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Source: (consider it)
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Thread: The Death of Darwinism
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ken
Ship's Roundhead
# 2460
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Posted
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Originally posted by Glenn Oldham:
"In the electron microscope, centrioles look like tiny turbines. Using TOPS [Theory of Organismal Problem-Solving]as my guide, I concluded that if centrioles look like turbines they might actually be turbines."
![[Eek!]](eek.gif)
Centrioles aren't turbines. I promise you. You heard it hear first.
Now ATP synthases and related membrane proteins - some of them are turbines - quite literally. Well, electric motors anyway. A proton passes through a tube with a spiral arrangement of charged molecules on it and the whole thing rotates.
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There is absolutely no resaon why a Darwinian might not think this thought!
Of course.
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Ken
L’amor che move il sole e l’altre stelle.
Posts: 39579 | From: London | Registered: Mar 2002
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Faithful Sheepdog
Shipmate
# 2305
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Posted
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Justinian said:
Neil, I am not claiming that they present clear evidence that evolution has happened - that is simply your misconception. What I am claiming is that they present proof that some of your cherished arguments against evolution are flat out wrong - things that it is claimed are impossible could both happen have been shown to do so. To claim that such models show that biological Darwinism clearly happened (rather than simply that many of your objections are false) is your misinterpretation, and although to accidentally construct such a strawman is a stupid mistake, I am prepared to apologise for extrapolating the fact that you have both started and maintained such a stupid strawman on this thread to the conclusion that you are stupid. If this is the case, then we all do stupid things and calling you either stupid or wilfully blind for doing something stupid is one of my stupid mistakes.
Justinian, your apology is welcome, such as it is, but your use of the phrases “stupid mistake” and “stupid strawman” undermine any of the good in it. I am as capable of misunderstanding as anyone – especially over the limited medium of the Internet – but you misrepresent my argument whilst continuing to hurl insults.
You didn’t introduce the article on the success of genetic algorithms in electronics for my general education and welfare. In the context of this thread these algorithms were submitted as evidence for a line of argument regarding the creative powers inherent in a Darwinist random mutation and natural selection scenario. Here are your words from 29/6/04, with your original emphasis:
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Constrained systems can come up with new solutions- one case comes to mind where there was an attempt to see how to make a tone detector using the lowest possible number of parts in an electric circuit- and it came up with a solution using fewer than the theoretical minimum number of parts- and a solution in which some of the necessary parts were not even part of the circuit - meaning that in some cases it was the physics of the individual cells that was affecting the circuit, not their properties as part of the circuit.
How's that for creation of something new via a genetic algorithm?
and you went on to say on 1/7/04:
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Part of the point is that the optimal solution wasn't just defined by the 1800 bits of information- the solution also involved the physical properties of the board- making for a more efficient solution, but one that was untransferable and completely breaking the chance of encoding the information in terms of a relatively small number of bits. It was also a solution that the [human] creator would never have come up with.
and then finally you said on 11/7/04:
quote:
Also it was an experiment done physically rather than in computer modelling - computer modelling would not have come up with that solution either - if it came up with a solution at all, the solution would have had all the cells involved actually connected to each other (unlike this one) unless you could model the exact physical properties into the algorithm (which would take a massive amount of information).
IIRC when New Scientist covered this, they also commented that the solution used fewer than the theoretical minimum number of parts to measure the frequencies.
That appears to be the sum total of your initial argument on these algorithms.
I have not denied that the experiment was very successful, nor that the solution to the electronics problem was indeed a novel one, but you have conspicuously not made any argument for a link between these algorithms and Darwinism. If you are going to submit these numerical algorithms as providing some insight into biological Darwinism, then the onus is on you to demonstrate their relevance to the biological processes, other than the linguistic similarities in the word “genetic”.
My argument all along has been that the processes in these algorithms are working in a far-from-Darwinian fashion. If I am correct in this, either partially or completely, then their value as insight into biological Darwinism is much reduced, and they may even become part of the evidence against Darwinism.
It is also clear to me that there is some confusion on your part over the notion of irreducible complexity. Here is how irreducible complexity was originally defined by Behe, as quoted on our old friends Talk Origins:
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By irreducibly complex I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system, because any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional. An irreducibly complex biological system, if there is such a thing, would be a powerful challenge to Darwinian evolution. (p. 39)
For a system to be irreducibly complex the fitness function must be a simple binary on/off measure. Either it works in some fashion – any fashion – or it grinds to a complete and total halt – “effectively ceases functioning”, as Behe puts it. That’s all that is needed. Think of a petrol engine car without a distributor arm – any distributor arm, even an electronic one – and you’ll see what I mean. It’s fitness as a binary integer function, which is a fundamentally different mathematical concept to fitness as a real continuous variable.
This experiment was explicitly designed to rule out the applicability of such a concept from the very start. I have previously laboured the point that the fitness function in this experiment was a mathematically continuous positive variable. Any value greater than 0 was adequate for nomination as the fittest “creature”, provided that this value was greater than its neighbours, even if only due to noise.
The discussion section of the paper itself provides considerable evidence that the final circuit could be modified slightly and still retain most of its function – see here. In the terms of the paper, the final circuit was definitely not irreducibly complex as understood by Behe.
Now, over to you, I want to hear some substantial arguments as to why this experiment in particular and these algorithms in general shed some light on biological Darwinism. You consider that “they present proof that some of my cherished arguments against evolution are flat out wrong”. Now is the time to demonstrate it rather than simply asserting it.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
Posts: 1097 | From: Scotland | Registered: Feb 2002
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ken
Ship's Roundhead
# 2460
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Posted
quote:
Originally posted by Faithful Sheepdog:
It is also clear to me that there is some confusion on your part over the notion of irreducible complexity.
Inevitably because it doesn;t seem to mean much
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Here is how irreducible complexity was originally defined by Behe, as quoted on our old friends Talk Origins:
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By irreducibly complex I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system, because any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional. An irreducibly complex biological system, if there is such a thing, would be a powerful challenge to Darwinian evolution. (p. 39)
I'm not sure there is such a thing in biology. No-one that I have heard of has proposed one that holds up.
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For a system to be irreducibly complex the fitness function must be a simple binary on/off measure. Either it works in some fashion ? any fashion ? or it grinds to a complete and total halt ? ?effectively ceases functioning?, as Behe puts it. That?s all that is needed.
But that's a hell of a lot that's neded then. Things like that are rare in nature if they occur at all.
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Think of a petrol engine car without a distributor arm ? any distributor arm, even an electronic one ? and you?ll see what I mean.
Well, an engine with a slightly bent one would still work, yes?
NB things can change their function - so something that is good at X and would be less good at X if it was slightly different may well have been doing Y before X.
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It?s fitness as a binary integer function, which is a fundamentally different mathematical concept to fitness as a real continuous variable.
Use of mathematical jargon to restate something that is not an accurate model doesn't make it an accurate model. It just obfuscates it for non-mathematicans.
In real life biological fitness isn't a function. It's a count - the number of of descendents something has. And it is of course contingent, historical. The continuously variable fitness numbers used in models are just that, models. And deterministic equations are very bad models of evolutionary or ecological processes. Stochastic ones better, but individual-based modelling better still.
It might be the case that in some parts of physics the equations used to describe things are the "real" description and the English words a mere approximation for the innumerate. That's not the case in biology. Lots of people are misled by treating the deterministic equations used in biological models as "real". They're not - they are just approximations that are easier to calculate.
If I say that one character has a fitness of 1, and another of 0.99 that's just a sort of statistical prediction. (& ought to be accompanied by a variance to be really accurate!). If I observe a real population of organisms (or a realistic stochastic or IB model) I will see how many offspring are actually born. And that number is the fitness. There are no hidden variables. Everything is dependent on the environment. If I think the fitness of one character should be 0.99 but in fact the bearers of that character only have 0.98 as many offspring that's not an error (in the common English sense of error - it is in the statistical jargon sense of course). It's just that the real outcome fitness has varied from the model. That outcome depends on many interactions between individuals, on many random occurences. There is no secrfet inner true fitness which is more or less expressed - the real fitness is the outcome, not the prediction. Even in a model.
NBB - fitnesses are relative anyway (one of the reasons that all that stuff about mutation load is guff). If you got a population and magically mutated all their genomes so every one of them had on average a fitness of 0.9 that doesn't mean the population would fall to 90% of what it was. Because there woudl be no competition against fitter genomes, so that in practice they would actually have a fitness of one. The concept of fitness only works in a context of competition - effectively all organisms being able to reproduce themsleves many times over in the absence of competition or limitation by scarce resources.
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This experiment was explicitly designed to rule out the applicability of such a concept from the very start. I have previously laboured the point that the fitness function in this experiment was a mathematically continuous positive variable. Any value greater than 0 was adequate for nomination as the fittest ?creature?, provided that this value was greater than its neighbours, even if only due to noise.
No, that's just an approximation
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The discussion section of the paper itself provides considerable evidence that the final circuit could be modified slightly and still retain most of its function ? see here. In the terms of the paper, the final circuit was definitely not irreducibly complex as understood by Behe.
How could it be? Behe, it seems, handwavingly defines a class of objects which cannot evolve. Then asserts that somewere something biological is in this class. So by definition that biological thing cannot have evolved. A fun mathematicians trick, but in the end not anything to do with biology.
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Ken
L’amor che move il sole e l’altre stelle.
Posts: 39579 | From: London | Registered: Mar 2002
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Glenn Oldham said:
But Dembski declares selective algorithms on computers to be as incapable as natural selection in creating 'complex specified information'. He draws no distinction between them but damns all trial and error processes as mere combinations of chance and necessity and therefore incapable of generating 'complex specified information'. The experiment we have been looking at refutes that assertion and thus makes his claims against evolution highly doubtful at best.
<snip>
But in where then, in the experiment that we have been looking at, did the complex specified information that was produced come from? We wound up with a complex and functional arrangement. This is an example of complex specified information. Where did it come from? Answer that and you can see that Dembski's arguments against natural selection are worthless.
In Dembski’s writings “complex specified information” (CSI) is a technical term that is defined mathematically with some rigour, drawing on accepted results in information and probability theory. He has argued that any CSI with a probability level of less than 10E-150 may lead to a design inference. This number is not totally arbitrary, but is derived from some fundamental physical constants of the universe.
In the experiment we have been looking at, the probability of the successful configuration being achieved by a random guess is 10E-540. So it appears to be correct to call the final configuration CSI in Dembski’s terms. I certainly agree that it is highly improbable that the correct configuration could have been achieved by a random guess. And using a human technician, successive trial and error would take far, far too long to be practical.
In order to speed up the process dramatically, the experiment was set up on a human-constructed computer. Like all computers, this can do calculations far quicker than any humans, but the instructions to the computer as to which calculations and on which numbers were provided by humans. All the computer provides is brute number crunching.
So, you are not correct to attribute the creation of the final information to the computer. That information was created by humans in the numerical parameters of the human-designed experiment, and also by humans in the physical properties of the human-constructed microchip, and yet again by humans, in the especially precise way in which humans defined the fitness function.
All the computer did was sort through many existing numbers to find an optimum value (actually a population of 50 optimum values) very much quicker than any human could do. It took the computer 2 to 3 weeks to complete all the calculations, but the resulting information was created by humans, not by the computer.
quote:
Glenn Oldham said:
If you know of any such 'front loaded models' I would be glad to hear of them.
These models consider that macroevolution is something which took place in the far past, and in some cases took place by saltation – that is, explicit large jumps. However, this process is not being observed today. The era of evolution is over; what we are now seeing is the era of extinctions. The speciation observed today is trivial in evolutionary terms, and not responsible for what the fossil record shows.
One common factor in these models is that the normal processes of sexual reproduction are not responsible for evolutionary development. In fact, for a sexual species sexual reproduction serves to bring macroevolutionary development to a complete halt. This neatly sidesteps the problem that Darwinism has always had with sexual reproduction.
One author you may wish to investigate is the Frenchman Pierre-Paul Grassé. He is no lightweight amateur, but a past president of the French Academy of Sciences. He is associated with development of the concept of stigmergy, the term for the apparent intelligence in large assemblies of unintelligent creatures, especially termites armies. See here for more information on stigmergy.
He repudiates Darwinism forcefully in favour of his “front loaded evolutionary model” based on “internal developmental factors”. His book “Evolution of Living Organisms” was published in French in 1973 and in English in 1977. I have yet to read it, but I have to admit, it does intrigue me.
Another character is a contemporary American university biology professor called John A. Davison, who has derived some of his evolutionary ideas from Grassé. You will find access to some of his papers and thoughts at the ISCID forums here and also here.
He uses the ISCID board name of Novisad and is something of a prickly character, but then his anti-Darwinian views have got him into trouble with his university employers, so which came first? The important question should be whether his scientific ideas are sound, even if unconventional.
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Glenn Oldham said:
As far as I can see the ID movement is solely an anti-Darwinian-evolution movement with no positive proposals for an alternative explanation of the phenomena.
Whilst many in the ID fraternity are clearly opposed to Darwinism, which they consider to be both a failed scientific hypothesis and a pernicious ideology restrictive on true scientific thinking, they are nevertheless open to many different scientific approaches, and from many different theological perspectives (or in the case of agnostic David Berlinski, none).
Although many ID ideas and terminology have been co-opted by the young earth creationist (YEC) fraternity, it is important to distinguish clearly the very different approaches of the two groups. If you are used to doing battle with YECists, then I am not surprised that you find ID a frustrating subject. It’s much more open to mainstream science whilst simultaneously being much more subtle in its philosophical approach.
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If you have a better idea as to why Intelligent Design is supposed to be so radically helpful in research please let me know.
