The Blind Watchmaker (9 page)

Sieving of this order of simplicity is not, on its own, enough to account for the massive amounts of nonrandom order that we see in living things. Nowhere near enough. Remember the analogy of the combination lock. The kind of nonrandomness that can be generated by simple sieving is roughly equivalent to opening a combination lock with only one dial:

It is easy to open it by sheer luck. The kind of nonrandomness that we see in living systems, on the other hand, is equivalent to a gigantic combination lock with an almost uncountable number of dials. To generate a biological molecule like haemoglobin, the red pigment in blood, by simple sieving would be equivalent to taking all the aminoacid building blocks of haemoglobin, jumbling them up at random, and hoping that the haemoglobin molecule would reconstitute itself by sheer luck. The amount of luck that would be required for this feat is unthinkable, and has been used as a telling mind-boggier by Isaac Asimov and others.

A haemoglobin molecule consists of four chains of amino acids twisted together. Let us think about just one of these four chains. It consists of 146 amino acids. There are 20 different kinds of amino acids commonly found in living things. The number of possible ways of arranging 20 kinds of thing in chains 146 links long is an inconceivably large number, which Asimov calls the ‘haemoglobin number’. It is easy to calculate, but impossible to visualize the answer. The first link in the 146-long chain could be any one of the 20 possible amino acids. The second link could also be any one of the 20, so the number of possible 2-link chains is 20x10, or 400. The number of possible 3-link chains is 20 x 20 x 20, or 8,000. The number of possible 146-link chains is 20 times itself 146 times. This is a staggeringly large number. A million is a 1 with 6 noughts after it. A billion 11,000 million) is a 1 with 9 noughts after it. The number we seek, the ‘haemoglobin number’, is (near enough) a 1 with 190 noughts after it! This is the chance against happening to hit upon haemoglobin by luck. And a haemoglobin molecule has only a minute fraction of the complexity of a living body. Simple sieving, on its own, is obviously nowhere near capable of generating the amount of order in a living thing. Sieving is an essential ingredient in the generation of living order, but it is very far from being the whole story. Something else is needed. To explain the point, I shall need to make a distinction between ‘single-step’ selection and ‘cumulative’ selection. The simple sieves we have been considering so far in this chapter are all examples of single-step selection. Living organization is the product of cumulative selection.

The essential difference between single-step selection and cumulative selection is this. In single-step selection the entities selected or sorted, pebbles or whatever they are, are sorted once and for all. In cumulative selection, on the other hand, they ‘reproduce’; or in some other way the results of one sieving process are fed into a subsequent sieving, which is fed into …, and so on. The entities are subjected to selection or sorting over many ‘generations’ in succession. The endproduct of one generation of selection is the starting point for the next generation of selection, and so on for many generations. It is natural to borrow such words as ‘reproduce’ and ‘generation’, which have associations with living things, because living things are the main examples we know of things that participate in cumulative selection. They may in practice be the only things that do. But for the moment I don’t want to beg that question by saying so outright.

Sometimes clouds, through the random kneading and carving of the winds, come to look like familiar objects. There is a much published photograph, taken by the pilot of a small aeroplane, of what looks a bit like the face of Jesus, staring out of the sky. We have all seen clouds that reminded us of something - a sea horse, say, or a smiling face. These resemblances come about by single-step selection, that is to say by a Single coincidence. They are, consequently, not very impressive. The resemblance of the signs of the zodiac to the animals after which they are named, Scorpio, Leo, and so on, is as unimpressive as the predictions of astrologers. We don’t feel overwhelmed by the resemblance, as we are by biological adaptations - the products of cumulative selection. We describe as weird, uncanny or spectacular, the resemblance of, say, a leaf insect to a leaf or a praying mantis to a cluster of pink flowers. The resemblance of a cloud toaweaselisonly mildly diverting, barely worth calling to the attention of our companion. Moreover, we are quite likely to change our mind about exactly what the cloud most resembles.

Hamlet
. Do you see yonder cloud that’s almost in shape of a camel?
Polonius
. By the mass, and ‘tis like a camel, indeed.

Hamlet
. Methinks it is like a weasel.
Polonius
. It is backed like a weasel.
Hamlet
. Or like a whale?

