Chaos and antichaos

Natural selection only works on what already exists, and we need therefore to understand what is it that “creates” novelties in life. An answer to this question comes from the ancient words of Democritus – “everything in the Universe is the fruit of chance and necessity” – which gave Jacques Monod the title of his famous book (1970) and its main thesis: “chance alone is at the source of every innovation, of all creation in the biosphere. Pure chance, absolutely free but blind, is at the very root of the stupendous edifice of evolution”.
Ernst Mayr, one of panselectionism’s founding fathers, sharply reprimanded Monod for not accepting that natural selection works at all levels, including the molecular one, and is the one and only source of novelties for all living creatures. In The Growth of Biological Thought (1982), and later in One Long Argument (1991), Mayr delivered his charge with blunt clarity: “Monod failed to understand the explanatory power of natural selection and opted for pure chance as having been responsible for the phenomena of nature. Such Epicureanism, however, is only rarely encountered in modern times”.
To Mayr’s rhetoric, however, neatly replied Kimura’s mathematics with the demonstration that “at the molecular level most evolutionary change and most of the variability within species are not caused by natural selection but by random drift”. This takes us to a unique conclusion: at the molecular level evolutionary novelties can be created either by the chaos of genetic drift or by an antichaos mechanism which is not natural selection.
Experience has taught us that we must firmly reject all forms of antichaos that have been proposed in the past, because they invariably ask us to give up understanding and embrace mystery, but this does not mean that we must abandon a rational search for an antichaos that could really exist in nature. Our best guide, in this endeavour, is again mathematics, and here we will turn once more to the reconstruction method.
A particularly useful hint comes from the very simplest of the algorithms that were described in Chapter 3 (Density Modulation).