For a thoughtful set of essays on the value of teleological thinking in respect to biological origins, see these writings by an Internet character called “Mike Gene”. He posts regularly at ARN.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
Posts: 1097 | From: Scotland | Registered: Feb 2002
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Glenn Oldham
Shipmate
# 47
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Posted
quote:
Originally posted by Faithful Sheepdog:
If you are going to submit these numerical algorithms as providing some insight into biological Darwinism, then the onus is on you to demonstrate their relevance to the biological processes, other than the linguistic similarities in the word “genetic”.
My argument all along has been that the processes in these algorithms are working in a far-from-Darwinian fashion. If I am correct in this, either partially or completely, then their value as insight into biological Darwinism is much reduced, and they may even become part of the evidence against Darwinism.
It is also clear to me that there is some confusion on your part over the notion of irreducible complexity. … For a system to be irreducibly complex the fitness function must be a simple binary on/off measure. Either it works in some fashion – any fashion – or it grinds to a complete and total halt – “effectively ceases functioning”, as Behe puts it. That’s all that is needed. … It’s fitness as a binary integer function, which is a fundamentally different mathematical concept to fitness as a real continuous variable.
This experiment was explicitly designed to rule out the applicability of such a concept from the very start.
This experiment involved a population of 50 individual circuits. Aspects of these circuits were subjected to a degree of random mutation. Those individual circuits which performed a particular function better than others were reproduced to a greater degree than the others. They were also interbred. Again, further mutation was introduced and the cycle was repeated again and again. Eventually a remarkably good level of function was produced.
This already sounds remarkably like the neo-Darwinian notion of evolution by natural selection, and it is therefore very odd to say that it is “working in a far-from-Darwinian fashion” and to imply that the only comparison with Darwinism is the word ‘genetic’ in ‘genetic algorithm’.
Since the experimenters did not want to die before the results of the experiment came in they used a high mutation rate and a rapid generation time. A lower mutation rate could have been used and a longer generation time. This would have slowed things down, but that could have been compensated for by using a population of far higher size.
Now since neo-Darwinism holds that evolution proceeds in a step-by-step fashion and NOT in great leaps, it was perfectly correct and perfectly Darwinian to make the fitness test in the experiment one where the circuits features are compared with an ideal and if it approaches that ideal more than its fellows then it gets to breed more. (There are thousands of such features in nature: being taller, running faster, having an enzyme that is slightly more efficient, and so on. )
To design the experiment with an all or nothing test for fitness where the change required is very, very large would not have produced the result (except by colossal chance). But such an experiment would not have been a Darwinian one.
As has been pointed out earlier in this thread (which contains extensive criticism of Behe’s views) there are many ways in which a system that is irreducibly complex can evolve gradually.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
Posts: 910 | From: London, England | Registered: May 2001
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TonyK
Host Emeritus
# 35
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Posted
Hmmmm - I'm trying to follow this - but you guys lost me several pages back.
As a result I missed one or two critical things...
Host Mode <ACTIVATE>
The argument seems to be spilling over into personal stuff - head banging on a wall (which in the context could be taken as a personal attack) and some rather unacceptable words. I think the people concerned know who and what I am talking about.
Could I suggest that all concerned take a break of at least a day from this thread (other than to post apologies if you feel they are needed) to allow emotions to cool - if this doesn't happen I will lock it for 48 hours.
Come on guys - it's a Dead Horse, You're not going to be able to resolve it here (or anywhere else!) Let's get things into perspective, shall we?
Oh and by the way - a Host's suggestion does carry some weight ![[Big Grin]](biggrin.gif)
Host Mode <DE-ACTIVATE>
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Yours aye ... TonyK
Posts: 2717 | From: Gloucestershire | Registered: May 2001
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Glenn Oldham
Shipmate
# 47
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Posted
First of all if I caused any offence by my icon of beting my head against a wall I apologise. It was not intended as an insult to Neil, or anyone and it was my head, figuratively speaking.
Neil,
First of all, thanks for the links to the various ID articles in your last post.
Second, and the subject of this post from me, I asked where the complex specified information of the final configuration of the 10 by 10 microchip came from. I said, quite deliberately, “answer that and you can see that Dembski's arguments against natural selection are worthless.” Let me explain why I said that. Judging by your answer you have rejected the argument of Dembski’s paper.
After accepting that the final configuration of the microchip was sufficiently complex and improbable to count as ‘complex specified information’ you said:
quote:
Originally posted by Faithful Sheepdog: [with my italicisation G.O.]
I certainly agree that it is highly improbable that the correct configuration could have been achieved by a random guess. And using a human technician, successive trial and error would take far, far too long to be practical.
In order to speed up the process dramatically, the experiment was set up on a human-constructed computer. … the instructions to the computer as to which calculations and on which numbers were provided by humans. All the computer provides is brute number crunching.
So, you are not correct to attribute the creation of the final information to the computer. That information was created by humans in the numerical parameters of the human-designed experiment, and also by humans in the physical properties of the human-constructed microchip, and yet again by humans, in the especially precise way in which humans defined the fitness function.
All the computer did was sort through many existing numbers to find an optimum value (actually a population of 50 optimum values) very much quicker than any human could do. It took the computer 2 to 3 weeks to complete all the calculations, but the resulting information was created by humans, not by the computer.
So on the one hand we have the humans an on the other we have the physical system (the computer with its settings and the microchip with its physical properties). The physical system has been designed by the humans. The physical system is then allowed to run and it follows a process modelled on natural selection – it tests a set of configurations for fitness and preferentially replicates the most fit, it then varies them slightly and randomnly and then repeats the cycle. It does this until the final result is reached of a highly fit configuration. That configuration is a state that is one of complex specified information. What the apparatus does is dictated by the laws of physics, the settings imposed by the software, and the random variation generated.
You wish to describe this information as having been created by humans. I imagine that you would see it as an example of intelligent design. I imagine too that Dembski would argue the same thing.
Now I think that the example reveals subtleties to what ‘design’ means that are often skated over in ID literature, where design is often seen as intelligence supplying the information of the final result direct to the system. BUT LET THAT PASS for the time being, for there is a more crucial difficulty for ID in the answer that you have given.
It is that on the basis of your reasoning, evolution by natural selection on neo-Darwinian lines would itself be an example of Intelligent Design and the designer in this case would be whoever created or designed the natural world. The physical world, with its parts subject to the laws of chemistry and physics and its organisms subject to selection for fitness, replicating, varying will, where the conditions are right, generate complex specified information.
It is one thing to argue that the natural world does not have time or sufficient sources of variation to operate natural selection and so on. That is to argue that Natural Selection does not occur. But the argument that Natural Selection cannot on principle generate complex specified information fails utterly, especially in the face of experiments like these.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
Posts: 910 | From: London, England | Registered: May 2001
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Glenn Oldham said:
First of all if I caused any offence by my icon of beating my head against a wall I apologise. It was not intended as an insult to Neil, or anyone and it was my head, figuratively speaking.
Glenn, no apology necessary, I certainly didn’t take it as an insult or a personal attack. The frustration induced by the difficulties of communication over the Internet is something I’ve certainly felt. It was Justinian’s later remarks to which I objected.
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Ken said:
Well, an engine with a slightly bent one [i.e distributor arm] would still work, yes?
The key question to ask is whether the engine starts or not.
A slightly bent distributor arm may still work enough to transmit the electrical spark at the right time, hence the engine starts, even if it subsequently runs a little roughly. In functional terms a distributor arm is still present.
A more heavily bent arm may fail to work at all, at which point the engine fails to start at all, and we’re calling the breakdown service.
The world of engineering is full of irreducibly complex systems, so this concept is almost intuitively obvious to me. The key question is whether the concept can be rightly applied to biological systems. You say:
quote:
Things like that are rare in nature if they occur at all.
I myself see no reason to support this assertion. Machines are subject to the laws of physics. Why should biology not be?
Note that Michael Behe is a biochemist, not a mathematician, a physicist or an engineer. For him, if Darwinian evolution is to be true, it must also satisfactorily explain the emergence of biochemical systems. It was his dissatisfaction on this point which eventually led him to write his book, Darwin’s Black Box, although the concept of irreducible complexity actually predates him.
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Ken said:
Use of mathematical jargon to restate something that is not an accurate model doesn't make it an accurate model. It just obfuscates it for non-mathematicians.
My comment on integer versus real numbers was not intended to blind people with mathematical jargon. This difference was one of the first things I was taught in my engineering degree, with relevance to computer programming.
An integer measure is counted in whole numbers, 1, 2, 3, 4 etc. A good everyday example is eggs – we buy them in the UK by the half dozen or dozen or whatever, but half an egg is simply not possible.
By contrast, a real number can be a decimal figure to any number of places you like (subject to the limit of the measuring equipment in question). A good example is the value for Pi (the ratio of a circle’s circumference to its diameter), which is a real number that can be quoted to as many decimal places as you wish (3.14157……etc).
quote:
Glenn Oldham said, with his emphasis:
It is one thing to argue that the natural world does not have time or sufficient sources of variation to operate natural selection and so on. That is to argue that Natural Selection does not occur. But the argument that Natural Selection cannot on principle generate complex specified information fails utterly, especially in the face of experiments like these.
There are many processes around us where complex assemblies are formed from the small incremental addition of new parts that in themselves are almost trivial. As a boy I called them jigsaw puzzles; as a professional engineer I call them skeletal steelwork structures. And we are all familiar with the process of writing, which begins with the first letter on the page, and ends up as a Booker prize-winning novel, or whatever.
In broader terms it is absolutely essential to distinguish between processes which are intelligently driven towards a pre-programmed goal – a telic process in philosophical jargon – and the rigorously naturalistic form of Darwinism, enthusiastically championed by the likes of Richard Dawkins, where teleology is completely out, full stop.
There is a brand of ID that would see natural selection as an intelligence-driven, goal-oriented process. The position of these people probably has much in common with what is sometimes called “theistic evolution”, presumably driven by God under the appearance of a Darwinian process. That seems to be the position of many on this thread, and indeed in the wider church, even if they would personally repudiate the term ID.
However, for Dawkins there is no intelligence abroad in the universe other than ourselves. Natural selection as he understands it is an unintelligent process that cannot possibly have a target or a goal. It knows only about the present. It can access the past indirectly through genetically stored information, but it definitely does not know about the future. Dawkins’ Darwinism is for the church of the true believers - there is no metaphysics allowed at all.
So a truly Darwinian process is not just one progressing in a step-by-step fashion. To be truly Darwinian it must be a process that truly does not know where it is going. It cannot have access to any form of ideal end goal, since that would be a form of teleology. To be truly Darwinian that cannot be allowed. At least, that’s how I understand it.
Since Darwinism ascribes a great deal to natural selection, it is essential to be clear on what is meant by it. As Ken says, the proper description of natural selection is not in terms of a “mathematical fitness function”, but in terms of the relative number of descendants. Here is how he put it earlier:
quote:
In real life biological fitness isn't a function. It's a count - the number of descendents something has. And it is of course contingent, historical. The continuously variable fitness numbers used in models are just that, models. And deterministic equations are very bad models of evolutionary or ecological processes. Stochastic ones better, but individual-based modelling better still.
In the light of these comments let’s look more closely at how the experiment operated:
Firstly it assigned a fitness value to each individual in each generation by reference to equation 1 in the paper. This equation incorporates all the information necessary to specify the final end point, the goal of the process. For each individual an absolute fitness was established by constant reference to this desired end goal. The relative fitness of each individual was only then established, in a secondary and derivative manner, as the ratio of the absolute fitnesses.
As Glenn Oldham put it, with my emphasis:
quote:
Now since neo-Darwinism holds that evolution proceeds in a step-by-step fashion and NOT in great leaps, it was perfectly correct and perfectly Darwinian to make the fitness test in the experiment one where the circuits features are compared with an ideal and if it approaches that ideal more than its fellows then it gets to breed more.
So, we are both agreed that these algorithms have access to an “ideal” at all times – the specified end goal.
Hence my first point is that these algorithms, by definition, cannot be a truly Darwinian process. They are driven throughout by a goal-oriented methodology, which is perfectly reasonable if trying to solve an engineering problem, but not if one is trying to model a Darwinian process.
Secondly, having established a numerical fitness measure for each individual, the algorithm then mimics the breeding process, allowing for the possibility of random mutation. It determines the relative number of offspring based on assigned probability values. These probability values are derived from the relative fitness values - a relatively fitter individual has more offspring than a less fit one.
But note what this implies: Since the relative fitness values are derived with reference to the absolute fitness values, and since the absolute fitness values are determined in relation to the final end goal, the algorithm ensures a priori that that individuals nearer to the specified target have relatively more offspring. So, if the target exists at all, it is no surprise when we eventually we hit it, since that was something the experiment intended all along.
So my second point is that these algorithms are not modelling natural selection as understood within Darwinism. In them the selection process means “nearer to the specified target”, not “who has the most grandchildren”. The experiment is not counting the descendants, and then deducing a theory from that empirical data. Instead it imposes a deterministic form of differential breeding in a pre-determined manner.
My third point is that this whole experiment was functionally deterministic, not stochastic. If the experiment was run again, it would converge to the same functional target. It is not free to do anything else. A true stochastic process would be free to give a different result and converge to some other functional target.
So I want to stand by my comment that these algorithms are working in a far-from-Darwinian fashion, and they are definitely not demonstrating a Darwinian process.
There is a long, detailed and highly technical article on genetic algorithms at Talk Origins here. The long factual description of the history of these algorithms is quite good, but if you scroll about 90% of the way down the page, there is a brief mention of our electronics experiment. The relevant paragraph begins :
quote:
However, genetic algorithms make this view untenable by demonstrating the fundamental seamlessness of the evolutionary process. Take, for example, a problem that consists of programming a circuit to discriminate between a 1-kilohertz and a 10-kilohertz tone, and respond respectively with steady outputs of 0 and 5 volts.