Polonius
. Very like a whale.

I don’t know who it was first pointed out that, given enough time, a monkey bashing away at random on a typewriter could produce all the works of Shakespeare. The operative phrase is, of course, given enough time. Let us limit the task facing our monkey somewhat. Suppose that he has to produce, not the complete works of Shakespeare but just the short sentence ‘Methinks it is like a weasel’, and we shall make it relatively easy by giving him a typewriter with a restricted keyboard, one with just the 26 (capital) letters, and a space bar. How long will he take to write this one little sentence?

The sentence has 28 characters in it, so let us assume that the monkey has a series of discrete ‘tries’, each consisting of 28 bashes at the keyboard. If he types the phrase correctly, that is the end of the experiment. If not, we allow him another ‘try’ of 28 characters. I don’t know any monkeys, but fortunately my 11-month old daughter is an experienced randomizing device, and she proved only too eager to step into the role of monkey typist. Here is what she typed on the computer:

UMMK JK CDZZ F ZD DSDSKSM S SS FMCV PU I DDRGLKDXRRDO RDTE QDWFDVIOY UDSKZWDCCVYT H CHVY NMGNBAYTDFCCVD D RCDFYYYRM N DFSKD LD K WDWK HKAUIZMZI UXDKIDISFUMDKUDXI

She has other important calls on her time, so I was obliged to program the computer to simulate a randomly typing baby or monkey:

WDLDMNLT DTJBKWIRZREZLMQCO P Y YVMQKZPGJXWVHGLAWFVCHQYOPY MWR SWTNUXMLCDLEUBXTQHNZVIQF FU OVAODVYKDGXDEKYVMOGGS VT HZQZDSFZIHIVPHZPETPWVOVPMZGF GEWRGZRPBCTPGQMCKHFDBGW ZCCF

And so on and on. It isn’t difficult to calculate how long we should reasonably’expect to wait for the random computer (or baby or monkey) to type METHINKS IT IS LIKE A WEASEL. Think about the total number of
possible
phrases of the right length that the monkey or baby or random computer
could
type. It is the same kind of calculation as we did for haemoglobin, and it produces a similarly large result. There are 27 possible letters (counting ‘space’ as one letter) in the first position. The chance of the monkey happening to get the first letter-M-right is therefore 1 in 27. The chance of it getting the first two letters ME - right is the chance of it getting the second letter - E - right (1 in 27)
given that
it has also got the first letter - M - right, therefore 1\27x1\27, which equals 1\729. The chance of it getting the first word - METHINKS - right is 1\27 for each of the 8 letters, therefore (1\27) x (1\27) x (1\27) x (1\27). ..,
etc.
8 times, or (1\27) to the power 8. The chance of it getting the entire phrase of 28 characters right is (1\27) to the power 28,
i.e.
(1\27) multiplied by itself 28 times. These are very small odds, about 1 in 10,000 million million million million million million. To put it mildly, the phrase we seek would be a long time coming, to say nothing of the complete works of Shakespeare.

So much for single-step selection of random variation. What about cumulative selection; how much more effective should this be? Very very much more effective, perhaps more so than we at first realize, although it is almost obvious when we reflect further. We again use our computer monkey, but with a crucial difference in its program. It again begins by choosing a random sequence of 28 letters, just as before:

It now ‘breeds from’ this random phrase. It duplicates it repeatedly, but with a certain chance of random error - ‘mutation’ - in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which,
however slightly
, most resembles the target phrase, METHINKS IT IS LIKE A

WEASEL. In this instance the winning phrase of the next ‘generation’ happened to be:

Not an obvious improvement! But the procedure is repeated, again mutant ‘progeny’ are ‘bred from’ the phrase, and a new ‘winner’ is chosen. This goes on, generation after generation. After 10 generations, the phrase chosen for ‘breeding’ was:

MDLDMNLS ITpSWHRZREZ MECS P

After 20 generations it was:

By now, the eye of faith fancies that it can see a resemblance to the

target phrase. By 30 generations there can be no doubt:

Generation 40 takes us to within one letter of the target:

