The Organic Influence: How Nature Stimulates Innovation
Originally published on Wonk Bridge
One of the keystones of Jungian psychological thought is the archetypal image. The eminent Swiss psychiatrist postulated the existence of certain images and symbols that resonate with the human imagination and orient patterns of thinking in a way that transcends time and circumstance. The list of archetypes manifest Tarot-like: the flood, the father, the mother, the trickster, the idealist, the wise elder, the shadow. They seem to occur and exercise their fascinations on cultures around the world with more or less equal frequency.
The archetypes were formulated in rebuke of Locke’s conception of the mind-as-tabula-rasa, as an argument in favour of the theory that the mind comes with certain software built-in. The archetypes are, like the work of Jung’s precursor Freud, unfalsifiable and ungeneralisable, more mystical than scientific, proof that metaphysics became psychoanalytic when it could not by any chalk be reckoned scientific anymore. That does not, however, mean that the archetypes are without usefulness — nor does it stop us from looking at instances wherein seemingly unprecedented human innovations may have had previously unknown roots of inspiration, and wondering whether or not some function of an archetype was at play.
The Plant-Hopping Issus
If you try to think of great historical coincidences in the fields of thought, the first thing you might think of might be Newton and Leibniz’s unrelated and almost exactly contemporaneous discoveries of calculus, or that European history’s two most eerily exact forecasters of future event (Burke in predicting Napoleon, Luxembourg on predicting Lenin) both wrote under the pen-name ‘Junius’.
One thing you wouldn’t think of is the humble mechanical gear. Well, humble through overfamiliarity at least — few innovations could ever be so profound. In fact, the gear has become so synonymous with human technology, so associated with the will of humankind to build, that is has become a sort of shorthand for technology itself — the symbol of our means to our relative mastery over time, water, electromagnetism. Early preserved cogs date from China in the 4th century BC; the Antikythera mechanism originated in Greece 150–200 years later. The worm gear then came about in the 13th and 14th century CE in India, shortly before the construction of the Salisbury Cathedral clock, one of the world’s first scale applications of gear technology.
But while humanity may have been responsible for inventing the gear, we did not in fact invent the gear — that’s to say, we did not invent it first, though we were, until 2013, ignorant of its actual inventor. The gear’s actual inventor is, in fact, nature itself. And its first product incorporating this innovation? The plant-hopping issus.
This distant cousin of the grasshopper possesses functional gears in its hind legs. The two interlocking gears allow the insect’s hind legs to synchronise to maintain its trajectory while jumping. As the insect prepares to jump, the gear teeth of one leg mesh with the teeth of the other, “like cocking a gun.” Potential energy is stored and is then released in an explosive jumping motion. Malcolm Burrows, a researcher on the study that first made the discovery, expressed his belief that the legs of the issus constitute “the first demonstration of functioning gears in any animal.”
All in the Mind
Of course, neither a Zhou dynasty engineer nor Hero of Alexandria nor any of the other genii of antiquity could possibly have taken direct inspiration from the issus in scoping the gear — the microscopic scale of the original machinery precludes that possibility. But it shows the roots of mechanical genius in nature’s own.
Deep learning and artificial intelligence are another area in which innovation strives to emulate nature. The human brain remains the most complicated structure in nature, in many ways still unfathomable to us. Much of the most ardently pursued work in neural networking has operated under the presumption of experiment that the brain we are seeking to model should be appraised as a mechanical system in order to be understood.
However, several of the most notable recent innovations in AI have been rooted in reversing that presumption, and instead trying to appraise AI structures as though they were biological models. For instance, where it was presumed that the more complex an AI’s capabilities in solving problems, the better it could emulate the brain, researchers from MIT CSAIL, TU Wien (Vienna) and IST Austria have discovered that neural networks that are simpler and smaller can perform many tasks more quickly and more efficiently than vastly complex ones.
In their study, a neural network based on the brain of a threadworm could control a self-driving car more capably than more complex deep learning models — the next time you worry about your lane discipline, remember that apparently even a nematode can keep-to-lane autonomously (once its brain has moved beyond its somewhat ‘starter’ casing). According to a report for CSAIL MIT, “[The simple model] copes much better with noisy input, and, because of its simplicity, its mode of operation can be explained in detail. It does not have to be regarded as a complex “black box”, but it can be understood by humans.” Even such simple brains, with so limited a neuronal palette, exhibit fascinating adaptability in behaviour.
The research group acknowledged that the fruits of this study were entirely based on their resolution to learn from nature to foreground the next great innovations in deep learning. As Professor Daniela Rus, director of MIT CSAIL and a key contributor to the study, succinctly put it, “Nature shows us that there is still a lot of room for improvement…[we tried] to massive reduce complexity and develop a new kind of neural architecture.”
https://www.youtube.com/watch?v=8KBOf7NJh4Y
Preservation of Our Archetypes
Perhaps, given such developments, it is no longer helpful to think of nature and technology dichotomously. Of course, gears having become a kind of ersatz component of our ‘nature’ — if they had not been ‘invented’ by humans, the human estate as we know it would never have had cause to develop as it has done — it too has become a device of mapping further innovation, its own archetype. Quantum gears form a mechanical system in quantum computing, serving as a model for various quantum systems “such as an artificially constructed nanomechanical device or a group of ring molecules.”
The idea of archetypes themselves, viewed as ‘built-in-mental-software’, have exerted themselves, either deliberately or by chance or through exertion of unconscious influence, through the innovation that brought Windows to eminence in ready-to-use home computing.
A lobbyist conception of economics often put the infinite necessity of innovation and the requirements of natural preservation at odds with one another — that in order to excel in the former, a certain ‘healthy’ disregard for the latter is required. What an assessment of the archetypes most certainly does is confirm to us how rich is the intellectual bounty of nature — that latent within systems of natural order are structures that are ripe for our appropriation, adaptation and use. The likes of Archimedes and Leonardo da Vinci understood this profoundly.
I am resistant to encourage a utilitarian view of the concept of natural preservation. Among other things, it is self-defeating — one of the reasons that Archimedes and Leonardo made the advances they did owed to their own ability to look beyond pure utility. But that one can convincingly make a utilitarian argument for preservation and ecological study goes to demonstrate the impregnable comprehensiveness of the preservational argument as a whole, and fortifies the parallel argument that preservation and study, two pillars of what is in all true senses conservative, are inextricable from making the most profound leaps in invention, one pillar of what is in all true senses progressive.