And goes on to conclude, with their original emphasis:
quote:
The circuit evolved, without any intelligent guidance, from a completely random and non-functional state to a tightly complex, efficient and optimal state. How can this not be a compelling experimental demonstration of the power of evolution?
On the contrary, this experiment was a compelling experimental demonstration of the power of humans to invent complex and sophisticated tools to help them solve their problems. That takes intelligence.
quote:
Glenn Oldham said:
You wish to describe this information as having been created by humans. I imagine that you would see it as an example of intelligent design. I imagine too that Dembski would argue the same thing.
I am intrigued by this comment – I presume that you disagree with my original comment about the human origin of the complex specified information in the experiment? Why do you think that the information was not created by humans?
On a broader note I have heard it said that, in their enthusiasm to rule out metaphysical agency, Darwinists also inadvertently rule out human agency. The comment above on this experiment from Talk Origins seems to take this line. As a professional engineer trained to solve technical problems I must say that I find it absolutely extraordinary.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Rex Monday
None but a blockhead
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Posted
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Originally posted by TonyK:
Hmmmm - I'm trying to follow this - but you guys lost me several pages back.
As a result I missed one or two critical things...
Host Mode <ACTIVATE>
The argument seems to be spilling over into personal stuff - head banging on a wall (which in the context could be taken as a personal attack) and some rather unacceptable words. I think the people concerned know who and what I am talking about.
Could I suggest that all concerned take a break of at least a day from this thread (other than to post apologies if you feel they are needed) to allow emotions to cool - if this doesn't happen I will lock it for 48 hours.
Come on guys - it's a Dead Horse, You're not going to be able to resolve it here (or anywhere else!) Let's get things into perspective, shall we?
Oh and by the way - a Host's suggestion does carry some weight
Host Mode <DE-ACTIVATE>
In accordance with the very sound wishes expressed by our host, I will not be posting further on this thread.
I have, however, called Faithful Sheepdog to Hell, where I will be more than happy to explain my feelings and thoughts over the path this thread has taken.
R
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I am largely against organised religion, which is why I am so fond of the C of E.
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Justinian
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Posted
Neil, They shed light in that they show from an evolutionary starting point that some of the objections raised are just plain wrong. They do not prove that evolution happened, and I'm sure can be used as the basis for new arguments against evolution, but in a number of cases new arguments are needed. The circuit is not an argument against ID via the mechanism of evolution (I don't think that that's remotely falsifiable without falsifying evolution- although Occam's Razor is an argument against it, as are the various odditites in evolution like nerves in the giraffe and unwanted extra fingers in birds), just against a string of arguments claiming that macroevolution could not have happened.
One of the things thought by some to be impossible that was shown was speciation, with the best solution not working if you moved it onto the circuit board of the second best solution and vise-versa (they couldn't interbreed and were very different).
Irreducible complexity strikes me as a chimera- a circuit can survive having some of the insulating plastic removed, but will break if it has the batteries or one of the conductors removed. Likewise a human can survive with an arm amputated, but not its brain removed. For that matter, most well designed engineering systems have built in margins of error and redundancies in order to cope with the real world.
Finally evolution works in the real world by feeding back the current state of the world, meaning the system for determining optimality is extremely chaotic.
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My real name consists of just four letters, but in billions of combinations.
Eudaimonaic Laughter - my blog.
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Glenn Oldham
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# 47
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Posted
Only time for a brief reply.
quote:
Originally posted by Faithful Sheepdog:
In broader terms it is absolutely essential to distinguish between processes which are intelligently driven towards a pre-programmed goal – a telic process in philosophical jargon – and the rigorously naturalistic form of Darwinism, enthusiastically championed by the likes of Richard Dawkins, where teleology is completely out, full stop.
…
So a truly Darwinian process is not just one progressing in a step-by-step fashion. To be truly Darwinian it must be a process that truly does not know where it is going. It cannot have access to any form of ideal end goal, since that would be a form of teleology. To be truly Darwinian that cannot be allowed. At least, that’s how I understand it.
…
… my first point is that these algorithms, by definition, cannot be a truly Darwinian process. They are driven throughout by a goal-oriented methodology, which is perfectly reasonable if trying to solve an engineering problem, but not if one is trying to model a Darwinian process.
Secondly, … if the target exists at all, it is no surprise when we eventually we hit it, since that was something the experiment intended all along.
So my second point is that these algorithms are not modelling natural selection as understood within Darwinism.
My third point is that this whole experiment was functionally deterministic, not stochastic. If the experiment was run again, it would converge to the same functional target. It is not free to do anything else. A true stochastic process would be free to give a different result and converge to some other functional target.
So I want to stand by my comment that these algorithms are working in a far-from-Darwinian fashion, and they are definitely not demonstrating a Darwinian process.
I am grateful that nothing in your post attempts the futile task of trying to prove that Darwinian natural selection cannot in principle create complex specified information. (Which is what Dembski seeks to do on purely logical grounds).
Organisms are tested against other organisms in terms of which of them are better able to survive and reproduce. What enables them to best do this changes over time. It is still a selective process as much as that in the experiment. If you want an experiment which models Darwinian evolution more accurately then this one is appropriate: The evolutionary origin of complex features- a pdf file
You will note that complex specified information is generated.
Finally, on the question of whether the humans created the information in the experiment we have been discussing: one could more accurately say that they designed a system that would search using a selection process and find one of an indeterminate number of configurations that would perform a certain function. The system then found it for them. Did they create that information? Did they design that final microchip? They certainly did not do so in most ordinary uses of the terms 'create' and 'design'. And it is the ordinary uses of those terms most people assume when they here talk about intelligent design. In the Lenski and Pennock experiment it is even further from normal usage to say that they designed the virtual creatures of their experiment.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Faithful Sheepdog
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Posted
quote:
Justinian said:
Neil, They shed light in that they show from an evolutionary starting point that some of the objections raised are just plain wrong. They do not prove that evolution happened, and I'm sure can be used as the basis for new arguments against evolution, but in a number of cases new arguments are needed.
I’m struggling to understand what you’re saying here, so perhaps you could identify which objections in particular are “plain wrong”. If new arguments are needed, then perhaps you could sketch some of them out in more detail.
I’ve given plenty of detail as to why I don’t think that genetic algorithms demonstrate what is being claimed for them. Where do you think my arguments are incorrect?
quote:
Justinian said:
The circuit is not an argument against ID via the mechanism of evolution (I don't think that that's remotely falsifiable without falsifying evolution- although Occam's Razor is an argument against it, as are the various oddities in evolution like nerves in the giraffe and unwanted extra fingers in birds), just against a string of arguments claiming that macroevolution could not have happened.
Once again I’m really not sure what you’re saying here. Why should Occam’s razor be applicable in the instance of a scientific question?
The argument from homology that Glenn has brought forward is an argument based on an inference from similar patterns. In essence his argument here is not dissimilar to that used in many ID circles, in which biological design is inferred based on comparison with a pattern from engineering systems. We are looking at the same facts, but drawing very different conclusions.
quote:
Justinian said:
One of the things thought by some to be impossible that was shown was speciation, with the best solution not working if you moved it onto the circuit board of the second best solution and vice-versa (they couldn't interbreed and were very different).
Now I’m really confused - I can’t find this information at all in the paper. Can you link to the relevant section? They did repeat the experiment on a different 10x10 part of the microchip, using as a starting population of 50 the final evolved configurations from the first experiment.
In the new location they found an immediate 7% drop in the fitness of the previously fittest individual, although another individual was now within 0.1% of perfect fitness. These differences are explainable by the random variations between the numerous micro-transistors on the chip. After another 100 generations in the new chip location, all members of the population had converged on perfect fitness.
quote:
Justinian said:
Irreducible complexity strikes me as a chimera- a circuit can survive having some of the insulating plastic removed, but will break if it has the batteries or one of the conductors removed. Likewise a human can survive with an arm amputated, but not its brain removed. For that matter, most well designed engineering systems have built in margins of error and redundancies in order to cope with the real world.
Has you car ever failed to start? That’s irreducible complexity in action for you.
We have many things in twos – eyes, ears, lungs, kidneys, arms, legs - but how many back-up hearts do you have?
quote:
Justinian said:
Finally evolution works in the real world by feeding back the current state of the world, meaning the system for determining optimality is extremely chaotic.
It’s essential to differentiate between positive and negative feedback from the environment. Negative feedback damps down a random mutation phenomenon and ensures that it grows smaller over time.
With positive feedback the phenomenon will grow bigger over time. In real engineering systems there are limits imposed on the growth of the phenomenon by the emergence of non-linearity in the system. If you’ve ever seen the footage of the collapse of the Tacoma Narrows suspension bridge under wind induced vibration, you’ll know what I mean.
In general positive feedback is certainly not beneficial in engineering, but of course, this begs the question in biology. Can positive feedback be applied to a biological system in a continuously beneficial fashion? Darwinism is a priori committed to the answer yes.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Glenn Oldham
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# 47
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Posted
quote:
Originally posted by Faithful Sheepdog:
quote:
Justinian said:
Neil, They shed light in that they show from an evolutionary starting point that some of the objections raised are just plain wrong. They do not prove that evolution happened, and I'm sure can be used as the basis for new arguments against evolution, but in a number of cases new arguments are needed.
I’m struggling to understand what you’re saying here, so perhaps you could identify which objections in particular are “plain wrong”. If new arguments are needed, then perhaps you could sketch some of them out in more detail.
I’ve given plenty of detail as to why I don’t think that genetic algorithms demonstrate what is being claimed for them. Where do you think my arguments are incorrect?
Neil,
Let me try to spell it out as clearly as I can. One of the arguments offered by some IDers and by Dembski in the article of his I posted earlier is that a system that generates complex specified information by random variation plus selection plus replication is impossible. Dembski's argument to this effect is purely logical. It does not raise questions of mutation rates or fitness functions or any of the matters that you have mentioned. It argues that chance, necessity, and design are the only causes around and that chance and necessity (working alone or even together) cannot generate complex specified information. He states this to be the case for natural selection and for genetic algorithms.
It is this argument to the effect that natural selction is not possible that is refuted by the kinds of experiments that we have been discussing. Such arguments are shown to be plain wrong. (Dembsi's argument is fallacious on logical graounds as well, of course.)
Now as to your arguments (rather than Dembski's) against the relevance of these experiments for natural selection, ... more tomorrow.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
Posts: 910 | From: London, England | Registered: May 2001
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Justinian
Shipmate
# 5357
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Posted
quote:
Originally posted by Faithful Sheepdog:
quote:
Justinian said:
Neil, They shed light in that they show from an evolutionary starting point that some of the objections raised are just plain wrong. They do not prove that evolution happened, and I'm sure can be used as the basis for new arguments against evolution, but in a number of cases new arguments are needed.
I’m struggling to understand what you’re saying here, so perhaps you could identify which objections in particular are “plain wrong”.
That an evolutionary algorithm won't come up with a solution the designer couldn't have found. The solution found by an evolutionary method had parts of the circuit not actually connecting to the circuit- something no human designer would come up with. (IIRC that's the reason I brought this up in the first place)
That "irreducable complexity" would not arise by means of natural selection. The thing is an irreducibly complex object that arises through natural selection.
quote:
If new arguments are needed, then perhaps you could sketch some of them out in more detail.
Why should I do your work for you?
quote:
I’ve given plenty of detail as to why I don’t think that genetic algorithms demonstrate what is being claimed for them. Where do you think my arguments are incorrect?
In trying to claim that I'm claiming more for them than I am. What I claim for the experiment is that it explodes some of your claims, which it does. What I am not trying to prove is that it thereby proves the whole of evolutionary theory.
quote:
quote:
Justinian said:
The circuit is not an argument against ID via the mechanism of evolution (I don't think that that's remotely falsifiable without falsifying evolution- although Occam's Razor is an argument against it, as are the various oddities in evolution like nerves in the giraffe and unwanted extra fingers in birds), just against a string of arguments claiming that macroevolution could not have happened.
Once again I’m really not sure what you’re saying here. Why should Occam’s razor be applicable in the instance of a scientific question?
Because your statement is not a scientific one. You have come up with an unfalsifiable and more complex modification to the theory being presented (that there is natural selection, selected by the creator). It is that sort of crap that Occam's Razor (do not multiply entities beyond necessity) was origionally trying to deal with.
Being unfalsifiable, you are not presenting a scientific question, therefore methods for dealing with pseudoscience are quite sufficient.
quote:
The argument from homology that Glenn has brought forward is an argument based on an inference from similar patterns. In essence his argument here is not dissimilar to that used in many ID circles, in which biological design is inferred based on comparison with a pattern from engineering systems. We are looking at the same facts, but drawing very different conclusions.
Yes. 1+1=2 is similar to 1+1=3. The problem is that your argument from design has many many anomilies like overlong nerves, extra bones running parallel to another set and seven vertebrae in the neck of a giraffe.
quote:
quote:
Justinian said:
One of the things thought by some to be impossible that was shown was speciation, with the best solution not working if you moved it onto the circuit board of the second best solution and vice-versa (they couldn't interbreed and were very different).
Now I’m really confused - I can’t find this information at all in the paper.
I wish to withdraw this argument- although I believe it is valid, it is not solid enough to be used for argument. The only further thing I will say on the subject is to ask you to work out just how much can change in a solution with a 2.7% mutation rate per generation and 100 generations.
To debunk another of your arguments in passing, the paper was not written with creationism in mind. Counter example found despite not being searched for.
quote:
quote:
Justinian said:
Irreducible complexity strikes me as a chimera- a circuit can survive having some of the insulating plastic removed, but will break if it has the batteries or one of the conductors removed. Likewise a human can survive with an arm amputated, but not its brain removed. For that matter, most well designed engineering systems have built in margins of error and redundancies in order to cope with the real world.
