Magic is a peculiar thing. We know what we mean by the word – or do we? A dictionary defines it as ‘illusion and trickery’, but that’s hardly what we mean when we talk of a magical occasion. To make practical use of a word, we need to have meanings from our own experience: magic as joy, as wonder, as wisdom. (Occultists talk of mages, whilst the biblical story refers to the three Magi – wise-men). Yet even these meanings are too limiting: we need words with meanings that somehow go beyond the words themselves.
Magic, many people would say, is just coincidence. Yet the word ‘coincidence’ is itself a prime example of the same problem. To say that magic is ‘just coincidence’ is to describe one known but undefinable ‘something’ in terms of another. For many people, each word is used to dismiss the other: neither is true, neither is valid, since, by definition, a coincidence is an event of no meaning. For others, every coincidence has meaning, part of preordained fate or, for the paranoiac, a part of a deliberate plot against them and the world. A coincidence, it seems, has either no meaning at all, or far too much meaning.
But look again at the word ‘coincidence’. Literally, it’s ‘co-incide-ence’: two events coinciding, coming together in place, in time or in any other context. And that is all: the meaning, or lack of meaning, of the co-incidence is quite separate, to be derived from the context, the circumstances in which it occurs. So if someone asks you whether some event ‘was real or a coincidence’, a proper answer would be “Yes”: without knowing the circumstances, the total context in which to interpret it, there is nothing more we can say.
This is far from trivial, for everything we perceive is a coincidence of one kind or another. Our senses are geared to notice change, coincidence – and have real difficulty in ‘perceiving’ continuity. In fact, the only thing we perceive – whether sight, sound, smell, taste, touch, feeling or whatever – is coincidence, the co-incidence of events of one kind or another. What we think of as ‘reality’, the real world, is our interpretation of those coincidences.
We tend to think in terms of ’cause or coincidence’; but the idea of ’cause’ is itself an interpretation of coincidences, so the choice of one or the other is hardly valid. For example, what caused you to be reading this book? You could say that the whole of your life has been a chain of coincidences leading to this word, at this moment. And any meaning, any ‘fact’, you may derive from these coincidences is your choice, your reality.
|Thirty spokes share the wheel’s hub;
It is the centre hole that makes it useful.
Shape clay into a vessel;
It is the space within that makes it useful.
Cut doors and windows for a room;
It is the holes which make it useful.
Therefore profit comes from what is there;
Usefulness from what is not there.
Lao Tzu, Tao Te Ching
Events are what we see, ‘what is there’; the meaning is ‘what is not there’, the context, the part from which usefulness comes. Anything and everything you realise – literally, ‘make real’ – has been and still is shaped by your interpretation of events, of coincidences. In effect, what we think of as fact – literally, a ‘making’ – is our choice: we invent ‘facts’ to give meaning to those events. That’s all there ever is: coincidence and its context, information and its interpretation.
What we think of as the facts of technology are better described as practical and predictable coincidences. And magic, as many people will tell you, is only coincidence. Just coincidence.
Working in the world
But to work within the world, we have to start somewhere. In this culture, it seems, most people would start by saying “Can’t we explain this scientifically?” But this carries with it the assumption that everything is amenable to a scientific study – and this is itself a main component of our difficulties with working in the world, as we shall see later. Since we are dealing with people rather than abstract ideas, we need to start from where those people – you and me – are; we need to start with ways of working on the world, our skills at operating within the world.
Many skills we tend to ignore: yet walking, speaking, writing, reading and the like are all learned skills. Operating many kinds of machinery – a bicycle, a telephone, a car – is so much a part of us that we tend to forget how much we have learned, how many coincidences relating to them we have learned to interpret. For example, pressing one foot hard on the floor is hardly a natural response to danger, and yet that’s what you learn to do when faced with danger in a car – and you’ll find yourself doing it even if you’re not driving! The ‘explanation’ of what you do, and why you do it, says as much about you as it does about the processes in which you’re involved: in any skilled work, the same results may be achieved in totally different ways, according to how each person approaches the tasks in hand.
Learning a skill is a magical process, in many ways. A skill, in effect, is how each person resolves for themselves the mechanics of the skill – the ‘real world’ – with the way in which they approach it. Technology is what we see as the outward form of skills; and magic, perhaps, is the inner form. We’ll be looking at this in more detail later on; for now, let’s limit ourselves to the way in which coincidence and its interpretation form a key part of skills, and thus of technology as we see it in practice.
We should remember that we need to see this in practice: it’s all too easy to drift off into a sterile discussion of theory without any practical grounding. So it’s useful to keep some practical examples in mind. To keep up the idea of technology or magic for the moment, we’ll use as examples, throughout this study, a skill from each side: the harsh world of computer programming, and the perhaps more dubious world of dowsing, or water-divining. What is interesting is that, by the time we’ve finished, you’ll probably see that they turn out to be much the same: the way in which they work is surprisingly similar.
Let’s start, then, with a (very) brief summary of what each skill involves.
