Complexity & The Brain Of The C-Elegans Worm

Nassim Taleb On Complexity & Hayek’s ‘Scientism’

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The Difference Between The Sum Of Its Parts & Its Behaviour

The difference between understanding the components of something versus how that same thing works can be everything.

It’s clearly not a universal rule. By understanding the components of a bike, and then how each component behaves with the other we can confidently claim to know how a bike works. I know that cycling the sturdy pedal will pull the chain that will then turn the wheels.

Everything else around that core functioning is just aesthetic or qualitative detail. 

But by mapping out all the organic components of a human body, from organs to bones and everything in between – does our understanding of each component then inform to confidently assert how it all works? I am not sure.

Just because you can map out a system does not mean you understand how it behaves.

Taleb argues not, and although I am sure much of the medical community might disagree, I will try and explain in this article the relationship between complexity and each additional variable to the cohort. 

In Nassim Taleb’s words… 

There are qualitative differences between a group of ten and a group of, say 395,435. Each is a different animal, in the literal sense, as different as a book is from an office building. When we focus on commonalities, we get confused, but, at a certain scale, things become different. Mathematically different. The higher the dimension, in other words, the number of possible interactions, the more difficult to understand the macro from the micro, the general from the units.

Back to me…

Here is the distinction between, I think, measuring the relationship between variables and complexity, which themselves can exhibit a wide range of behaviour. A chain has less functional uses than does say, a human being. There are way more variables.

Back to Taleb…

Or, in spite of the huge excitement about our ability to see into the brain using the so-called field of neuroscience: Understanding how the subparts of the brain (say, neurons) work will never allow us to understand how the brain works.

Ok, back to me… 

So just because we can map out the human brain, does not then mean we understand how the human brain works. Understanding each component of a group will not necessarily shed light on then how a whole group might behave. 

Back to Taleb…

So far we have no f***g idea how the brain of the worm C Elegans works, which has around three hundred neurons. C Elegans was the first living unit to have its gene sequenced. Now consider that the human brain has about one hundred billion neurons. and that going from 300 to 301 neurons may double the complexity. (I have actually found situations where a single additional dimension may more than double some aspect of the complexity, say going from a 1000 to 1001 may cause complexity to be multiplied by a billion times.) So the use of never here is appropriate. And if you also want to understand why, in spite of the trumpeted “advances” in sequencing the DNA, we are largely unable to get information except in small isolated pockets of some diseases. Understanding the genetic make-up of a unit will never allow us to understand the behavior of the unit itself.

Ok, back to me…

So, if we have no idea how the brain of a worm works which has 300 neurons, how on Earth can we claim to have any actionable insights into how the human brain works. When complexity can feasibly double or as Taleb says, in some cases 100, 200, 1,000,000 x with each additional node? The scale here is only understandable to technicians. It’s like the difference between an atom and a kilometre. We can acknowledge it is a big difference, but for us to appreciate the difference is another thing. And so if we cannot answer what the complexity of 300 neurons entails, what do we do about billions that have compounded on themselves billions of times? 

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Nassim Taleb, Complexity & The Dutch

I am reminded of this company ASML – a company I recently did a business profile on, who are printing billions of lines onto a microchip the size of a fingernail – a scale of accuracy that can only be appreciated by the techincians involved.

We are talking about how complexity scales exponentially – with the ultimate insight being that our attempts to make sense of a future prediciton based within a realm of unnapreciated complexity is bound to failure. There will be second, third, fourth order conseqeuences that you couldnt predict because your prediction was not sophisticated enough to take into account the complexity. 

Back to Taleb…

A reminder that what I am writing here isn’t an opinion. It is a straightforward mathematical property. I cannot resist this: Much of the local research in experimental biology, in spite of its seemingly “scientific” and evidentiary nature fail a simple test of mathematical rigor. This means we need to be careful of what conclusions we can and cannot make about what we see, no matter how locally robust it seems. It is impossible, because of the curse of dimensionality, to produce information about a complex system from the reduction of conventional experimental methods in science. Impossible.

Back to me… 

I understand this to be saying in other words – the difference between understanding how a thing is made and then understanding how a thing behaves is everything. 

Back to Taleb… 

My colleague Bar Yam has applied the failure of mean-field to evolutionary theory of the selfish-gene narrative trumpeted by such aggressive journalists as Richard Dawkins and Steven Pinker (btw notice how he calls them journliasts) and other naive celebrities with more mastery of English than probability theory. He shows that local properties fail, for simple geographical reasons, hence if there is such a thing as a selfish gene, it may not be the one they are talking about. We have addressed the flaws of “selfishness” of a gene as shown mathematically by Nowak and his colleagues.

Hayek, who had a deep understanding of the properties of complex systems, promoted the idea of “scientism” to debunk statements that are nonsense dressed up as science, used by its practitioners to get power, money, friends, decorations, invitations to dinner with the Norwegian minister of culture, use of the VIP transit lounge at Kazan Airport, and similar perks. It is easier to take a faker seriously, since science doesn’t look neat and cosmetically appealing. So with the growth of science, we will see a rise of scientism, and my general heuristics are as follows: 1) look for the presence of simple nonlinearity, hence Jensen’s Inequality. If there is such nonlinearity, then call Yaneer Bar Yam at the New England Complex Systems Institute for a friendly conversation about the solidity of the results ; 2) If the paper writers use anything that remotely looks like a “regression” and “p-values”, ignore the quantitative results.

Back to me…

It is at the very least an exponential function, if each additional node at least doubles the complexity than it starts becoming more clear why smaller groups are easier to understand than larger groups. Everything from behaviour to beliefs

When you introduce employee 10 to your company all the potential behaviour and variables might seem manageable, but when you introduce employee 1000 there is too much complexity in the overall group so the behaviour will be managed and tampered by soul destroying bureaucracy.

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