Has you car ever failed to start? That’s irreducible complexity in action for you.
We have many things in twos – eyes, ears, lungs, kidneys, arms, legs - but how many back-up hearts do you have?
None. Neither do I have a backup life. In order to have reducible complexity, you need for there to be two distinct but identical entities.
On the other hand, the circuit indicated earlier developed through evolution rather than direct design- and it being an electronic circuit, it ipso facto was irreducibly complex as removing certain parts would break the circuit.
So we have an evolved object that is irreducibly complex. Counter example presented.
quote:
quote:
Justinian said:
Finally evolution works in the real world by feeding back the current state of the world, meaning the system for determining optimality is extremely chaotic.
It’s essential to differentiate between positive and negative feedback from the environment. Negative feedback damps down a random mutation phenomenon and ensures that it grows smaller over time.
[SNIP]
And natural selection uses both positive and negative feedback. It usually seems to use positive feedback until after a certain optimum point is passed then negative to get it back there.
quote:
In general positive feedback is certainly not beneficial in engineering, but of course, this begs the question in biology. Can positive feedback be applied to a biological system in a continuously beneficial fashion? Darwinism is a priori committed to the answer yes.
Bullshit! First, not all mutations that are selected fo are continuously benificial- see sickle cell anemia, which has benifits at times (for dealing with malaria) but certainly isn't beneficial all the time. Secondly, situations change- what was beneficial in the ice age isn't beneficial with global warming. Thirdly, there appear to be some optimal forms- sharks haven't changed their basic design in aeons. Fourthly, and related, there may me maneuvering round an optimal point- taller humans have an advantage, but if I were to follow your simplistic summary, humans would be at least 60' tall- although there are negative feedback mechanisms working against this.
You seem to have fundamentally misunderstood the mechanisms involved in darwinism.
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My real name consists of just four letters, but in billions of combinations.
Eudaimonaic Laughter - my blog.
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Glenn Oldham
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# 47
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Posted
quote:
Originally posted by Faithful Sheepdog
I’ve given plenty of detail as to why I don’t think that genetic algorithms demonstrate what is being claimed for them. Where do you think my arguments are incorrect?
Neil,
There are three main aspects of your arguments about genetic algorithms that I want to address. The first two are the questions of whether any new information is created by the experiments and, if so by whom. The second is whether these genetic algorithms are so different from natural selection that they have no evidential value for neo-Darwinism.
1) On whether new information is created.
In my immediately previous post I explained that one thing being claimed for these genetic algorithms is that they show that random variation plus selection plus replication is capable of generating new complex specified information. Now, since it is a claim of Darwinian theory that random variation plus selection plus replication is a key factor responsible for the adaptations of organisms to their environment, then experiments like this one clearly have relevance to that claim and provide evidential support for it. It is absolutely clear from this experiment (the 10 x 10 microchip one) that something new was produced: in this case it was a new configuration of a chip that had the ability to perform a complex electronic function.
On an earlier post (30 June, 2004 23:14) you said: quote:
Firstly, there is a sense in which the optimised design that emerges from the evolutionary algorithm can rightly be called new, since that particular combination of parameters has probably never seen the light of day before. …
However – and this is the but – the algorithm cannot break away from the original N parameters and the programmed constraints to give us the answer to a problem with N+M parameters and a different set of constraints. The program begins with N parameters for a specific engineering problem, and finishes with N parameters – for that same problem. So in that sense nothing has changed. We simply have a more desirable set of numbers than we started with.
[…]
So at the start, even before the algorithm has begun “number crunching”, all fitness values in the xyz space have been defined in principle by the programmed fitness function(s) and all the other constraints. There is a sense in which the program knows in advance the fitness values for all possible x, y and z values. The only problem remaining is the exact x, y and z location(s) of maximum fitness within the permitted region.
The program does NOT know ‘in advance the fitness values for all possible x, y and z’ values. If it can be said to know anything it can be said to know how to calculate the fitness value. In this case if either the humans or the system knew the exact specification of the successful chip configuration ’in advance’ then they could have configured the chip straight away without having to run the random variation plus selection experiment to find it. In this case they could not.
2) What creates the new information?
When we turn to the question of to what we are to attribute the creation of the new information you quote from a paper that says: “The circuit evolved, without any intelligent guidance, from a completely random and non-functional state to a tightly complex, efficient and optimal state. How can this not be a compelling experimental demonstration of the power of evolution?” And then you remark on this: On the contrary, this experiment was a compelling experimental demonstration of the power of humans to invent complex and sophisticated tools to help them solve their problems. That takes intelligence. Earlier you said “The engineer has defined both the problem (where is the optimum?) and its solution (an efficient search algorithm). The numbers may be new, but the creativity belongs to the engineer. The algorithm is simply a creative tool in his or her hands.”
But there is no ‘on the contrary’ or ‘simply’ about it, because the two perspectives are not mutually incompatible. In the chip experiment the humans designed the equipment and set the parameters for the selection process. They did indeed design the tool, and so without them the final result would not have been found. But it was the tool, the system, that found the exact configuration of the final chip. It was the system that generated the new information. The humans set the system up in the hope that it could do that, but they did not specify the final configuration of the chip in advance. They specified what the ideal chip should be capable of doing but that is not the same as specifying how it should do it. They did not work that out: the system worked that out. What this means is that it is in principle possible for a physical system to produce complex specified information. Populations of biological organisms exhibit random variation plus selection plus replication and thus can in the right circumstances generate increased complex specified information.
3) Do these examples differ so much from natural selection that they have no evidential value for Darwinism?
On several occasions, Neil, you have said of these kinds of experiments things like:
“this process is very far from being a model of Darwinian evolution in biology”
“My argument all along has been that the processes in these algorithms are working in a far-from-Darwinian fashion.”
“these algorithms, by definition, cannot be a truly Darwinian process”
“I want to stand by my comment that these algorithms are working in a far-from-Darwinian fashion, and they are definitely not demonstrating a Darwinian process”.
3.1) Firstly, the (repeated) use of the words ‘far from’ is unjustifiable. These systems use random variation plus selection plus replication – the very elements of neo Darwinian natural selection. They are therefore NOT ‘far from’ a Darwinian process.
3.2) But having said that one must still consider whether the algorithms are so far different from selection in the real biological world as to be worthless as support for neo-Darwinism. To make that point you have argued about things like the fitness function, mutations, constraint. These differences (and they vary depending on which algorithm we are talking about) do limit the extent of the conclusions that can be drawn from the algorithms. However, none of the differences, especially in the chip experiment we have been considering is such as to make them of no value.
3.2.1) The argument about mathematics:
You said on 23 June, 2004 11:31 of genetic algorithms: “I do not think that they are a model of Darwinian evolution, unless you are prepared to accept that natural selection can operate in a mathematical fashion according to intelligently determined numerical rules with a clear sense of purpose behind them.” But this has as little merit as saying that “I do not think that computer models of bridge behaviour a model of real bridge behaviour, unless you are prepared to accept that bridges can operate in a mathematical fashion according to intelligently determined numerical rules with a clear sense of purpose behind them.” Physical things of all sorts obey the laws of physics and chemistry and show statistical patterns and these can be modelled, more or less well, using numbers. There is nothing special about biology that rules out computer modelling [/I]a priori.[/I]
…
But I am out of time and must return to the other points later. However most of them I have already covered in an earlier post of the 12 July, 2004 06:42. Your comments on fitness in particular seem to reveal a lack of acquaintance with that topic and with the concept of selection.
Glenn
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Originally posted by Glenn Oldham:
Organisms are tested against other organisms in terms of which of them are better able to survive and reproduce. What enables them to best do this changes over time. It is still a selective process as much as that in the experiment. If you want an experiment which models Darwinian evolution more accurately then this one is appropriate: The evolutionary origin of complex features- a pdf file
You will note that complex specified information is generated.
Glenn, thank you for the reference to the Nature paper on AVIDA. As it happens, there has been considerable discussion on AVIDA in recent weeks at both the ARN and ISCID forums, so I was partially aware of this software. For anyone interested, it is available for free download to the general public here.
I have printed out the Nature article and am presently studying it for myself. It is clear that AVIDA is substantially more sophisticated than the genetic algorithms we have discussed to date, so it may take me a while to get my head round the various logic functions that constitute an AVIDA “critter”. If I become confident that I understand how it is working (and at present I am not), then I may come back with some detailed observations.
However, I do have one preliminary observation on the Nature paper: Nature is a prestigious scientific journal, yet the paper cites as a reference “The Blind Watchmaker” by Richard Dawkins. Clearly the paper authors consider this to be an appropriate work of reference for the scientific background of the evolutionary process they are modelling in their software.
So, before we get into further debate about either AVIDA, I want to be sure that we understand the same thing about a Darwinian evolutionary process. In The Blind Watchmaker, shortly after his famous "weasel" algorithm, Richard Dawkins says this on page 50, with his emphasis:
quote:
Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in various 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 long-term goal. There is no long distance target, no final perfection to serve as a criterion of 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 the short-term goal of 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 long-term goal.
So that is how Dawkins describes a Darwinian process. Natural selection has “no long distance target”. It is “blind to the future and has no long-term goal”. He does not say that there may possibly be a long-term goal behind it, but we have yet to discern it, whether using scientific tools, or indeed any other tools. No, he is very specific indeed. There is definitely no purpose to natural selection. Any form of teleology is completely out. We are an accident of nature.
As this thread has noted many times now, we are surrounded by everyday processes that form a complex result by a process of cumulative selection in tiny incremental steps. In just 9 months a single fertilised cell grows by a cumulative stepwise process into a baby, a most impressive example of macroevolution in the most general sense of the word. But of course, an embryonic process is not a Darwinian process.
So, before we get into further discussion about Dembski and whether natural selection can create complex specified information, my question to you is this: How do we distinguish between a Darwinian evolutionary process and a non-Darwinian one? How do we decide whether the selection we observe in a modelled evolutionary process properly models natural selection, and not some other form of selection? What are the essential determining criteria for natural selection?
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Faithful Sheepdog
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# 2305
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Posted
Glenn, unfortunately we appear to have cross-posted. I will consider your latest post and respond in due course.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Faithful Sheepdog
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# 2305
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Posted
quote:
Justinian said:
That an evolutionary algorithm won't come up with a solution the designer couldn't have found. The solution found by an evolutionary method had parts of the circuit not actually connecting to the circuit- something no human designer would come up with. (IIRC that's the reason I brought this up in the first place)
I read this assertion the first time you posted it, but it is no more correct now than then. Firstly you are not comparing like with like. You are confusing the normal process of electronic circuit design using conventional methods with one of the key points to this experiment, which was to investigate a highly unconventional situation.
Engineers normally utilise conventional circuit design methods because they know in advance that they will work. In this case conventional methods were excluded from the start by the explicit aim of the experiment: Was there any chip configuration at all that could achieve the desired result? At the start no one knew the answer.
The genetic algorithm made answering the question in a reasonable time frame a practical proposition. With a search space of 10E+542 configuration possibilities, it would need a lot of human technicians and even more time to complete the experiment by a crude process of blind search, noting the results manually.
However, what you have conspicuously failed to consider is that a crude blind search process by humans, using the same functional tests and equipment as the computer experiment, would eventually get to the same answers as the genetic algorithm. All that the computer has done is to save someone from a great deal of highly laborious lab work.
Intelligently designed software can certainly be a very beneficial scientific tool, but then that is hardly news.
quote:
Justinian said:
None. Neither do I have a backup life. In order to have reducible complexity, you need for there to be two distinct but identical entities.
On the other hand, the circuit indicated earlier developed through evolution rather than direct design- and it being an electronic circuit, it ipso facto was irreducibly complex as removing certain parts would break the circuit.
So we have an evolved object that is irreducibly complex. Counter example presented.
Yet more evidence that you do not understand the concept of irreducible complexity. This concept certainly does apply to some (but not all) electronic circuits, as you will know when your TV or computer dies completely due to a failed component.
However, it is by no means applicable to all engineering systems in all circumstances, and in many cases may only apply to a distinct subset of any system. You may lose the red colour gun on your TV, but otherwise it still functions, after a fashion. But a brick through the screen will ruin your whole day. ![[Smile]](smile.gif)
The microchip and all its electronic circuit connections and connection possibilities were a given at the start of the experiment. Hence the computer was not evolving any physical objects at all. What the computer manipulated and evolved was the 1800 configuration bits required to control the chip, eventually finding a configuration that produced the required functional behaviour.
Your argument presumes that the concept of irreducible complexity can apply to 1800 bits of computer information, but unfortunately you are seeking to apply this concept to a context where it is completely inapplicable. Here is Behe’s definition again:
quote:
By irreducibly complex I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning.
Information held in a computer memory has no interacting parts, well matched or otherwise, and certainly no function as a single engineering system. Hence the concept of irreducible complexity cannot possibly apply to a string of 1800 parameters held in a computer memory. The concept is irrelevant in this case.
Counter example rebutted.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Glenn Oldham said:
Neil,
There are three main aspects of your arguments about genetic algorithms that I want to address. The first two are the questions of whether any new information is created by the experiments and, if so by whom. The second is whether these genetic algorithms are so different from natural selection that they have no evidential value for neo-Darwinism.
Glenn, thank you very much for your post. You have certainly represented my views fairly, using my own words. I think I’ll address each of your points in turn, leaving as much of the formatting intact as I can.
quote:
Glenn Oldham said:
1) On whether new information is created.