For some people, the computer represents the ultimate de-humanising force in current technology; so it’s worth remembering that a computer is only a tool. The English term ‘computer’ is confusing, since most computers – such as the one I’m using in writing this study – do very little computing, or ‘number-crunching’, at all; the French term ordinateur – literally, ‘an orderer’ – describes the process much better. A computer is, in effect, a very fast but very stupid idiot: a logic machine, following logical rules or instructions, made up in a sequence that we call a ‘program’.
Each set of rules is usually built up on top of other layers of rules: a programming language, then the ‘operating system’, machine-language below that, and so on, right down through the logic built into the processor, to the simple logic of switches – two states, on or off.
Within the terms of the logic, everything a computer does is ‘true’. But whether it is appropriate, or useful, is quite another matter.
But let’s start by looking at the basic principles. And if we keep it to the bare essentials we can break it down to just five concepts.
The first is the idea of doing things in sequence. (Parallel processing, which is essential for handling anything happening at speed in the real world, handles many sequences simultaneously, passing results and instructions from one strand to another). One instruction is given, then another, then another – in some cases, millions of times a second.
The second key principle is the idea of naming things: ‘if you don’t know what it is, give it a name’. (This is a key principle taken from algebra: that mysterious character called ‘X’, for example, who was somewhere between 1 and 3 – or, more accurately, ‘X’ holds a number between 1 and 3.) Once named, this store or ‘address’ can hold some value, which might remain constant or be varied – as a ‘variable’ – by some other process, and can be referred to by its name. (Many programming languages, such as Pascal and C, need these names to be formally ‘declared’ within the program; other languages, such as most versions of BASIC, allow you to allocate names at whim; but the principle of something given an arbitrary name for practical convenience is common to all.) The value stored in this named place is just a value: what it means – as a number, a letter, a place, a pointer, a reference or whatever – depends on the context. It’s just information, waiting for the context to give it its meaning.
Which leads us to the third principle: an instruction can imply some operation, some context, using these stores by name. (An instruction is itself something that has been given a name; a programming ‘language’ is a convention describing a list of named instructions and their use.) Most of these instructions are exceedingly trivial – it’s only the sheer speed of processing that gives the computer program any semblance of intelligence. A typical operation might be to copy a value from one place to another, or to compare two values – almost the limit at the base-level of many processors – or, in a ‘higher’ level of logic, to show some value on the screen.
The next key point is the idea of ‘perhaps’: a logic decision, given in most programming languages as an 'IF ... THEN ... ELSE ...' structure – ‘if so-and-so is true, then I’ll do this, else I’ll do that’. The context is built up logically, layer upon layer, with each decision made logically upon the context already defined by other instructions, other operations; these decisions thus become the apparent ‘intelligence’ of the program.
Finally, we have the idea of ‘do it again’: we can break the sequence – usually after a ‘perhaps’, a logic decision – and start the sequence from another place, repeating instructions and skipping over others.
And really, that’s all there is to it: layer upon layer of logic based on these five concepts. For example, here’s a short program using terms from the programming language ‘BASIC’:
10 LET X=1
20 PRINT SPACE$(X) "Hello there!"
30 LET X=X+1
40 IF X<10 THEN GOTO 20
50 PRINT "That's a very basic piece of BASIC"
It doesn’t matter if you haven’t come across BASIC before: all that matters is that if you type this sequence of instructions on a suitable computer, and then type RUN, it produces this result on the screen:
That's a very basic piece of BASIC
And yes, it is a trivial program.
You can see that we have a sequence: in this case, the line numbers, from 10 to 60. Each line consists of one or more named instructions.
Line 10 puts a number into a store which we label X.
In line 20 we use the current number in that store to tell the SPACE$() instruction how many spaces to print, followed by the words ‘Hello there!’.
In line 30 we add 1 to the number currently stored in X, and put the result back in X –
so the number increases on each pass.
In line 40 we use that stored value to decide – depending on whether it is still less than 10 – to ‘do it again’ by going back to line 20 or to move on to line 50. Note that 'Hello there!' is only shown nine times – the question in the instruction is ‘Is X less than 10?’.
And in line 60 we say that the sequence has ended, so that another layer of logic – the ‘operating system’ level – can take over.
Note how the meaning of the value stored in the place labelled X has different meanings at different points in the program: its meaning, its use, depends on the context in which it is used.
This example is trivial: it doesn’t do anything useful. But as with all computer programs, it’s a set of made-up rules; the skill of the programmer is in making up sets of rules that do do something useful. As we’ll see with dowsing, the question is not whether a program is ‘true’ – which it must be, by definition, since a digital computer of this type can only make true/false decisions of logic – but whether the rules it is given actually relate to the real world we experience. As with dowsing, the rules need to relate to the world in a way that is efficient, reliable, elegant (if you like), and, above all, appropriate: a way that relates to people. Otherwise, there’s no point – an exercise in expensive and sometimes dangerous triviality.
