(Review intended for Nature)
Paul Marsh KBS MSc
The main subject that is tackled in this book is the description of the processes that can lead evolution from simple replicating molecules to an organism such as an elephant. Dawkins tackles much of his argument as a counter argument to someone who does not believe in evolution, for example religious fundamentalists. This is what really places the book in the popular science market rather than a more specialist field. In fact it shows that Dawkins is particularly aggravated by these views.
For people with more rational, scientific views, the book contains a number of interesting arguments. The core one is that evolution is able to produce complex organisms by progressing in small steps or up a steady slope of change rather than trying to scale a whole proverbial ‘mountain of probability’ in one go. The reason why it has been able to produce this complexity is because of the length of time it has been operating and the power of the natural selection process.
There are several major arguments developed over a chapter which are used to support small step evolutionary change and other ideas. One of these is the evolution of the eye which is estimated to have evolved over at least forty times independently. Dawkins takes us through each manifestation of an evolving eye, suggesting plausible uses for each structure at each stage. In fact the central idea here is that without a beneficial use at each stage a mutation which may eventually lead to a more complex and functional structure will not survive in a population over time. Being detrimental reduces the survival chances of an organism and hence essentially removing the gene for a given characteristic from a species. Evolutionary adaptation can not degrade in order to improve but must always be functional.
One of the most interesting points about the book is that computer software simulation is used to back up some of the ideas developed. In the past it has only been possible to understand evolution from researching on fast breeding organisms or using the fossil record. Dawkins makes use of computers which are able to simulate changing populations with genetically defined characteristics. Admittedly these will be very simple agents but it is possible to gain an understanding of some of the more dynamic principles. There are several programs described in the book.
Curiously one of the final chapters in the book concerns the “Robot Repeaters’. It describes the necessary steps in constructing machines that are physically able to reproduce themselves. Although this is an enormous task it may be one of the goals of fields such as artificial intelligence. It is then suggested that this is what organisms are, with the analogy of a Duplicate Me program. Dawkins, in previous books, has introduced the idea that the units of reproduction devices, essentially genes, are selected to try and promote themselves over helping the survival of other useful genes in an organisms DNA. However it is possible for genes to be promote each other which allows co-operation between large numbers in one collection hence a full length of DNA. ‘An elephant’s genes are like a gigantic colony of mutually supportive viruses’.
The purpose of the discussion of repeaters now becomes apparent. Closer parallels are drawn with machinery to explain how the difference between co-operative organism building pieces of DNA, and uncooperative parasitic viruses.
Dawkins final example is a discussion of the intricate relationship between the fig and the wasp. This is a classic example of two species that have evolved to depend on each other one for food and the other for reproduction. Dawkins explains why it is possible when it may be asserted that natural selection would not produce such interdependencies, which make organisms reliant on each other.
This book leaves one with the impression of a well thought out and structured scientific argument at every stage. Many of the topics have been at least partially covered in previous books. For those who have already read them the new set of examples will be worth reading as they are all well described. The introduction of parallels with modern technology is also interesting, although it does show that this is not the authors area.
The overall task Dawkins is trying to achieve is to educate the reader in the process of evolution. His main idea is that evolution is essentially a small step, hill climbing algorithm and so has some of the limitations and characteristics of all hill climbing. In this case the landscape is not one of error but more one of possible improvement, with the valleys being simple organic structures and the hill tops being complex organisms or indeed parts of organisms. Continuing research in the field, especially from new computer technology, seems to be giving credibility to this theory.
Paul Marsh, COGS Department, University of Sussex is a student on the MSc Knowledge Based Systems course.