In my immediately previous post I explained that one thing being claimed for these genetic algorithms is that they show that random variation plus selection plus replication is capable of generating new complex specified information. Now, since it is a claim of Darwinian theory that random variation plus selection plus replication is a key factor responsible for the adaptations of organisms to their environment, then experiments like this one clearly have relevance to that claim and provide evidential support for it. It is absolutely clear from this experiment (the 10 x 10 microchip one) that something new was produced: in this case it was a new configuration of a chip that had the ability to perform a complex electronic function.
On an earlier post (30 June, 2004 23:14) you said:
quote:
Firstly, there is a sense in which the optimised design that emerges from the evolutionary algorithm can rightly be called new, since that particular combination of parameters has probably never seen the light of day before. …
However – and this is the but – the algorithm cannot break away from the original N parameters and the programmed constraints to give us the answer to a problem with N+M parameters and a different set of constraints. The program begins with N parameters for a specific engineering problem, and finishes with N parameters – for that same problem. So in that sense nothing has changed. We simply have a more desirable set of numbers than we started with.
[…]
So at the start, even before the algorithm has begun “number crunching”, all fitness values in the xyz space have been defined in principle by the programmed fitness function(s) and all the other constraints. There is a sense in which the program knows in advance the fitness values for all possible x, y and z values. The only problem remaining is the exact x, y and z location(s) of maximum fitness within the permitted region.
The program does NOT know ‘in advance the fitness values for all possible x, y and z’ values. If it can be said to know anything it can be said to know how to calculate the fitness value. In this case if either the humans or the system knew the exact specification of the successful chip configuration ’in advance’ then they could have configured the chip straight away without having to run the random variation plus selection experiment to find it. In this case they could not.
I think my reply here will start with the fact that computers “know” things in a very different sense to the way humans “know” things. Since computers have no self-awareness, I would argue that they actually “know” nothing in a human sense – colloquial language is somewhat loose here. What they do have is access to binary data that is provided for them by humans and instructions on how to manipulate that data, also from humans.
So I think your distinction between a computer having a fitness value “in advance” versus only “knowing” how to calculate it is a spurious one. If the computer did not know how to calculate a fitness value, it could never give us any fitness values at all. Access to the fitness values follows as a logical consequence of having access to the fitness function.
Maybe it would be a little clearer to say that the given fitness function has defined in advance the set of all possible fitness values. As data becomes available from the experiment, the computer then calculates a fitness function value. This arithmetical calculation obtains the relevant value from the pre-existing set of all possible values.
When a genetic algorithm is given a fitness function in the form of a mathematically continuous real equation, as in the experiment, the computer is provided at the start with some wide-ranging and highly-specified information. Without it there is simply no problem to solve.
But note that even if we throw away the computer and revert to blind search by humans – the slowest and crudest possible search technique – humans would still need that same information about the fitness function to make any progress. With that information they would eventually reach the same solution as the computer (but with 10E+542 possible configurations I wouldn’t want to be the project manager on that job ).
quote:
Glenn Oldham said:
2) What creates the new information?
When we turn to the question of to what we are to attribute the creation of the new information you quote from a paper that says: “The circuit evolved, without any intelligent guidance, from a completely random and non-functional state to a tightly complex, efficient and optimal state. How can this not be a compelling experimental demonstration of the power of evolution?” And then you remark on this: On the contrary, this experiment was a compelling experimental demonstration of the power of humans to invent complex and sophisticated tools to help them solve their problems. That takes intelligence. Earlier you said “The engineer has defined both the problem (where is the optimum?) and its solution (an efficient search algorithm). The numbers may be new, but the creativity belongs to the engineer. The algorithm is simply a creative tool in his or her hands.”
But there is no ‘on the contrary’ or ‘simply’ about it, because the two perspectives are not mutually incompatible. In the chip experiment the humans designed the equipment and set the parameters for the selection process. They did indeed design the tool, and so without them the final result would not have been found. But it was the tool, the system, that found the exact configuration of the final chip. It was the system that generated the new information. The humans set the system up in the hope that it could do that, but they did not specify the final configuration of the chip in advance. They specified what the ideal chip should be capable of doing but that is not the same as specifying how it should do it. They did not work that out: the system worked that out. What this means is that it is in principle possible for a physical system to produce complex specified information. Populations of biological organisms exhibit random variation plus selection plus replication and thus can in the right circumstances generate increased complex specified information.
IMO I think you are using language loosely again when you say that “the system generated the new information”. Computers do not in fact “generate” anything new in the sense of “create”. What a computer can do is to search much more efficiently than any human through a much larger range of possibilities.
However, a computer cannot tell you anything that wasn’t first put into the computer by a human. The proof of this is simple. Take any computer. Do not give it any data or software outside the basic operating system. Ask it any question you wish (outside basic operating system parameters). I guarantee that you will get no answer.
I also think you are using the phrase “work out (the configuration)” somewhat loosely here. I think a more accurate phrase in relation to the source of the final configuration would be “pre-existing information found through an efficient search pattern”.
I would argue that the computer sorted through a range of possibilities, albeit in a much more efficient manner than any human, but that this range of possibilities was defined beforehand by a human. The information associated with that range of possibilities was therefore provided by a human.
quote:
Glenn Oldham said:
3) Do these examples differ so much from natural selection that they have no evidential value for Darwinism?
On several occasions, Neil, you have said of these kinds of experiments things like:
quote:
“this process is very far from being a model of Darwinian evolution in biology”
“My argument all along has been that the processes in these algorithms are working in a far-from-Darwinian fashion.”
“these algorithms, by definition, cannot be a truly Darwinian process”
“I want to stand by my comment that these algorithms are working in a far-from-Darwinian fashion, and they are definitely not demonstrating a Darwinian process”.
3.1) Firstly, the (repeated) use of the words ‘far from’ is unjustifiable. These systems use random variation plus selection plus replication – the very elements of neo Darwinian natural selection. They are therefore NOT ‘far from’ a Darwinian process.
This comes back to my earlier post about the precise criteria to define a Darwinian process. Any old selection is not good enough – it must be natural selection. I hope that we are agreed on that, although I notice that you often say “selection” rather than “natural selection”. This is not mere semantics, and the difference is crucial.
I am certainly not denying that an intelligently designed teleological selection process can deliver some impressive results, but that, by definition, is not natural selection. The article at Talk.Origins lists at least 9 different types of selection used in these algorithms. If the selection process in the algorithm imports some hidden form of teleology, then my previous comments are fully justified.
I would like to hear your response on the specific criteria to define natural selection within a Darwinian process before I comment any further, otherwise the argument degenerates to a “yes it is, no it’s not” type of exchange.
quote:
Glenn Oldham said:
3.2) But having said that one must still consider whether the algorithms are so far different from selection in the real biological world as to be worthless as support for neo-Darwinism. To make that point you have argued about things like the fitness function, mutations, constraint. These differences (and they vary depending on which algorithm we are talking about) do limit the extent of the conclusions that can be drawn from the algorithms. However, none of the differences, especially in the chip experiment we have been considering is such as to make them of no value.
I have only encountered these algorithms thanks to this thread, and they are clearly useful mathematical tools, inspired by evolutionary ideas. However, it’s fairly obvious from the article at Talk.Origins that some Darwinists do consider them to be corroborating evidence for biological Darwinism.
But what I find amazing about this article is the way that virtually no arguments are provided to say why these algorithms bear any necessary relation to biological Darwinism, something I have already complained about on this thread. After a long, informative and mostly factual description, the article launches straight into a rebuttal of “Creationist Arguments”.
I find this extraordinarily naïve, and evidence that metaphorical language has been misunderstood in a very literalistic fashion. The basic argument seems to be that, just because I can model an evolutionary process of some kind on a computer, that is evidence for a Darwinian evolutionary process to be true in the biological world. If there is a more sophisticated argument there, I haven’t found it yet.
This argument can be scotched easily by reference to the computer graphics in modern films, which are highly impressive, and also highly fake. I’ve been accused of erecting a strawman several times on this thread already, unfairly in my opinion, but this is one occasion when I will be glad to have my misconceptions pointed out to me. Is there a more sophisticated argument that links these algorithms to biological Darwinism?
quote:
Glenn Oldham said:
3.2.1) The argument about mathematics:
You said on 23 June, 2004 11:31 of genetic algorithms: “I do not think that they are a model of Darwinian evolution, unless you are prepared to accept that natural selection can operate in a mathematical fashion according to intelligently determined numerical rules with a clear sense of purpose behind them.” But this has as little merit as saying that “I do not think that computer models of bridge behaviour [are] a model of real bridge behaviour, unless you are prepared to accept that bridges can operate in a mathematical fashion according to intelligently determined numerical rules with a clear sense of purpose behind them.” Physical things of all sorts obey the laws of physics and chemistry and show statistical patterns and these can be modelled, more or less well, using numbers. There is nothing special about biology that rules out computer modelling a priori.
I am all in favour of the use of computers in biology and science generally to model and study physical behaviour. However, I am also a great believer in the aphorism “To forgive is divine, to err is human, but to really screw things up you need a computer”.
My highlighted comment above was very specific to genetic algorithms, as my summary of the algorithmic logic at work. The Talk.Origins article cites genetic algorithm models in all sorts of diverse fields as support for Darwinism. Either I am misreading these models badly, or Darwinists are quite mistaken in claiming them as support for their position.
Although I intended my comment to be for genetic algorithms, I would note that it is indeed also applicable to bridge models, especially during the construction stage when bridges change regularly, and are arguably at their most vulnerable. The design of the construction sequence is frequently a crucial stage for a major bridge.
One of the reasons I am jumping all over these particular models is that my professional work has involved me in critiquing computer models in relation to structural integrity and nuclear safety issues. If I told the vetting authorities, “Nuclear power is safe, the computer model says so”, I would be justifiably asked (and indeed have been) to demonstrate how realistic my model was, before my word would be accepted.
The computer model needs to be an accurate reflection of physical reality. Even then, any model is only ever as good as the assumptions and data in it. “Garbage in equals garbage out” is as true as ever. Even a good model delivering reliable results can be misinterpreted by a fallible human, or misused by a perverse one. Humans are always the weak link in the chain, since the buck stops with us.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Glenn Oldham
Shipmate
# 47
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Posted
Oops, another cross post Neil,
Neil,
I have been laid up so sorry for the delay in continuing my earlier post about the genetic algorithms:
I was on section 3) Do these examples differ so much from natural selection that they have no evidential value for Darwinism?
…
And I had got to the bit about the points you have raised regarding things like the fitness function, mutations, constraint. These differences do limit the extent of the conclusions that can be drawn from the algorithms, but they don’t render them worthless as support for neo-Darwinism.
…
3.2.2) Points about fitness.
3.2.1) Unfitness One of your comments on the chip experiment was “I consider that this is an example of unconstrained evolution, starting with an completely unfit (i.e. dead or unsuccessfully breeding) life-form and passing through many unfit stages (but still breeding), until the numbers enter a region where the fitness function starts giving desirable answers”
This is to misunderstand fitness. The experiment can be seen as modelling the case of a trait or function that is advantageous to the organism but lack of which does not prevent the organism from living and reproducing. It just makes it less fit than its fellows that possess the trait. An example would be a rabbit like animal that ran in a straight line from its predator compared with one that ran but also zigzagged. The latter strategy may be more successful and a rabbits showing that trait would, on average, survive to breed more successfully than those that did not. But those that ran straight would not thereby all die. The experiment could be seen as analogous to that kind of case. There would be no problem at all with the population showing no evidence of zigzag running either initially or for generations. Once the trait starts to appear though selection can get going. (See also 3.4)
3.2.2) The fitness function I have already dealt with some of your comments on the fitness function. To address your most recent in your post of 18 July, 2004 16:28 where you appear to have been, at best, misled, by kens unfortunately loose wording. You quoted ken as saying: “In real life biological fitness isn't a function. It's a count - the number of descendents something has. And it is of course contingent, historical. The continuously variable fitness numbers used in models are just that, models. And deterministic equations are very bad models of evolutionary or ecological processes. Stochastic ones better, but individual-based modelling better still.” Then you then said:
quote:
let’s look more closely at how the experiment operated … it assigned a fitness value to each individual in each generation by reference to equation 1 in the paper. This equation incorporates all the information necessary to specify the final end point, the goal of the process. … In the light of these comments For each individual an absolute fitness was established by constant reference to this desired end goal. ... these algorithms have access to an “ideal” at all times – the specified end goal. … . these algorithms, by definition, cannot be a truly Darwinian process. They are driven throughout by a goal-oriented methodology,
It is a mistake to deny (as ken seems to do) the link between fitness and function. Darwinism depends on the view that some variations are genuinely, physically, advantageous to the organism. They don’t get to breed more than others just by chance but because the variation makes them more capable of doing something that promotes their breeding than their fellows and THAT increases their chances of breeding. The equation in this experiment was used to determine which of current configurations in any generation was performing the functions most nearly correctly. It compared what they were doing with what they were ideally intended to do. There is nothing inherently problematic with this. Lots of fitness in the wild could be assessed in this way. Which rabbits run most in a zigzag fashion? Or which animal has the more opposable thumb, and so on. (From the informational point of view it is crucial to be clear that the equation did not compare how they were doing it with how it would finally be done, by the way - it is NOT true to say that “This equation incorporates all the information necessary to specify the final end point” in the sense of it being able to specify the final configuration.)
quote:
these algorithms are not modelling natural selection as understood within Darwinism. In them the selection process means “nearer to the specified target”, not “who has the most grandchildren”. The experiment is not counting the descendants, and then deducing a theory from that empirical data. Instead it imposes a deterministic form of differential breeding in a pre-determined manner.
