No Newton of a blade of grass: Organisms beyond mechanisms – Fellows’ seminar by Johannes Jäger

10 June 2020

“Immanuel Kant famously remarked that there will never be ‘a Newton of a blade of grass’. Although he was sympathetic to the scientific investigation of living processes, he did not believe that organisms as a whole could be understood mechanistically. This is because living systems are organised in a way which defies mechanistic-reductionist analysis. Kant’s view — even though sorely neglected in recent time — has stood the test of time,” said STIAS fellow Johannes Jäger of the Complexity Science Hub, Vienna.

STIAS Fellow Johannes Jäger presented his webinar on 4 June 2020.

He explained that Kant was emphasising that it is absurd for humans to think that even Newton could make a blade of grass comprehensible according to natural laws. “We can’t understand living organisms through mechanical science. Even the simplest of bacteria is a very complex world.”

Jäger explored specific aspects of living organisms that defy the mechanistic approach.

Swimming through molasses

“The first is their fundamentally stochastic nature,” he said. “Not only do organisms tolerate what we call ‘noise’, they thrive on it! In fact, fluctuations are an essential part of their nature, which renders any attempt at describing them in the form of some kind of ‘programme’ hopelessly inaccurate and misleading.”

He pointed out that the default behaviour in any multicellular organism is cell proliferation with variation and motility. “An organism is not a static network. Cells are not ordered, static structures but are constantly changing and self-organising. There is no centralised authority but there is continuous transformation.”

“Organisms are open systems,” he added. “There is a constant exchange of energy and renewal at every timescale – it’s far from equilibrium.”

Organisms can change their own structure without help from the outside while non-living systems cannot. Such constant fluctuations allow the biological system to survive. “Machines decay but cells harvest and profit – they are both fragile and anti-fragile – they profit from noise and perturbation”.

Sum of the parts

“The second aspect is the autopoietic, or ‘self-making’ organisation of living beings, which defies reduction since properties of the whole influence and alter the behaviour and properties of its parts in a dynamic of constant dialectic co-generation across levels of organisation.”

“Each part owes its presence to all the other parts,” continued Jäger. “Each part is both an end and means – being generated and generating – to create a whole.”

“You cannot take the system apart without losing the autopoiesis and killing it.”

He highlighted that even the simplest of organisms – primitive bacteria – have goals and make decisions to attain them.

“They are not consciously thinking like humans but are selecting from different behaviours – in other words, they have agency.”

Using a video, he showed that we are able to observe such goal-orientated behaviour when one bacteria colony raids and devastates another colony for food.

“But there is no programme, no sequence of steps,” he continued. “And, if there was a programme, what would it run on? There is no distinction between hardware and software in the human system.”

He explained that although the human body has a genetic code this is a blueprint for making proteins not a programme for making bodies. He added that the approach of applying mechanical science to the study of nature implied that all we have to do is understand the mechanics to understand what life is.

“You can’t apply general laws of physics in the biology and social realm. Mathematical tools are not suited to study a system that rewrites the rules as it goes along.”

“Also over time the machine model was no longer a metaphor – organisms are no longer like machines but are machines. This is a very bad idea and has huge implications for the evil twins of genetic determinism and reductionism.”

“Genetic determinism of any kind is a bad idea. The most pernicious incarnation is genetic programming,” he added.

Even though this type of dynamic hierarchical structure does not fit into traditional ways of doing science, Jäger believes there are scientific explanatory strategies available to us to understand living beings as goal-oriented agents.

“But,” he added, “science like this is in its adolescence. What does it even look like? It’s fundamentally different.”

This view also, obviously, has profound moral implications for the study of life, evolution and the way we treat living beings.

“We won’t understand evolution by just studying genes,” he said. “We are seeing the negative consequences now of treating evolution like a machine. The universe rewrites the rules. They are constantly changing and open to innovation.”

“Human beings are distinguished by the flexibility of their behaviour – no other organisms have the same level of complexity.”

“I have renewed awe for the comprehensive and fundamental differences between living and non-living systems. We don’t really know anything about life yet.”

In discussion, he spoke about the need to change our approach to healthcare. “Medicine should allow the body to heal itself. Western medicine doesn’t do that. For example, there is no one cancer, cancer is an individual disease. Time and money has been wasted by thinking that has been too mechanical. The old approaches are hitting a wall.”

He also said that a deeper understanding of this could make our response to the current crisis very different: “Society is an organism not a machine. Reality is dominated by random fluctuations and is context dependent. Phenomena are not generalisable. The system makes use of randomness. It’s a fundamentally unpredictable world. The systems that survive are those able to take advantage of the noise.”

“It’s also important to realise where the boundaries of predictability and control are,” he added. “Any rigid, top-down control is anti-fragile. This is a huge problem at the moment.”

“People also expect prediction from science. But prediction is not understanding. It’s not about control and predictability but about understanding and wisdom.”

Michelle Galloway: Part-time media officer at STIAS
Photograph: Supplied

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