First of all I strongly object to the use of the word ‘information’ in this article. There is no limit on the amount of information in the gene if by information we mean anything like Kolmogorov complexity. Any extra random string of bases that get tacked on to the DNA sequence is information by any reasonable definition. If you mean something like Shannon’s entropy then things are just totally unclear because you need to tell us what distribution you are measuring the information of.
As far as the actual conclusions your post is too unclear and nonrigorous to really make sense of so I’m going by the paper a commenter linked to by MacKay so if your arguments substantially differ please clarify.
The first problem in MacKay’s analysis is his model of fitness as being distance to one particular master genome. This is a good model if the question is how much information could god convey to someone who just got to see the bitstring of human DNA and no other facts about the universe by appropriate selection of physical laws but doesn’t seem particularly related to what we usually mean when we informally talk about an organisms complexity. What we want to know is not how quickly convergence could be driven to a particular pre-selected bitstring but how quickly complex functionality could be evolved.
The second problem in MacKay’s analysis is that he assumes sexual mating occurs at random. It is easy to give a counterexample to his bound in a society where people choose mates wholly on the basis of their fitness (i.e. in his model distance from the ideal bitstring).
I’m not going to go any further because I have other things to do now but while it’s an interesting little mathematical toy many of the other simplifying assumptions seem questionable as well. In particular what I would primarily derive from this work is the importance of meta-systems in evolution.
Yup, if we all mated at random it would be tough to evolve. Hence we choose mates based on our estimation of their evolutionary fitness. Similarly with easy to modify control sequences affecting gene traits.
No, No, No, No!!
First of all I strongly object to the use of the word ‘information’ in this article. There is no limit on the amount of information in the gene if by information we mean anything like Kolmogorov complexity. Any extra random string of bases that get tacked on to the DNA sequence is information by any reasonable definition. If you mean something like Shannon’s entropy then things are just totally unclear because you need to tell us what distribution you are measuring the information of.
As far as the actual conclusions your post is too unclear and nonrigorous to really make sense of so I’m going by the paper a commenter linked to by MacKay so if your arguments substantially differ please clarify.
The first problem in MacKay’s analysis is his model of fitness as being distance to one particular master genome. This is a good model if the question is how much information could god convey to someone who just got to see the bitstring of human DNA and no other facts about the universe by appropriate selection of physical laws but doesn’t seem particularly related to what we usually mean when we informally talk about an organisms complexity. What we want to know is not how quickly convergence could be driven to a particular pre-selected bitstring but how quickly complex functionality could be evolved.
The second problem in MacKay’s analysis is that he assumes sexual mating occurs at random. It is easy to give a counterexample to his bound in a society where people choose mates wholly on the basis of their fitness (i.e. in his model distance from the ideal bitstring).
I’m not going to go any further because I have other things to do now but while it’s an interesting little mathematical toy many of the other simplifying assumptions seem questionable as well. In particular what I would primarily derive from this work is the importance of meta-systems in evolution.
Yup, if we all mated at random it would be tough to evolve. Hence we choose mates based on our estimation of their evolutionary fitness. Similarly with easy to modify control sequences affecting gene traits.