What ken said has again misled you here. Selection operates by, on average, ensuring that those offspring with the advantageous variation breed more than those without. A selection process that selected to breed those individuals that had the most grandchildren would not be able to start, or would be viciously circular, since who has the most grandchildren depends on who is selected to breed.
quote:
My third point is that this whole experiment was functionally deterministic, not stochastic. If the experiment was run again, it would converge to the same functional target. It is not free to do anything else. A true stochastic process would be free to give a different result and converge to some other functional target.
The stochastic character of evolution is that chance enters into whether an organism gets to breed and not just whether or not it has an advantageous variation. There was some element of the stochastic in the experiment in that some of the less well-adapted individuals got to breed as well. I do not see that making the process more stochastic would alter the final outcome. Selection would still be operating in the direction of the function chosen. It might well take a different route and take longer to get there, but the change would be in the direction of improved matching to the function. Incidentally, if the experiment was run again there is no guarantee that the same final configuration would be arrived at. There may be many such configurations for all we know.
3.3) Mutations You made a number of remarks about deleterious mutations not being allowed suggesting that the individuals were unkillable and so on. Well, deleterious mutations were allowed but, of course, did not get to breed because their fitness was therefore less than the others. (see also 3.4)
3.4) What is mutating? ‘What is mutating?’ are not your words but mine to pick out a question that incorporates one of your points about fitness and about mutation. You may have felt my 3.2.1 was overlooked something. Once the genotype for the trait shows some degree of fitness then selection can get going, fair enough. But what happens prior to that? If, in the early stages of the experiment no fitness was shown by the individuals there may have been some generations where the genotype of the individuals was varying in an unconstrained fashion. Could this happen in real life? What is mutating, exactly, and how unconstrained can it be in how much it mutates? Surely you can’t have unconstrained mutation that does not make the organism unfit?
Well, this is where things like gene transposition and gene duplication can get going. In gene duplication for example, a gene for a particular protein duplicates. If one of the genes then mutates then even if its own functionality is compromised it may have no deleterious effect on the organism because the other genes operation is unimpaired. The duplicate gene may then mutate further with comparatively little constraint. If it then changes so that it acquires a mildly beneficial function then selection can begin to operate on it.
This is not an ad-hoc face saving explanation since we have compelling grounds, from DNA sequencing, for believing gene duplication and transposition (and indeed chromosome duplication) to have been a major feature of evolutionary history.
Conclusion
The chip experiment does model the Darwinian selection of an advantageous trait although it has limitations. It does, however, show that a system that combines variation, selection, reproduction and inheritance – the essential features of natural selection – can evolve and improve a function. It is a particularly nice aspect of this experiment, as opposed to other algorithms, that it did not have the final configuration specified in advance as its target. Instead only the function was specified, NOT the configuration that it must use to get it. Indeed non-one knows if the final configuration is the only configuration that would work.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Glenn Oldham
Shipmate
# 47
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Posted
quote:
Originally posted by Glenn Oldham:
Oops, another cross post Neil,
Sorry, I meant 'crossed post' ( not 'cross post' as in ![[Mad]](angryfire.gif) )
____
You asked a question (which turned out to be three!)
quote:
Originally posted by Faithful Sheepdog:
So, before we get into further discussion about Dembski and whether natural selection can create complex specified information, my question [singular!] to you is this:
[1] How do we distinguish between
· a Darwinian evolutionary process and
· a non-Darwinian one?
[2] How do we decide whether the selection we observe in a modelled evolutionary process properly models
· natural selection, and not
· some other form of selection?
[3] What are the essential determining criteria for natural selection?
The key elements of Darwinian selection are variation, selection, reproduction, and inheritance (these last two are often just called ‘replication’). So we have:
1) Variation within a population of entities. The cause of the variation is a random process. It needs to be noted that ‘random’ here does not mean ‘completely without pattern or limit or constraints’. It just means that the cause of the variation is random with respect to whether the variation is advantageous to the entity or not. There are obviously going to be physical and chemical limits and tendencies involved in the way in which variation can arise. The contrast here is with the variation proposed in Lamarckian evolution which is automatically advantageous, for example where the striving of the animal for leaves on higher branches supposedly gives it a longer neck than it inherited. Without variation there would be nothing for selection to ‘choose’ between. If all individuals in a population are identical for a particular trait then natural selection on that trait cannot occur.
2) Selection that is non-random. This simply means that some variations give the individual entities that possess them an advantage (or advantages) over their fellows by enabling them to produce more offspring, on average, than those individuals that do not possess one of those variations.
3) Reproduction. This just means that there must be individuals in the population that reproduce. If there is no reproduction then the cycle cannot repeat and the change lasts one generation only.
4) Inheritance. The advantageous variation must be heritable. If the variation is not heritable then it is lost and future generations are unable to benefit from it or natural selection build further variation on it. The heritability need not be 100% but if the heritability is too low then the variation is more likely to be lost.
Any selective process that incorporates these elements or analogues of them deserves to be called a Darwinian selection process.
It is because so many of the evolutionary algorithms DO incorporate these elements that they can lay claim to modelling Darwinian selection. Clearly, the more it can include other relevant variables from nature then the better it can model natural selection. For example, having different types of creature competing with each other for resources. This means that the fitness criterion for one organism will change even more over time if the other species it competes with is evolving and presenting new challenges.) The limits to the models limit the evidential support that they offer to neo-Darwinism but do not invalidate that evidence.
One rhetorical tactic popular with some anti-Darwinian’s is to say of a piece of evidence that if it is not proof then it is not evidence. That is fallacious. Just because a piece of evidence does not conclusively establish the truth of the conclusion does not mean it is of no evidential importance at all. The case for neo-Darwinian evolution is a cumulative case and these algorithms add to that cumulative case. Insofar as someone considers that case to be fatally flawed in other areas not related to selection then these algorithms are unlikely to persuade them.
Philip Johnson is charged by Nancy Murphey with this kind of illogic. One theory of the origin of life for example says that organic molecules could be formed in the primordial environment by ordinary chemical reactions in certain conditions. They replicate what they think the conditions were, including artificial lightning etc and organic molecules are formed. Philip Johnson then argues that because the experiment did not create life, is not an instance of the creation of life then it provides NO reason to believe the theory. But this is nonsense. It does not prove the theory but it provides support for one part of it. It is certainly not irrelevant data that can responsibly be ignored!
Likewise with genetic algorithms. Even though they are not instances of natural selection and so do not conclusively prove evolution by natural selection they do provide confirmatory support that the proposed mechanism for natural selection may be correct.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Faithful Sheepdog
Shipmate
# 2305
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Posted
Glenn, I will reply to your latest post in due course, but that may be later today (Thursday) or even tomorrow. To avoid any more cross-posting I suggest that you wait until then if you wish to reply further.
In the meantime here is a brilliant example of irreducible complexity in action. You'll need Flash 6 and the picture is a little dark on my screen, but otherwise it is a perfect example. One tiny component out of place and the system would not work at all.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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ken
Ship's Roundhead
# 2460
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Posted
quote:
Originally posted by Faithful Sheepdog:
In the meantime here is a brilliant example of irreducible complexity in action. You'll need Flash 6 and the picture is a little dark on my screen, but otherwise it is a perfect example. One tiny component out of place and the system would not work at all.
One suspects the influence of a human designer.
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Ken
L’amor che move il sole e l’altre stelle.
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ken
Ship's Roundhead
# 2460
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Posted
quote:
Originally posted by Glenn Oldham:
It is a mistake to deny (as ken seems to do) the link between fitness and function.
I never did that!
In the bit you quoted we were talking about mathematical functions.
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Ken
L’amor che move il sole e l’altre stelle.
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Glenn Oldham
Shipmate
# 47
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Posted
quote:
Originally posted by ken:
quote:
Originally posted by Glenn Oldham:
It is a mistake to deny (as ken seems to do) the link between fitness and function.
I never did that!
In the bit you quoted we were talking about mathematical functions.
![[Hot and Hormonal]](icon_redface.gif) apologies, ken, so you were. I took it from the context in which Neil quoted you that you were referring to function as physical capacity/fitness, so either Neil misunderstood you or I misunderstood Neil (or both even).
Apologies again.
Glenn
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Glenn Oldham
Shipmate
# 47
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Posted
quote:
Originally posted by Faithful Sheepdog:
Glenn, I will reply to your latest post in due course, but that may be later today (Thursday) or even tomorrow. To avoid any more cross-posting I suggest that you wait until then if you wish to reply further.
Noted, Neil, but I will just add the following on a part of the topic on which you have posted the most recent response.
Neil, one issue we have been discussing is the question of whether or not new complex specified information was created in the chip experiment and what or who created or provided that information. This is relevant to the debate about Intelligent Design because some IDers (such as Dembski) deny that either natural selection or genetic algorithms can generate new ‘complex specified information’ (to use Dembski’s term).
I argued that the complex specified information was indeed new and that it had been generated by the system and not provided by the human designers of the system. In response you said (with bits snipped as indicated by ellipses):
quote:
Originally posted by Faithful Sheepdog:
I would argue that they [computers] actually “know” nothing in a human sense … What they do have is access to binary data that is provided for them by humans and instructions on how to manipulate that data, also from humans.
So I think your distinction between a computer having a fitness value “in advance” versus only “knowing” how to calculate it is a spurious one. … Access to the fitness values follows as a logical consequence of having access to the fitness function.
… the given fitness function has defined in advance the set of all possible fitness values. As data becomes available from the experiment, the computer then calculates a fitness function value. This arithmetical calculation obtains the relevant value from the pre-existing set of all possible values.
When a genetic algorithm is given a fitness function in the form of a mathematically continuous real equation, as in the experiment, the computer is provided at the start with some wide-ranging and highly-specified information.
IMO I think you are using language loosely again when you say that “the system generated the new information”. Computers do not in fact “generate” anything new in the sense of “create”. What a computer can do is to search much more efficiently than any human through a much larger range of possibilities.
However, a computer cannot tell you anything that wasn’t first put into the computer by a human.
I also think you are using the phrase “work out (the configuration)” somewhat loosely here. I think a more accurate phrase in relation to the source of the final configuration would be “pre-existing information found through an efficient search pattern”.
I would argue that the computer sorted through a range of possibilities, albeit in a much more efficient manner than any human, but that this range of possibilities was defined beforehand by a human. The information associated with that range of possibilities was therefore provided by a human.
First of all there is a very definite and precise piece of information whose origin we are discussing here. That piece of information is that which represents or describes the exact configuration of the chip in the experiment at the point near the end when it became perfectly functional call this information ‘X’. This information, X, that specifies that configuration is 1800 bits in quantity. Information can exist in a variety of forms and be encoded in a variety of ways (it could be written, a diagram, a physical model, magnetic blips on a disc, the configuration of the chip itself and so on). At the end of the experiment the information X was present in the system in at least two copies. Firstly, as the configuration of the chip itself and, secondly, in the memory of the computer which had just used that information to configure the chip in that pattern. The computer had just taken a very similar 1800 bit piece of memory and mutated it randomly to yield what turned out to be X the final configuration. In the computers memory the information X was probably a sequence of 0’s and 1’s 1800 digits long as magnetic blips or however such information is physically stored.
My contention is pretty simple, it is that:
- · X did NOT exist before that final step of the experiment either in the computer or on the chip or in the minds of the designers;
- · In other words, there was NO physical copy of X in existence before the final step of the experiment.
- · (It is possible that, by a freak of chance, amongst the trillions of binary digits represented on the computers discs and which make up the computers general software there might have been a string of 1800 digits identical to X (somewhere in the Solitaire or Word program, say). However, the presence of that X would NOT be the cause of X appearing as the final configuration. )
It is, therefore, false to say that the information X was provided by humans in the sense that they put X into the system. They did not because there was no copy of X entered into the system (and in this case the humans did not even possess a copy of X).
This is an important point and an important distinction because to hear some ID advocates talk you would imagine that that is exactly how they think that God does provide what they see as certain essential information to organisms that natural selection cannot otherwise acquire. This experiment shows that the provision of information in that direct way is NOT required for a Darwinian type of selection process to arrive at new complex specified information. Whether it is needed for certain types of allegedly supercomplex information such as for irreducibly complex systems is another question. What I am attacking here is the view that natural selection cannot arrive at complex specified information under any circumstances, without it being inserted into the system by a designer.
You say that:
quote:
” a more accurate phrase in relation to the source of the final configuration would be “pre-existing information found through an efficient search pattern”.”
But this is inaccurate. Information X was NOT ‘pre-existent’ in the information provided to the system. NEITHER was information X found by a search amongst ’ the pre-existing set of all possible values’ since there was never a complete set of such values in the computer at any time. As a comparison if I ask my calculator to tell me what 158,791 multiplied by 884,672 is it does not look up the answer on an internal table that lists the results of the multiplication of every possible set of two numbers (within some huge range). Instead, it calculates it using a basic set of repetitive instructions and says: 140,477,951,552. It is, therefore NOT literally true to say, as you do, that, “a computer cannot tell you anything that wasn’t first put into the computer by a human”. No-one put in 140,477,951,552 into my computer.
The actual information that the computer was provided with was, as you say, “wide-ranging and highly-specified information” and was “binary data … provided … by humans and instructions on how to manipulate that data, also from humans.” Indeed so, but it was not given the range of possible configurations in the form 0, 1, 10, 11, 100, 101, 111, 1000, all the way through to 1 followed by 1800 zeros. It is much more economical of information to tell the computer something like ‘the range of possible configurations is represented by a string of binary digits 1800 digits long where any digit can be 0 or 1’. This will take a lot of code, but less than listing the roughly 10 to the power 541 numbers individually. So, again, the computer was not provided with the number X that represented the final solution.
