The picture of causality that this viewpoint evokes is one in which the only reasons for things to happen are because the Theory of Everything says so. The alternative is that the universe is doing whatever the universe does, and the stone is in a sense exploring the consequences of what the universe does. It doesn't 'know' that it will skid on grass until it hits some grass and finds itself skidding. It doesn't 'know' how to splash mud all over the place, but when it hits the puddle, that's what happens. And so on. Then we humans come along and look at what the stone does, and start finding patterns. 'Yes, the reason it skids is because friction works like this ...' 'And the laws of fluid dynamics tell us that the mud must scatter like that...'
We know that these human-level rules are approximate descriptions, because that's why we invented them. Mud is lumpy, but the rules of fluid dynamics don't take account of lumps. Friction is something rather complicated involving molecules sticking together and pulling apart again, but we can capture a lot of what it does by thinking of it as a force that opposes moving bodies when in contact with surfaces. Because our human-level theories are approximations, we get very excited when some more general principle leads to more accurate results. We then, unless we are careful, confuse 'the new theory gives results that are closer to reality than the old' with 'the new theory's rules are closer to the real rules of the universe than the old one's rules were'. But that doesn't follow: we might be getting a more accurate description even though our rules differ from whatever the universe 'really' does. What it really does may not involve following neat, tidy rules at all.
There is a big gap between writing down a Theory of Everything and understanding its consequences. There are mathematical systems that demonstrate this point, and one of the simplest is Langton's Ant, now the small star of a computer program. The Ant wanders around on an infinite square grid. Every time it comes to a square, the square changes colour from black to white or from white to black, and if it lands on a white square then it turns right, but if it lands on a black square then it turns left. So we know the Theory of Everything for the Ant's universe, the rule that governs its complete behaviour by fixing what can happen on the small scale - and everything that happens in that universe is 'explained' by that rule.
When you set the Ant in motion, what you actually see is three separate modes of behaviour. Everybody, mathematician or not -immediately spots them. Something in our minds makes us sensitive to the difference, and it's got nothing to do with the rule. It's the same rule all the time, but we see three distinct phases:
• SIMPLICITY: During the first two or three hundred moves of the Ant, starting on a completely white grid, it creates tiny little patterns which are very simple and often very symmetric. And you sit there thinking 'Of course, we've got a simple rule, so that will give simple patterns, and we ought to be able to describe everything that happens in a simple way.'
• CHAOS: Then, suddenly, you notice it's not like that any more. You've got a big irregular patch of black and white squares, and the Ant is wandering around in some sort of random walk, and you can't see any structure at all. For Langton's Ant this kind of pseudorandom motion happens for about the next 10,000 steps. So if your computer is not very fast you can sit there for a long time saying 'Nothing interesting is going to happen, it's going to go on like this forever, it's just random.' No, it's obeying the same rule as before. It's just that to us it looks random.
• EMERGENT ORDER: Finally the Ant locks into a particular kind of repetitive behaviour, and it builds a 'highway'. It goes through a cycle of 104 steps, after which it has moved out two squares diagonally and the shape and the colours along the edge are the same as they were at the beginning of that cycle. So that cycle repeats forever, and the Ant just builds a diagonal highway, for ever.
Those three modes of activity are all consequences of the same rule, but they are on different levels from the rule itself. There are no rules that talk about highways. The highway is clearly a simple thing, but a 104-step cycle isn't a terribly obvious consequence of the rule. In fact the only way mathematicians can prove that the Ant really does build its highway is to track through those 10,000 steps. At that point you could say 'Now we understand why Langton's Ant builds a highway.' But no sooner.
However, if we ask a slightly more general question, we realize that we don't understand Langton's Ant at all. Suppose that before the Ant starts we give it an environment, we paint a few squares black. Now let's ask a simple question: does the Ant always end up building a highway? Nobody knows. All of the experiments on computers suggest that it does. On the other hand, nobody can prove that it does. There might be some very strange configuration of squares, and when you start it off on that it gets triggered into some totally different behaviour. Or it could just be a much bigger highway. Perhaps there is a cycle of 1,349,772,115,998 steps that builds a different kind of highway, if only you start from the right thing. We don't know. So for this very simple mathematical system, with one simple rule, and a very simple question, where we know the Theory of Everything ... it doesn't tell us the answer.
Langton's Ant will be our icon for a very important idea: emergence, Simple rules may lead to large, complex patterns. The issue here is not what the universe 'really does'. It is how we understand things and how we structure them in our minds. The simple Ant and its tiled universe are technically a 'complex system' (it consists of a large number of entities that interact with each other, even though most of those entities are simply squares that change colour when an Ant walks on them).
We can create a system, and give it simple rules which 'common sense' suggests should lead to a rather dull future, and we will often find that quite complex features will result. And they will be 'emergent', that is, we have no practical way of working out what they are going to be apart from ... well, watching. The Ant must dance. There are no short cuts.
Emergent phenomena, which you can't predict ahead of time, are just as causal as the non-emergent ones: they are logical consequences of the rules. And you have no idea what they are going to be. A computer will not help, all it will do is run the Ant very fast.
A 'geographical' image is useful here. The 'phase space' of a system is the space of all possible states or behaviours, all of the things that the system could do, not just what it does do. The phase space of Langton's Ant consists of all possible ways to put black and white squares on a grid, not just the ones that the Ant puts there when it follows its rules. The phase space for evolution is all conceivable organisms, not just the ones that have existed so far. Discworld is one 'point' in the phase space of consistent universes. Phase spaces deal with everything that might be, not what is.
In this imagery, the features of a system are structures in phase space that give it a well-defined 'geography'. The phase space of an emergent system is indescribably complicated: a generic term for such phase spaces is 'Ant Country', which you can think of as a computational form of infinite suburbia. To understand an emergent feature you would have to find it without traversing Ant Country step by step. The same problem arises when you try to start from a Theory of Everything and work out what it implies. You may have pinned down the micro-rules, but that doesn't mean that you understand their macro-consequences. A Theory of Everything would tell you what the problem is, in precise language, but that might not help you solve it.