METHINKS IT IS LIKE I WEASEL

And the target was finally reached in generation 43. A second run of the computer began with the phrase:

Y YVMQKZPFfXWVHGLAWFVCHQXYOPY,

passed through (again reporting only every tenth generation):

Y YVMQKSPFTXWSHLIKEFV HQYSPY YETHINKSPITXISHLIKEFA WQYSEY METHINKS IT ISSLIKE A WEFSEY METHINKS IT ISBLIKE A WEASES METHINKS IT ISJLIKE A WEASEO METHINKS IT IS LIKE A WEASEP

and reached the target phrase in generation 64. In a third run the computer started with:

and reached METHINKS IT IS LIKE A WEASEL in 41 generations of selective ‘breeding’.

The exact time taken by the computer to reach the target doesn’t matter. If you want to know, it completed the whole exercise for me, the first time, while I was out to lunch. It took about half an hour. (Computer enthusiasts may think this unduly slow. The reason is that the program was written in BASIC, a sort of computer baby-talk. When I rewrote it in Pascal, it took 11 seconds.) Computers are a bit faster at this kind of thing than monkeys, but the difference really isn’t significant. What matters is the difference between the time taken by
cumulative
selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of
single-step selection
: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed. Actually it would be fairer just to say that, in comparison with the time it would take either a monkey or a randomly programmed computer to type our target phrase, the total age of the universe so far is a negligibly small quantity, so small as to be well within the margin of error for this sort of back-of-an-envelope calculation. Whereas the time taken for a computer working randomly but with the constraint of
cumulative selection to
perform the same task is of the same order as humans ordinarily can understand, between 11 seconds and the time it takes to have lunch.

There is a big difference, then, between cumulative selection (in which each improvement, however slight, is used as a basis for future building), and single-step selection (in which each new ‘try’ is a fresh one). If evolutionary progress had had to rely on single-step selection, it would never have got anywhere. If, however, there was any way in which the necessary conditions for
cumulative
selection could have been set up by the blind forces of nature, strange and wonderful might have been the consequences. As a matter of fact that is exactly what happened on this planet, and we ourselves are among the most recent, if not the strangest and most wonderful, of those consequences.

It is amazing that you can still read calculations like my haemoglobin calculation, used as though they constituted arguments
against
Darwin’s theory. The people who do this, often expert in their own field, astronomy or whatever it may be, seem sincerely to believe that Darwinism explains living organization in terms of chance - ‘single-step selection’ - alone. This belief, that Darwinian evolution is ‘random’, is not merely false. It is the exact opposite of the truth. Chance is a minor ingredient in the Darwinian recipe, but the most important ingredient is cumulative selection which is quintessentially nonrandom.

Clouds are not capable of entering into cumulative selection. There is no mechanism whereby clouds of particular shapes can spawn daughter clouds resembling themselves. If there were such a mechanism, if a cloud resembling a weasel or a camel could give rise to a lineage of othel clouds of roughly the same shape, cumulative selection would have the opportunity to get going. Of course, clouds do break up and form ‘daughter’ clouds sometimes, but this isn’t enough for cumulative selection. It is also necessary that the ‘progeny’ of any given cloud should resemble its ‘parent’
more
than it resembles any old ‘parent’ in the ‘population’. This vitally important point is apparently misunderstood by some of the philosophers who have, in recent years, taken an interest in the theory of natural selection. It is further necessary that the chances of a given cloud’s surviving and spawning copies should depend upon its shape. Maybe in some distant galaxy these conditions did arise, and the result, if enough millions of years have gone by, is an ethereal, wispy form of life. This might make a good science fiction story -
The White Cloud, it
could be called - but for our purposes a computer model like the monkey\Shakespeare model is easier to grasp.

Although the monkey\Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a
distant ideal
target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no longterm goal. There is no long-distance target, no final perfection to serve as a criterion for selection, although human vanity cherishes the absurd notion that our species is the final goal of evolution. In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success. If, after the aeons, what looks like progress towards some distant goal seems, with hindsight, to have been achieved, this is always an incidental consequence of many generations of short-term selection. The ‘watchmaker’ that is cumulative natural selection is blind to the future and has no longterm goal.