. It is here where concepts of the human and machine integrate and the computer begins to interact (Wiener 1950:163)[vi] with the human body and its biology, bringing about the concept of the cyborg. Comparisons are often drawn between the cyborg and the transhuman deliberately and also unwittingly. A cyborg is positioned as an endpoint for the integration of human, machine, and computer; however, the transhuman is a continuous human evolution. This evolution includes a confluence of organic human, technological advances in AI, nanomedicine, and gene therapies that mitigate disease, the devices and prosthetics and enhance biology that append biology, and an awareness of personal identity, as a transformative, telematic, and expanded agency that expands through new tech-communication systems. https://www.humanityplus.org/the-transhumanist-manifesto
Ironically keeping the work ‘mechanics’ even though there is hardly anything ‘mechanical’ about the quantum realm.
McGilchrist goes to great lengths in the first half of his 12th chapter to tease this out.
Teleology: the fact or character attributed to nature or natural processes of being directed toward an end or shaped by a purpose; the use of design or purpose as an explanation of natural phenomena.
McGilchrist doesn’t use the ocean as a metaphor but I threw it in there as it makes a good one the more you think about it.
The transhumanists themselves admit there are such dangers:
“We recognize that humanity faces serious risks, especially from the misuse of new technologies. There are possible realistic scenarios that lead to the loss of most, or even all, of what we hold valuable. Some of these scenarios are drastic, others are subtle. Although all progress is change, not all change is progress.” (The Transhumanist Declaration)