And, as you say, it is certainly true that “Access to the fitness values follows as a logical consequence of having access to the fitness function.” Yes, the computer had clear instructions how to calculate (or set up and measure in this case) the fitness values i.e. how well any given configuration performed its function. But having access to those fitness values does not mean that those fitness values were physically present in the computer. No copy of X was lying around in the memory or elsewhere in the system to be ‘accessed’.
So the humans did NOT provide the computer with the information X. BUT, you may protest, they did provide it with all the information it needed to arrive at X after a suitable series of search operations involving replication variation and selection. (I understand that this may be what Dembski confusingly and misleadingly describes as ‘front loading of information’.) I have no objection at all to saying that information X as a solution to the problem of performing the required function was inherent in the parameters and physical constraints of the system. But as I have pointed out before that is NOT in any way an anti-Darwinian view. A Darwinian is happy to agree that the adaptations and organisms that have arisen in nature are the results of the parts of the system at a variety of levels (molecular, cellular, organismal, etc) interacting in accord with laws of physics and chemistry and so on and that replication, variation, and selection operates wherever the conditions for it in the system are right.
The question of where the system comes from and whether it is designed is a separate question. Here I am simply looking at one argument against natural selection. If the system has a designer then evolution by natural selection can be seen as Intelligent Design. If the system has not got a designer then it cannot.
Glenn
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
Posts: 910 | From: London, England | Registered: May 2001
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Glenn Oldham said:
I was on section 3) Do these examples differ so much from natural selection that they have no evidential value for Darwinism
And I had got to the bit about the points you have raised regarding things like the fitness function, mutations, constraint. These differences do limit the extent of the conclusions that can be drawn from the algorithms, but they don’t render them worthless as support for neo-Darwinism.
My overall point with respect to genetic algorithms is that it is up to Darwinists to demonstrate the relevance of these particular computer techniques to actual biological processes, especially in the light of our now much enhanced knowledge of the biochemistry of genes and genetic functions. Talk.Origins is exceptionally bad in this regard, taking a huge amount for granted.
Genes are far more sophisticated things than simply a string of binary data in a computer. Yes, they contain information, but they do not act in the same way as a string of binary data in a computer. These differences are crucial to the true relevance of any computer models. Furthermore, as Richard Dawkins puts it on page 60 of “The Blind Watchmaker”:
quote:
But natural selection doesn’t choose genes directly, it chooses the effects that genes have on bodies, technically called phenotypic effects.
So there is the whole question of the genotype/phenotype distinction. There is no doubt in my mind that conventional genetic algorithms are selecting at the level of genes, and not phenotypes. These algorithms have no concept of a body or phenotypic effects within them. The fitness function acts directly on a string of binary data, metaphorically referred to as “genes”, but acting very differently to real genes.
So I would argue that there is in fact a major difference between these models and the biological facts, and in consequence they do not properly reflect Darwinian theory either. This conflation of genes with phenotypes appears in your post when you say:
quote:
This is to misunderstand fitness. The experiment can be seen as modelling the case of a trait or function that is advantageous to the organism but lack of which does not prevent the organism from living and reproducing. It just makes it less fit than its fellows that possess the trait. An example would be a rabbit like animal that ran in a straight line from its predator compared with one that ran but also zigzagged.
I think I’ve said enough about genetic algorithms for now. From what I can see the AVIDA programme is indeed a step in the right direction. It is certainly very different to the genetic algorithms we have been discussing. I am still trying to get my head round it, so I won’t comment on it any further.
From here on I will respond to your comments on the subject of fitness and mutation (21 July, 2004 16:46) and natural selection within a Darwinian process (22 July, 2004 10:20). To keep this post within limits I will only quote small fragments from your posts as necessary, but rest assured, they have been printed out and studied in full.
THE CONCEPT OF “FITNESS”
I will begin by noting that in “The Blind Watchmaker” the word fitness (or even unfitness) does not appear in the index at all. As a concept it would appear to have no use for Richard Dawkins. This would tally with what I have heard of Darwin himself, who apparently never used the phrase “survival of the fittest”. He spoke of “useful variants” or “usefulness”. You use the word “advantageous”.
Whilst the concept is of usefulness or fitness would appear to be intuitively obvious, it is impossible to measure them independently of actual survival and reproduction, without ending up in a hopeless tautology. That is why Ken spoke of fitness in terms of counting numbers rather than any form of [mathematical] function. Here are his words again with one edit of mine:
quote:
In real life biological fitness isn't a [mathematical] function. It's a count - the number of descendents something has. And it is of course contingent, historical. The continuously variable fitness numbers used in models are just that, models. And deterministic equations are very bad models of evolutionary or ecological processes. Stochastic ones better, but individual-based modelling better still.
I do not think it was misleading of him to speak in this way. All we can hope to measure is differential survival. I am certainly happy to accept that in any given generation in any population, there will be variations between individuals – for any and every reason – better hunter of food, better defences against predators, better resistance to disease, etc.
If we define the reproductive success x as the number of offspring per individual, then there is certainly no reason for x to be constant throughout the population. x may be distributed in all sorts of ways, as it is in human mothers.
However, I do not think there is any way in which x can be directly measured at a given moment. We can only determine the value of x for an earlier generation by a count of the later offspring. Its value only becomes clear in retrospect, assuming that we are monitoring data. This is certainly how Kettlewell did his famous peppered moth research (but note in fact that he counted the parental survivors rather then the offspring).
This contrasts completely with a conventional genetic algorithm, where each generation has access directly to the relevant x value before the generation “gives birth” numerically. You speak truer than you think when you say:
quote:
A selection process that selected to breed those individuals that had the most grandchildren would not be able to start, or would be viciously circular, since who has the most grandchildren depends on who is selected to breed.
The only way to break out of this circularity in a genetic algorithm is to impose onto the algorithm a concept of fitness – the fitness function - that can be clearly distinguished from subsequent reproductive success (x). Reproductive success can then be linked to this separate concept of fitness in any manner that we choose. And that is certainly what the electronics experiment has done from here..
quote:
After evaluation of each individual on the real FPGA, the next generation was formed by first copying over the single fittest individual unchanged (elitism); the remaining 49 members were derived from parents chosen through linear rank-based selection, in which the fittest individual of the current generation had an expectation of twice as many offspring as the median-ranked individual.
As a numerical experiment it is of course perfectly acceptable to postulate all sorts of figures and scenarios for reproductive success (x) in relation to the fitness function, but it is at precisely this point that the algorithm has broken away from the real world of biology, where we simply cannot measure fitness in a given population directly and do not have access to the reproductive success (x) until a much later time.
By giving the computer access to this privileged information, we have a Deus ex machina driving the answers in a certain predetermined way as a starting assumption. IMO this invalidates any appeal to the success of the algorithmic methodology as necessarily demonstrating anything in biology.
MUTATION
I won’t say much on this subject. Paradoxically I threw in my comment on mutation rates as a response to a comment from Rex Monday who said, with my emphasis:
quote:
So, the problem you propose that the model may not address doesn't exist, and the lack of correspondence between the model and nature doesn't exist either. (there are plenty of other lacks: it is, like Camelot, only a model.
The electronics experiment was not set up specifically to model a biological process – it was to investigate electronic possibilities using a certain algorithmic approach. It is now being discussed as biological evidence only in a secondary and derivative fashion. It is therefore unfair of me to critique it on the subject of mutation rates.
It is my understanding that, in the mathematics of evolutionary genetics, excessive mutation rates are deleterious to the species as a whole, resulting in an “error catastrophe”, but this is something I need to investigate further. Let’s not forget that the vast majority of observed mutations in nature are highly deleterious. Very few – the raw material for Darwinism - are beneficial (see pages 306-307 of TBW).
Incidentally, the average mutation rate in the electronics experiment was 2.7 [bits] per genotype [of 1800 bits], not 2.7% (i.e. percent) as quoted by Justinian above. 2.7 bits is 0.15% of an 1800-bit genotype, a much lower figure.
NATURAL SELECTION
Firstly we have the definition that you give (which again, I note, simply says “selection”, not “natural selection”:
quote:
Selection that is non-random. This simply means that some variations give the individual entities that possess them an advantage (or advantages) over their fellows by enabling them to produce more offspring, on average, than those individuals that do not possess one of those variations.
Bearing in mind my earlier comments on the profound difficulties with the definition of “advantage” or phenotype fitness (as opposed to Ken’s concept of counting survival numbers), here is how American neo-Darwinian geneticist John Endler in his book “Natural Selection in the Wild” sets up a syllogism for his understanding of natural selection:
quote:
If, within a species or population, the individuals:
a) vary in some attribute or trait q (physiological, morphological, or behavioural) – the condition of variation;
b) leave different numbers of offspring in consistent relationship to the presence or absence of trait q – the condition of selection differences;
c) transmit the trait q faithfully between parents and offspring – the condition of heredity;
d) then the frequency of trait q will differ predictably between the population of all parents and the population of all offspring.
(This is quoted in the July/August 1999 edition of Touchstone Magazine in an article by Paul Nelson entitled “Unfit for Survival: The Fatal Flaws of Natural Selection” – unfortunately I can’t link to this article. However, this edition has also now been published as a book called “Signs of Intelligence”, edited by William Dembski and James Kushiner, published by Brazos Press 2001, available from ARN here.)
So, under Endler’s formulation, we must demonstrate that conditions a), b) and c) are all satisfied, before we can infer consequence d), i.e. that any variation in the frequency of trait q in the offspring relative to the parents is due to “natural selection”. Note that this syllogism avoids any form of circularity or tautology by rigorously excluding any consideration of “the quality of the phenotype”.
According to Nelson’s interpretation of Endler, natural selection is “simply a directional shift in the trait frequencies of species”, and no more. Endler therefore agrees with Ken that natural selection is about natural history, not natural philosophy. It is descriptive, not prescriptive. It is a statistical statement, not a “mechanistic, causal account” (Dawkins).
Nelson quotes Endler (who is a neo-Darwinist) as follows:
quote:
To say that a new adaptation necessarily arose through natural selection is an incomplete description, a tautology, and a misrepresentation of natural selection, adaptation and evolution.
In comparison with this, we have already seen how Richard Dawkins describes natural selection on page 50 of The Blind Watchmaker:
quote:
Evolution has no long-term goal. There is no long distance target, no final perfection to serve as a criterion of 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 the short-term goal of 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 long-term goal.
and Dawkins goes on to say on pages 61 and 62 of “The Blind Watchmaker”, immediately after the section on biomorphs:
quote:
But this isn’t getting us any closer to simulating natural selection. The important point is that nature doesn’t need computing power in order to select, except in special cases like peahens choosing peacocks. In nature the usual selecting agent is direct, stark and simple. It is the grim reaper. Of course the reasons for survival are anything but simple – that is why natural selection can build up animals and plants of such formidable complexity. But there is something very crude and simple about death itself. And non-random death is all it takes to select phenotypes, and hence the genes they contain, in nature.
These appear to be the sole references to the definition of natural selection in “The Blind Watchmaker”, but then he may have returned to the subject in his other writings (which I do not have). So we have natural selection as “simple survival”, “reproductive success” and “non-random death”. Dawkins gives us no further information, nor does he define what he means by non-random death. I notice that you use the phrase “non-random” too.
DARWINIAN PROCESSES
A deterministic process governed by natural law (such as gravity) is certainly non-random, but I very much doubt that this is what Dawkins means here. On the other hand, certain kinds of non-deterministic (i.e. stochastic) processes can be termed non-random, since they can be quantified accurately in terms of statistical properties which can be measured with consistency (wave action and wind turbulence come to mind from engineering).
This data can be used to predict future outcomes. We cannot say precisely what the wave height or wind turbulence will be, but we can cite probability bounds for them lying within a certain range under certain circumstances. Quantum mechanics in atomic physics operates similarly. But again I doubt that this is what he means.
So once again Dawkins is loose in his language. If he is using the word non-random in a special sense, then he needs to explain exactly how he is using it. Since you use the phrase as well, in what sense are you using non-random? Can you explain it any further?
Whatever is meant by non-random, it is clear that for Dawkins a teleological process of any kind would be completely unacceptable. This is the main basis for my many comments on the non-Darwinian nature of genetic algorithms. I sniff out a hint of teleology and shout “foul”, citing Dawkins as my authority:
quote:
Evolution has no long-term goal. There is no long distance target,…(TBW, page 50)
All I would insist on is that these respects [i.e. the non-random nature of mutations] do not include anything equivalent to anticipation of what would make life better for the animal (TBW, page 306, his emphasis)
I am beginning to suspect that one of the reasons for our lack of agreement on whether genetic algorithms can be considered a Darwinian process is our difference in understanding over exactly what natural selection is. Given the central role of natural selection in Darwinism, and the huge creative power assigned to this mechanism by Dawkins, “[it] can build up animals and plants of such formidable complexity” (TBW, page 62), I think I need a much better understanding. But is one available?
At the moment the definition is so vague that it can include not only all 9 types of selection in the genetic algorithms discussed at Talk.Origins, but just about any other type of deterministic or stochastic selection one cares to name, provided that it is “non-random”, whether teleological or otherwise.
I’m certain that Dawkins does not have any teleology of any kind in mind by natural selection. But is that consistent with neo-Darwinism as a whole, or even your own perspective? If there are no excluded forms of non-random selection, then this leaves the door wide open to a teleological form of selection and the brand of Intelligent Design that has much in common with a theistic form of Darwinism.
So, as a discussion starter, is there any form of non-random selection that is not natural selection? And if it’s not, why is it not?
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
Posts: 1097 | From: Scotland | Registered: Feb 2002
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ken
Ship's Roundhead
# 2460
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Posted
In the quote from Dawkins "non-random death" clearly means that the chance of dying is associated with some other character(s) of the organism. So if you know whether or not the organism has such-and-such a character or not you can make better predictions as to whether it will die before reproducing or not.
