Mother Nature is infinitely inventive. The forces that have given rise to and shaped all of the life here on Earth are constant puzzles to scientists. But they are entirely fathomable puzzles and not irreducibly complex, regardless of what you may have been taught at Sunday school…
If you managed to read through some of the arguments by the so-called “Intelligent Design” movement without laughing, or just throwing your arms up in the air in sheer despair, then you may have come across an argument of theirs called Irreducible Complexity.
On the face of it, Irreducible Complexity seems like a sound and entirely reasonable argument.
However, it’s merely a thin facade that gives the appearance of scientific reasoning, when in actuality, it’s nothing more than a theistic justification for a defeatist attitude.
Since this tragically naive idea emerged, it’s since been roundly panned by most reasonable thinkers and essentially crippled in a court of law. But still people persist in rallying around such nonsense notions.
Reducing the complexity of the brain
Scientists at the University of Reading here in England have created their own little robot. To look at, it’s nothing remarkable. Better and more sophisticated have been made, many of which you could actually buy for your children.
But what sets their robot apart from all others is the thinking apparatus you won’t find in any robot bought from Toys ‘R’ Us — this robot is powered by actual living brain tissue:
“This is no ordinary robot control system – a plain old microchip connected to a circuit board. Instead, the controller nestles inside a small pot containing a pink broth of nutrients and antibiotics. Inside that pot, some 300,000 rat neurons have made – and continue to make – connections with each other.”
Actually, the brain itself isn’t in the robot. Because it’s a living component, it’s susceptible to environmental vagaries. So it’s kept in a: “temperature-controlled cabinet the size of a microwave oven and communicates with the robot over a Bluetooth radio link.”
A sort of man-made telekinesis, if you like.
The remit of the research is broad; from understanding how neurons make their physical connections, how they communicate and store memories, right up to disease research:
“Such insights might help in the treatment of conditions like Alzheimer’s, Parkinson’s disease and epilepsy.”
Such research isn’t entirely new. Others are working in similar areas to the University of Reading. Even the process they’re working to isn’t new, either. The idea of breaking a system down into something smaller and more manageable is most probably the cornerstone of research — and that’s what I find so fascinating.
As an aside, something very unusual happens within the mesh of dense neurons when there’s no sensory input:
“The neurons seem to be randomly firing, producing pulses of voltage known as action potentials. Often, though, many or all of them will fire in unison, a phenomenon known as ‘bursting’.
Like a creature with no limbs or senses, the cut-down brain is simply bursting out of boredom, says Whalley. ‘With no structured sensory input the hypothesis is that you get arbitrarily random and quite often detrimental activity because all these cells are asking for some kind of direction.’”
Almost immediately, I thought of those sporting events when out of sheer boredom, almost the entire crowd act in unison, acting out that iconic Mexican Wave — people rising from their seats, arms held aloft and cheering, as a rippling, wave motion around the entire stadium.
The comparison is eerily similar, reminding me of my Symmetry of Scales discussion back in 2005.
Wall-E has a complex
The brain of any life form here on Earth is sufficiently complex that we can’t know with any absolute certainty what’s occurring inside.
Even when we have complete control of the environment and the likely sources of sensory input, and when can record the responses with total precision, we still do not fully understand the mechanics of the brain.
So how do we deal with this apparent paradox of irreducible complexity? We reduce systems into smaller components, thus reducing the complexity.
This is precisely what the University of Reading researchers have done. By controlling the size of the system — 300,000 neurons from the brain of a rat — they can be more sure of what is actually occurring because the scale of the “brain” has been reduced massively, when compared to a fully-functional rat brain, which I imagine is composed of many millions of neurons.
This small, rudimentary brain is able to remotely control a robot that looks, albeit superficially, like Wall-E, the enigmatic animated character from the Disney-Pixar movie Wall-E.
Ironically and coincidentally, one of the scientists involved is called Ben Whalley.
Mother Nature is a programmer
As a programmer I totally understand the challenges faced, even though my challenges are on a hugely smaller scale. As a programmer, I start with a brief, which outlines the requirements of the client and what actions they expect their web application to perform.
Once the brief is decided, I begin with some visual representation of their application and its component processes, which is usually in the format of a flow chart.
Once that’s agreed, I begin to write the code for the application proper, one component process at a time.
There is no start and end as such, since programming isn’t a linear process. I might start with elements which could be considered to be latter parts of the application. Sometimes, I might end the application by adding in things like a sign-in system, which is the first thing the user sees when they use the application.
I write my applications using a programming language called PHP. I use a process called OOP (Object-Oriented Programming), which essentially means that each component process might be contained within one object, or class file.
Typically, these objects accept data and return more data and / or information (information is data when it’s been manipulated in some way) in return. As these component processes are assembled, they begin to communicate with each other — each with its own unique roll, each talking to one or more other component process, broadly analogous to the regions within a brain.
As these component processes are assembled incrementally, each usually undergoes mostly small, sometimes radical changes, so that they work with all of the other component processes in a predictable, logical fashion.
Once the application is finally complete, the whole is much greater than the sum of its constituent parts. To look at the whole application as files & folders is daunting even for an experienced programmer, since there’s a level of complexity that needs to be understood — especially when things go wrong!
When things do go wrong, it’s sometimes an onerous task trying to discover the cause of the error. As has been the case in the past, I’ve had to reduce class files to smaller component processes so that I can see what’s happening.
In these situations, one by one, I go through the different parts of a function within a class object (often, there are several, which are actually called methods), strip them right down to their most basic forms and then perform tests, limiting what data goes in, so that I can see more clearly what comes out.
This is my example of reducible complexity, which mirrors in some ways what the University of Reading are doing. Once you reduce something to ever smaller parts, the mysteries contained within are revealed.
There is no magic in nature, only complexities with entirely reducible component processes, which invites the enquiry of the mind of man. Unless your faculties for reasoning are somehow compromised by your illogical desire to place faith before common sense…