Measuring the information-theoretic optimizing power of evolutionary-like processes
Intelligent-Design advocates often argue that the extraordinary complexity that we see in the natural world cannot be explained simply by a ‘random process’ as natural selection, hence a designer. Counterarguments include:
(seemingly) Complicated and complex phenomena can often be created by very simple (mathematical) rules [e.g. Mandelbrott sets etc]
Our low-dimensional intuition may lead us astray when visualizing high-dimensional evolutionary landscapes: there is much more room for many long ‘ridges’ along which evolution can propagate a species.
Richard Dawkins has a story about how eyes evolved in step-like manner from very primitive photo-receptors etc. In this case he is mostly able to explain the exact path.
To my eyes these are good arguments but they certainly are not conclusive. Compare:
Stuart Kauffmann has a lot of work ( see ‘At Home in The Universe’) on which kind of landscapes allow for a viable ‘evolution by natural selection’. Only some landscapes are suitable, with many being either ‘too flat’ or ‘too mountainous’. Somewhat hilly is best. Most systems are also too chaotic to say anything useful
Population geneticists know many (quantatitive!) things about when different evolutionary forces (Drift, Mutation, Sexual Recombination) may overwhelm natural selection
Alan Grafen has a fairly precise mathematical framework that he says is able to determine when Darwinian-Wallacian evolution is maximizing a ‘fitness function’. Importantly, not all situations/ecosystems can support the traditional ‘survival of the fittest’ interpretation of evolution
The take-away message is that we should be careful when we say that evolution explains biological complexity. This might certainly be true—but can we prove it?
Measuring the information-theoretic optimizing power of evolutionary-like processes
Intelligent-Design advocates often argue that the extraordinary complexity that we see in the natural world cannot be explained simply by a ‘random process’ as natural selection, hence a designer. Counterarguments include:
(seemingly) Complicated and complex phenomena can often be created by very simple (mathematical) rules [e.g. Mandelbrott sets etc]
Our low-dimensional intuition may lead us astray when visualizing high-dimensional evolutionary landscapes: there is much more room for many long ‘ridges’ along which evolution can propagate a species.
Richard Dawkins has a story about how eyes evolved in step-like manner from very primitive photo-receptors etc. In this case he is mostly able to explain the exact path.
To my eyes these are good arguments but they certainly are not conclusive. Compare:
Stuart Kauffmann has a lot of work ( see ‘At Home in The Universe’) on which kind of landscapes allow for a viable ‘evolution by natural selection’. Only some landscapes are suitable, with many being either ‘too flat’ or ‘too mountainous’. Somewhat hilly is best. Most systems are also too chaotic to say anything useful
Population geneticists know many (quantatitive!) things about when different evolutionary forces (Drift, Mutation, Sexual Recombination) may overwhelm natural selection
Alan Grafen has a fairly precise mathematical framework that he says is able to determine when Darwinian-Wallacian evolution is maximizing a ‘fitness function’. Importantly, not all situations/ecosystems can support the traditional ‘survival of the fittest’ interpretation of evolution
The take-away message is that we should be careful when we say that evolution explains biological complexity. This might certainly be true—but can we prove it?