How things come to be as they are
Something it’s important to understand about me is that I read Susan Blackmore’s “The Meme Machine” at a formative age, and it infected all my thinking. This wasn’t helped when, much later, I read Steven Johnson’s “Where Good Ideas Came From” and it convinced me that I was 100% right about how all of this worked. Fortunately, the resulting foundational beliefs are in fact true, so that’s OK. Obviously I am completely unbiased in saying this.
Anyway, let me tell you the truth underpinning everything.
Sorry, that was very grandiose as promises go. I’m not about to introduce you to any deep mystical secrets. I’m just here to talk to you about the theory of evolution.1
The theory of evolution in its most general form is this:
(Sometimes) new things spontaneously come into existence through one or more mechanisms.
Things stop existing, either through attrition or through more active destruction.
New things are created based on modifications or combinations of one or more things that already exist.
Over time, the things that exist will tend to be the ones that are:
Likely to be created.
Less likely to stop existing.
Likely to be used as the basis for future things.
This is what we mean by “natural selection” in the context of your classic biological theory of evolution: Organisms get killed, organisms breed, and the organisms you see in the wild are the ones that are better at not dying before they have babies.
It is, however, much more general than that. In contrast, it happens all the time in non-biological replicators. For example, Dawkins’s notion of “memes” is that ideas are replicators - they die off, new ideas are based on old ideas, etc. This is explored in more useful depth in Steven Johnson’s “Where good ideas come from”.
In my general evolutionary algorithm I had a “things are spontaneously created” step, which you don’t see much in biological evolution discussions when not talking to creationists. It did happen once, but biological life is super complex so generally it’s much much easier to build on your existing versions than create new ones. It’s also useful to think of invasive species this way - you have a closed ecosystem of biological evolution, then a new organism is “created” in it (introduced from outside the context of the system).
In contrast, this happens all the time with non-biological replicators. Memes for example are very often “spontaneously” created from the point of view of the memetic system, because things happen in the physical world. From the mountain comes the idea of the mountain, and a whole new lineage of memes about its significance.
Pretty much any collection of objects is useful to think of through this lens. You can, for example, regard technologies as an evolving system just as easily:
People create new technologies based on new discoveries.
Technologies die off as they become no longer useful, or superseded by new technologies, and people stop using them.
People create new technologies based heavily on existing ones.
e.g. mobile phones are a “species” of technology, where you can see clear lineages of design as people have based their designs for phones off previous designs.
Sadly, whatever selection pressures we’ve got currently got going on for mobile phones seems to favour the survival of increasingly large and unwieldy generic black rectangles. I’m not sure what’s going on there, but from an evolutionary point of view there’s almost certainly some advantage.
Such an advantage doesn’t necessarily have to be any of the users mind you. Dawkins’s2 notion of a selfish replicator (in the original case, genes and organisms) applies: Phone users play host to the replicating phones, and part of that is because they find phones useful, but that doesn't mean that the phones are seeking to benefit the user. They just "want" to replicate, and will help the user to the degree that it helps them do so.
Economists have a notion of “revealed preferences” - what preferences your actions exhibit, separate from how you behave. I think this is a misleading term, because it suggests that you in some sense deeply want those things. What’s actually happening is not your revealed preferences, but what selection pressures you exhibit on the things you are choosing between.
For example, the phones situation could emerge because:
Some large fraction of users don’t care about phone size but do care about features.
Everyone else needs a phone.
All else being equal, companies would prefer to produce fewer phones, because it reduces manufacturing costs, so if one phone is 5% more profitable than another, the less profitable phone gets the axe.
This results in a situation where smaller phones are more likely to die off than larger phones, so phone sizes get bigger.
Another way this could emerge is if there is prestige among industry insiders to produce the coolest specs for phones, so people are more likely to copy the top end specs than the bottom end specs, giving larger phones an advantage at the replication stage, not the survival stage.
Here we’re running into a problem that you inevitably run into when you use evolutionary explanations: It’s very easy to tell just so stories, because there are so many plausible mechanisms. Possibly it’s both of the above, possibly it’s neither, probably it’s maybe a bit those and a bit some other things. It would require a lot more careful study than I’m prepared to do in this essay.
You see this a lot when people try to do evopsych (evolutionary psychology) - you can pretty much make up any explanation you want for why the ancestral environment makes inevitable the specific social patterns you happen to see in your local cultural context as inevitable feature of human nature that definitely happens everywhere and not just in the united states (or wherever you happen to be currently3).