You’ve possibly seen dowsers in action, or played with it yourself at some point in the past. In principle, you wander around with some kind of instrument – traditionally a hazel twig, but nowadays more often a couple of bent wires or a bob on a thread – looking for something or other. When you stand over what you’re looking for, the instrument reacts: the hazel rod bends up or down, the bent wires cross over, the plumb bob or ‘pendulum’ describes a circle hanging on its thread. In other words, the response marks the coincidence of what you’re looking for and where you are.
The reaction of the instrument is in fact its reaction to your hands moving; and your hands move because you tell them to. Not consciously, but as a reflex response to something or other – undefined. If you like, your hands move in response to a set of rules which you invent, which state that they should move when that coincidence occurs. It’s much the same as with riding a bicycle: you direct the process rather than control it. Indeed, if you do try to control it by deliberate action, you’re more likely to make a mess of it than if you leave it to ‘work itself’.
In essence, that’s all there is to it; which is why many people think that there is nothing to it. They can’t understand how anything so simple could work, therefore it can’t possibly work.
Which is to miss the whole point. Perhaps the shortest summary of the skill is to say that dowsing is entirely coincidence and mostly imaginary: and the catch with that, as we’ve seen, is that it depends on how you interpret those two words. Literally, the dowsing reaction marks the coincidence of what you’re looking for and where you are; and both of those things – what you’re looking for, and where you are – are defined by images, by descriptions, by imagination.
You decide what you are looking for, by describing it as an image. Traditionally, this was done by holding beside the rod a sample of the sought-for material – a sample of water, or coal, perhaps, or some other minera; but unless you insist that dowsing is the sensation of some as-yet-undefined ‘radiations’ (for which there is, of course, no scientific evidence), there is no structural difference between holding a physical sample, and holding a written label, or a drawing, or even just a description of it in your mind’s eye. Conceptually, they’re all images.
Imagination is a powerful tool: we often forget how powerful. For example:
|Imagine that there’s an orange on the table in front of you. (You choose what kind of orange it is: it’s your choice, you’re making up the rules here). You can see, in imagination, its colour and texture; see the way the light shows the dimples on its surface.
Reach out and touch it; take some time to feel its surface, let the texture and weight describe itself to you.
Now dig your fingernails in; feel and smell and sense the orange as the zest in the pith bursts out.
Remove the skin, slowly, carefully; break the orange into its segments.
Now put a segment into your mouth; feel the texture, then bite into it; taste the juice as it breaks through.
Even though it’s entirely imaginary, your senses will be at least part-convinced that it’s real… very real… So is it real, or imaginary? You’ll find that the only accurate answer here is “Yes”…
Now do the same with an imaginary sewer-pipe… you’ll see just how powerful these images can be! It’s all imaginary, and real at the same time – in an imaginary sense. And you can use that sense of reality to match what you’re looking for; to note the coincidence between this image and the ‘real’ world.
You’re also using images to describe where you are, the current position of ‘here’. In basic dowsing, your ‘here’ is marked by where you stand: the rod (or whatever) moves when you stand over what you’re looking for. Yet that’s not all that practical when you’re looking for something in a wall; so you change the rules, and say instead that ‘here’ is where you are pointing to. Then you can change the rules again, and say that, having marked the point above what you’re looking for, you’ll now get another reaction at the same distance away from that point as the object is down: ‘distance out equals distance down’, sometimes referred to in traditional dowsing as the ‘Bishop’s Rule’. Yet it’s a made-up rule: it’s a convenient image to describe something, rather than a ‘fact’ as such.
Follow the operational logic of that, and you’ll see that there’s no structural difference between someone out in a field dowsing with a hazel rod, and someone else looking for the same thing using a pendulum and pointing to various places on a map. A difference in degree, it’s true, and probably a considerable difference in reliability; but no structural difference.
In both cases, people are following rules that they have invented, to pre-limit the meaning of the coincidence that the rod or pendulum marks. It’s a significant point that dowsing instruments have a very limited range of responses: it’s easier to pre-limit the range of possible ‘answers’ – coincidences – in that way. In effect, you declare in dowsing that a coincidence shall have a particular meaning, and then set up conditions under which that coincidence can occur: if you like, you program the circumstances to have that particular meaning.
The catch comes in how well you can set up the conditions, so that a given coincidence does have the specific meaning you’ve declared. The point is not whether the reaction is ‘true’ – which it is, by definition, if you think about it – but whether it’s useful: the key questions in dowsing are about whether the method being used is efficient. reliable, elegant (if you like), and, perhaps most important, whether it is an appropriate tool for the job in hand. And the answers to these questions depend on the people involved, not on the outer form of the technology.
In both dowsing and programming, the rules we use are not pre-defined: we make them up. We choose to follow certain rules, for convenience and for useful convention to be able to discuss our results with others: but that is a choice, not a requirement. If you like, we use those rules to explain to others how we work. Yet within reasonable limits, anything goes.
But what are those ‘reasonable’ limits? And what do we mean by ‘reason’ anyway? It all depends, I suppose, on your point of view: it all depends on how you choose to explain things.