Knowing What We Know, part 1: "Patterns"

The first book on physics I ever read was Stephen Hawking's A Brief History of Time. It's actually the book that catapulted me from a sort of weak theistic agnosticism into full-on atheism. It wasn't that I thought Hawking had disproved the existence of God or anything like that, but it was the thought process that intrigued me – he bravely took certain "big questions" out of the realm of mysticism and into the quantifiable world of science. This was also the book that introduced me to the famous double-slit experiment in quantum mechanics. In the experiment, a particle does not take one path from A to B, but rather all possible paths simultaneously. That's a profoundly counter-intuitive idea, one that's even more counter-intuitive than the weirdness of things like gravitational time dilation from Einstein's General Relativity.

Our minds play tricks

We tend to view the world from a rather insular kind of bubble. We're bombarded with a massive amount of sensory data which our brain constructs into a reasonably reliable model that we call "reality". We develop an intuitive understanding of the world, where we assume that things are going to work a certain way. We don't test every inch of ground before we step on it to make sure we won't fall through. We know from experience that if we let go of something, it will fall to the ground – and we don't bother making sure that applies to every object we encounter. In case you were wondering, cognitive psychologists have a name for these assumptions – they're called "intuitive physics".

Strange things like gravitational time dilation and the double-slit experiment are a big slap in the face to our intuitive understanding of reality. Like an optical illusion, we've learned that the model of reality that our brain gives us, while generally useful for our everyday frame of reference, isn't particularly reliable as a model of how things really work. Not only do some things completely defy our intuitions the way quantum mechanics does, but even on our everyday scale we find that our brains aren't always as reliable as we'd like to believe.

Here's a simple thought experiment: have you ever been driving down the road and slammed on your brakes as an animal scurried in front of your car... just before you realized that it wasn't an animal at all, but a leaf tumbling in the wind? Have you heard sounds that you believed were voices or footsteps, but turned out just to be your house creaking in the wind? Have you ever mistaken a shadow for a sulking prowler or a shy animal? Most of us have many such experiences. In every case, we are making a pattern-recognition error: we are subconsciously imposing a pattern of goal-oriented behavior where there is nothing but randomness.

Now, try to think of the opposite: have you ever mistaken an animal for a tumbling leaf? A voice for the howling of the wind? A prowler for a shadow? We do make such errors, but we make them far less frequently. To the gazelle, it's much safer to mistake the lazy teetering of the grass for a lion – and run away – than to mistake a hungry lion for the lazy teetering of the grass. Similarly, we're much better off if we mistake a prowler for a shadow than vice-versa. From a survival standpoint, it's far better to impose a pattern when it does not exist than it is to fail to see a pattern where one does exist.

A canvas of patterns

Our intuitive model of reality is a canvas of patterns. We see patterns in nature, patterns in behavior, patterns in events – even patterns in our minds. We can think of these patterns as the raw sensory data that bombards us every day. But what are these patterns? Why do they work the way they do? Which ones are real, and which ones are we mistakenly imposing upon the randomness of reality? How can we know the difference?

Science, at its most fundamental form, is a methodology by which we attempt to explain these patterns. We try to explain them by positing a mechanism. If we are correct in our understanding of the mechanism, it will do two things: First, it will explain the patterns we have already seen. Secondly, it will predict what specific patterns we will observe in the future.

Of course, we humans are quite imaginative, and we didn't have to wait around for science to start positing various mechanisms to explain the patterns we see. Primitive mechanisms have always tended to be rather anthropomorphic conceptualizations of ethereal beings, from gods to ancestral spirits. Animistic cultures, for example, do not believe that what they observe in nature is random, but the product of intent by conscious spirits of nature. It is certainly possible that gods or spirits are in control of the patterns we observe and experience. But that's not a particularly useful explanation; in order to move from possible to plausible we have to have a mechanism that is reliable – it doesn't just explain what we do see, but what we will see. This is what is meant when a mechanism (i.e., a theory) is falsifiable. If a we posit a mechanism that predicts a certain pattern but we subsequently observe a different one, the mechanism is falsified – it must be either reworked or discarded entirely. If a mechanism is unfalsifiable, that means it does not make any predictions about the patterns we should see, and thus cannot be tested for reliability.

Unintelligent design

I discussed an example of this in an old post about Intelligent Design back in the early days of this blog. Like evolution by natural selection, ID also posits a mechanism to explain the diversity and complexity of life. ID advocates insist that they are looking at the same data as evolutionary biologists, and simply making a different inference – that it was a conscious being instead of natural processes. But this mechanism has a fatal flaw: it is unable to predict the patterns we ought to see. For example, evolution predicts that species evolve according to the specific pattern known as the phylogenetic tree of life. Species on one "branch" will share more of their DNA than species on separate branches.

That post was called "Chicken Teeth", which was used to make a point: chickens have latent genes for producing teeth. Humans have latent genes for producing functional tails. Whales and dolphins have latent genes for producing functional limbs. We call these genes "junk DNA" – they're present in the genetic code, but they don't appear to do anything. Jellyfish and bacteria, despite both being fully modern animals, do not have latent genes for producing teeth, tails or limbs because they evolved on completely separate branches of the tree of life. So we can see that evolution by natural selection not only fully explains the presence of specific kinds of junk DNA, but also tells us what kind of junk DNA we should see – animals should always retain the DNA specific to their branch of the tree of life. ID is left to speculate about the motives and characteristics of the designer to retroactively account for this information.

This concept is of pivotal importance to the philosophy to which most atheists hold, and which is the backbone of all scientific inquiry: methodological naturalism. People often claim to possess knowledge about the fundamental nature of reality, and often attribute this knowledge to intuition, emotion, experience, or authority. But how can we really know which of our experiences are reliably true? How do we know whether the patterns we observe or the experiences we have correspond to a metaphysical reality rather than being mere projections and pattern-recognition errors?  As the weirdness of the quantum double-slit experiment showed, we can't always trust our intuitions.

Part 2: "Congruence"


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