You also see this a lot in biological evolution. Why do giraffes have long necks? Bunch of reasons. Teleology is fake, so there isn’t a straightforward “why”. Things come to be as they are because those are the patterns that thrive, and they thrive due to a combination of factors. This is especially true because of exaptation, where things that are selected for for one reason become useful for something else and start being selected for that too. Bird feathers are the example everyone uses for this - they weren’t originally for flight - but Giraffe necks probably have some element of this too. A non-biological example is that the behaviour of carrying mobile phones around was originally driven by the need to make and receive phone calls, but is now largely driven by compulsively checking how many likes your tweet got (or other similar behaviours).
Pretty much everything you see evolves, in that everything is a pattern in the world that dies off over time, and everything that persists while individuals are dying off must be recreated.
Often there isn’t much very overt selection or lineage at first glance, but there is when you take into account coevolution. For example, did you know that rocks plausibly evolved, due to the role of life in creating them?
You can see similar patterns in landscape. Land supports life, and life shapes land. If you reintroduce wolves, they eat the large herbivores, which improves foliage, which reduces soil erosion, which strengthens and reshapes rivers…
Depending on how you look at the existing pool of replicators, you can think of most things as coevolution rather than “direct” evolution, and it’s just a question of what level of abstraction you’re looking at. e.g. memes don’t “really” evolve, in that what you see are instead behaviours that replicate. But memes drive behaviours, and behaviours generate memes. So to the degree that a meme is a replicator, so is a landscape.
At the most general level, what evolves are patterns in the world. The world consists of an endless interlocking collection of patterns, each driving the evolution of other types of pattern, and being forced to evolve in turn, and thus things come to be as they are, with the patterns that are selected for persisting and replicating being the ones that flourish.
Sorry, it’s all gone a bit mystical again.
The thing you may be noticing in the above is that it is a very general theory, that is very good at generating specific plausible stories about how things came to be, and that actually checking if any of those stories is true is extremely hard.4 This makes it somewhat hard to use well, and easy to use badly, if what you're looking for is a specific explanation of how things came to be as they are.
It can still be useful, as these partial explanations give you way to explore the problem, and sometimes it will be worth looking for evidence for and against an explanation. It’s also useful in that it can be helpful evidence that you’re missing something if you find yourself in a situation that seems to make no sense with regards to this theory.
It’s also good at explaining various structural patterns of the world even when you’re not clear on the details. For example, inheritance tends to be better at building complex and sophisticated “organisms” than spontaneous creation, so initially you’ll see lots of novel designs, and then over time as the winning patterns become better and better adapted to their environment, it becomes much harder for entirely novel entry points to occur, so everything inherits from a much smaller number of lineages. You see this in biological evolution - the animals of the Burgess shale were weird - by modern standards, but you also see it in other contexts too. We went through a lot of different types of mobile phone designs initially, but now ~everything is a black rectangle.
But the most helpful feature of this sort of reasoning in my opinion is that it works much better as an action generator than it does as a source of explanations. You can generate these just so stories, and then you can decide how you would behave if they were true, and you can just try those actions and see what happens. Whether or not those actions work is evidence in favour or against of your theory, but only relatively weak evidence given how messy evolutionary systems tend to be, but this doesn’t matter so much as whether they’re useful actions.
Additionally, you can always introduce new mechanisms that in some sense “must” work under this pattern - if things are not as you want them to be, you can introduce new mechanisms that cull them (e.g. you can learn to notice behaviours you don’t want and stop them), you can introduce mechanisms that spontaneously introduce new things (e.g. borrowing approaches from other traditions), or you can try to promote the growth of things that you want to see more of (focus your time and energy on things you want to see more of).
This also ties in in important ways with How to understand groups of people. The behaviour of a group is very much subject to this sort of evolutionary development, and you need to think in these terms in order to keep a community healthy - what brings people in, what causes them to leave, and how the behaviours within the community proliferate and change each other.
In many ways, this ties in well to the origins of evolutionary theory itself. I’m partial to the theory that the agricultural revolution was critical in the development of evolutionary theory. Evolution is much easier to understand in controlled domains - we can start from, and shape, evolution in the wild, but more artificial environments make the evolutionary mechanisms more obvious.
Understanding how evolution works is key to understanding how things came to be as they are, but it’s also a tool through which we can make them more as we want them to be.
In another sense, the theory of evolution is in fact a deep mystical secret.
Sorry, it’s impossible for me to write this article without mentioning Dawkins.
But if you’re doing this I give you 80% chance of being an American, and 15% that you talk to too many damn Americans.
In some sense this has to be true of any theory of everything, right? If you have a fully general theory then either it has to be hard to generate specific explanations from it, or it has to be hard to test those explanations, because otherwise science would be easy, and it’s not.