I think that is a more, not less, rigorous statement than the one y9ou quote earlier:
quote:
b) leave different numbers of offspring in consistent relationship to the presence or absence of trait
[...]
d) then the frequency of trait q will differ predictably between the population of all parents and the population of all offspring.
which perhaps goes to far in using the words "consistent" and "predictably".
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Ken
L’amor che move il sole e l’altre stelle.
Posts: 39579 | From: London | Registered: Mar 2002
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Faithful Sheepdog
Shipmate
# 2305
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Posted
This is in response to Glenn Oldham’s post at 23 July, 2004 10:09
quote:
Glenn Oldham said:
First of all there is a very definite and precise piece of information whose origin we are discussing here. That piece of information is that which represents or describes the exact configuration of the chip in the experiment at the point near the end when it became perfectly functional call this information ‘X’. This information, X, that specifies that configuration is 1800 bits in quantity.
<snip>
The computer had just taken a very similar 1800 bit piece of memory and mutated it randomly to yield what turned out to be X the final configuration. In the computers memory the information X was probably a sequence of 0’s and 1’s 1800 digits long as magnetic blips or however such information is physically stored.
My contention is pretty simple, it is that:
1) X did NOT exist before that final step of the experiment either in the computer or on the chip or in the minds of the designers;
2) In other words, there was NO physical copy of X in existence before the final step of the experiment.
3) (It is possible that, by a freak of chance, amongst the trillions of binary digits represented on the computers discs and which make up the computers general software there might have been a string of 1800 digits identical to X (somewhere in the Solitaire or Word program, say). However, the presence of that X would NOT be the cause of X appearing as the final configuration. )
I think there is some danger that we are now using the word information in various nuanced ways and arguing past each other. Looking back over my recent comments I can see places where I could have tightened up in places on my usage of the word information – I’ll come back to this in due course. It is an awkward term to define with full mathematical and philosophical precision, especially in Dembski’s usage.
Note also that each and every configuration of the chip is associated with 1800 bits of information, whether it delivers the required functionality or not. There is no informational difference between perfect functionality and none at all, they all contain 1800 bits. However, achieving the chosen functionality made a huge difference to the researchers and was the whole purpose of he experiment – teleology again!
Since the functional specification certainly did exist in the minds of the minds of the designers before the start of the experiment, your comment in 1) above cannot be sustained. Without the information of this target functionality, the experiment would have gone nowhere. But of course, they didn’t know the right configuration at that stage, or even whether one was possible.
A specified function was how the experiment was set up, and so the specified function is intimately associated with Dembski’s notion of complex specified information (CSI). By specifying one function they ruled out a huge number of others. Therefore there is a large informational content associated with that function – in this case 1800 bits.
quote:
Glenn Oldham said:
It is, therefore, false to say that the information X was provided by humans in the sense that they put X into the system. They did not because there was no copy of X entered into the system (and in this case the humans did not even possess a copy of X)
<snip>
This experiment shows that the provision of information in that direct way is NOT required for a Darwinian type of selection process to arrive at new complex specified information.
<snip>
What I am attacking here is the view that natural selection cannot arrive at complex specified information under any circumstances, without it being inserted into the system by a designer.
I can’t see that this conclusion is correct at all on the basis of the electronics experiment. You seem to think that providing the required functionality and the fitness function is not providing information in a direct way. I must disagree completely.
Dembski has attempted to use some general mathematical theorems regarding complex specified information (No Free Lunch), but for now I won’t go there – it’s too complex for me. I’ll concentrate instead on some details of the experiment, which are adequate for my purpose. At the beginning we have the following as givens:
- The configurable microchip with 10E+542 possible configuration states
- The computer programmed with a genetic algorithm, the fitness function equation and all associated software.
- All ancillary equipment such as the analogue integrator, connections to the computer etc.
- A target functionality, defined fully in the form of a mathematically continuous fitness function.
The experiment had two aims:
- Could any configuration achieve the specified function (this was not a given)?
- If so, what were the best configurations for delivering the specified function?
At this stage the experiment in principle was no different qualitatively to many others in the physical sciences where we test certain hardware to see if it can achieve a certain function, and how well it achieves that function. At the start we are ignorant of these facts, but we expect to learn something through the experiment. Full size or scale model load tests in engineering are a case in point.
The only significant difference in the present case was a quantitative one: There were 10E+542 possible states to investigate – a huge number. Could any configuration deliver the required function, especially since it was such an unusual one for such a chip? The experiment was set up to find out.
It’s important to note that the functional abilities of the chip were governed by the laws of physics. This included the various configuration states which were designed and built in to the chip. So at the start of the experiment the set of all possible physical functions delivered by the chip was in existence and was constrained by:
- The laws of physics
- The properties of the chip
- The functional possibilities associated with each of the 10E+542 configuration states.
I emphasise: they began with a finite set of functional possibilities as a given. Each configuration state of the chip had a functional possibility of some kind. The fact that humans did not have knowledge of all these functional possibilities did not invalidate the fact that these possibilities existed. The problem was not to create the functional possibilities from scratch, or even to find all the possibilities, but rather to search the finite set of possibilities for the function they had specified.
GENETIC ALGORITHM SEARCH
In the genetic algorithm the first generation of 50 “genes” was generated randomly, each 1800 bits long, using a human programmed random number generator. So at this point they actually gave the computer 50 times 1800 bits of information. They set the algorithm running and it found the specified functionality in 2 to 3 weeks.
But now what has changed? At the end all 50 “genes” had the human specified functionality, but they still only had an information content of 1800 bits each (though not necessarily the same configuration). So the algorithm began with 50 times 1800 bits of information given to the computer, and ended with 50 times 1800 bits of information.
Hence there had been no change in the amount of information within the computer at all. Although the configuration bits were constantly changing in the genetic algorithm, there has been no increase in the amount of information present. You come close to agreeing with me here when you say:
quote:
The computer had just taken a very similar 1800 bit piece of memory and mutated it randomly to yield what turned out to be X the final configuration.
But from this point our views diverge, and we disagree. I think fundamentally you are confusing “systematic change of given information following an algorithmic formulation” with “creation of new information”.
CRUDE BLIND SEARCH
As another proof that no new information is created by the genetic algorithm process, consider the possibility of leaving aside the genetic algorithm, and doing instead a crude blind search by computer. This would still be much faster that a human could do it, but still impossibly slow and inefficient. It is also possible in principle to do the search without a computer, since the time factor does not obviate my conclusions.
So we pick any configuration to start with, giving the computer 1800 bits of information picked at random, and we begin a crude blind search, one configuration at a time. We plough laboriously through the configuration states, one at a time, knowing that we will get there in the end.
In this way we would eventually stumble upon a successful configuration. (We and the whole universe may be dead and gone by then, but that’s irrelevant for now. ) When we do find the required functionality, we will do so with 1800 bits of information, no more and no less. Once again, this process has not changed the amount of information in the computer.
CONCLUSION
There is no change in the amount of information in the computer whether using a genetic algorithm or pure blind search. Therefore no new information is created by either of these two processes.
So when I said earlier on, as you quote me:
quote:
a more accurate phrase in relation to the source of the final configuration would be “pre-existing information found through an efficient search pattern”.
you replied:
quote:
But this is inaccurate. Information X was NOT ‘pre-existent’ in the information provided to the system. NEITHER was information X found by a search amongst ’ the pre-existing set of all possible values’ since there was never a complete set of such values in the computer at any time.
Here I must disagree. Configuration information X (if it exists at all) is completely consequent to the specification of the required functionality. I was not inaccurate to use the phrase “pre-existing information”, but it would have been even more accurate if I had said “pre-existing specified functionality”. That functionality was given by the laws of physics in combination with the properties of the chip. As a concept it existed whether we had conscious access to it or not.
quote:
Glenn Oldham said:
I have no objection at all to saying that information X as a solution to the problem of performing the required function was inherent in the parameters and physical constraints of the system. But as I have pointed out before that is NOT in any way an anti-Darwinian view. A Darwinian is happy to agree that the adaptations and organisms that have arisen in nature are the results of the parts of the system at a variety of levels (molecular, cellular, organismal, etc) interacting in accord with laws of physics and chemistry and so on and that replication, variation, and selection operates wherever the conditions for it in the system are right.
Giving the computer information in the form of continuous mathematical functions and the ability to perform arithmetical operations using those functions is a significantly higher-order provision of information that a large list of numbers. This, of course, is another sign of intelligence. The number 140,477,951,552 may never have appeared on your calculator before, but it has had the ability to access it all along through its physical design and its algorithms for arithmetical operations.
To say that the up-front provision of information in this experiment was only “inherent” is to say far too little. There was a full and rich provision of information at the start, without which the experiment would have definitely failed. The only unknown was whether the chip could actually perform the function that was asked of it, and that ignorance is common to many experiments.
I agree with Dembski’s concept of the “front loading of information”, but I would be interested to hear more of why you consider it “confusing and misleading”. Is your disagreement on scientific grounds, philosophical, theological, or elsewhere?
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
Posts: 1097 | From: Scotland | Registered: Feb 2002
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Ley Druid
Ship's chemist
# 3246
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Posted
quote:
Originally posted by Faithful Sheepdog:
I’m certain that Dawkins does not have any teleology of any kind in mind by natural selection. But is that consistent with neo-Darwinism as a whole, or even your own perspective? If there are no excluded forms of non-random selection, then this leaves the door wide open to a teleological form of selection and the brand of Intelligent Design that has much in common with a theistic form of Darwinism.
So, as a discussion starter, is there any form of non-random selection that is not natural selection? And if it’s not, why is it not?
Neil
Let me guess, you would suggest supernatural selection (God's intelligent design).
No there are no excluded forms of non-random selection. You can make up any one you fancy.
Consider the quantum nature of molecular bonds, there is a probability that a bond breaks and two atoms dissociate resulting in a mutation. Is this random event not in fact supernatural selection? God's intelligent design? Another example of non-random selection? What experiment could prove that God had not devised a very intelligent design, resulting in the dissociation of those atoms?
The fact that you have had to question the meaning of "non-random" suggests to me that your thinking has led you to difficulty in distinguishing random from non-random.
Darwinism looks at hereditary changes and seeks to distinguish the random from the non-random, those subject to experimental control, and those that are not. This is hard work. But even after much toil and study, for any mechanism of non-random selection that Darwinists can reproduce experimentally, anyone else can come along and suggest any other mechanism they want, including God's intelligent design.
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Ley Druid
Ship's chemist
# 3246
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Posted
quote:
Originally posted by Faithful Sheepdog:
THE CONCEPT OF “FITNESS”
I will begin by noting that in “The Blind Watchmaker” the word fitness (or even unfitness) does not appear in the index at all. As a concept it would appear to have no use for Richard Dawkins. This would tally with what I have heard of Darwin himself, who apparently never used the phrase “survival of the fittest”. He spoke of “useful variants” or “usefulness”.
OK I've heard this "Darwin never used 'survival of the fittest'" a few times.
I think ignorance of The Origin of Species is simply a brilliant context for a debate on Darwinism.
Let's parse this carefully
quote:
This would tally with
what I have heard
of Darwin himself,
who apparently
never
used the phrase “survival of the fittest”.
Who tells you things about Darwin Neil? Darwinists? Did you hear the works of Darwin recited? Or have you heard about Darwin from people opposed to Darwinism?
Have you read Darwin himself? The Origin? Did you perversely read the first edition, which doesn't include Darwin's attempts to strengthen his position and correct deficiencies?
Apparent to whom Neil?
Never? Not even once? How do you know? Did you even check?
Used the phrase "survival of the fittest". You mean like this
quote:
This preservation of favourable individual differences and variations, and the destruction of those which are injurious, I have called Natural Selection, or the Survival of the Fittest. The Origin of Species
Forget about Darwin's The Origin of Species, death to Darwinism rah rah rah!
[ 24. July 2004, 06:10: Message edited by: Ley Druid ]
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Glenn Oldham
Shipmate
# 47
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Posted
quote:
Originally posted by Faithful Sheepdog:
I agree with Dembski’s concept of the “front loading of information”, but I would be interested to hear more of why you consider it “confusing and misleading”. Is your disagreement on scientific grounds, philosophical, theological, or elsewhere?
It is confusing and misleading because it is presented as an alternative to a neo-Darwinian explanation but is in fact NO DIFFERENT. I notice that about the one thing in my post on the question of information that you do not comment on is that frontloading "is NOT in any way an anti-Darwinian view."
The rest of your post on this subject in deeply wrong about information theory. Your idea that all the possibilites exist at the start of the experiment confuses mathematical existence with actual physical existence. The configuration X had no physical existence until the end of the experiment. It came into physical existence then. The parallel in nature is much starker contrast: on the one hand we have the possibility of anti-biotic resist bacteria and on the other we have a physically real one that kills people. That was not present before and is now.
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Originally posted by Ley Druid:
quote:
Originally posted by Faithful Sheepdog:
THE CONCEPT OF “FITNESS”
I will begin by noting that in “The Blind Watchmaker” the word fitness (or even unfitness) does not appear in the index at all. As a concept it would appear to have no use for Richard Dawkins. This would tally with what I have heard of Darwin himself, who apparently never used the phrase “survival of the fittest”. He spoke of “useful variants” or “usefulness”.
OK I've heard this "Darwin never used 'survival of the fittest'" a few times.
I think ignorance of The Origin of Species is simply a brilliant context for a debate on Darwinism.
Let's parse this carefully
quote:
This would tally with
what I have heard
of Darwin himself,
who apparently
never
used the phrase “survival of the fittest”.
Who tells you things about Darwin Neil? Darwinists? Did you hear the works of Darwin recited? Or have you heard about Darwin from people opposed to Darwinism?
Have you read Darwin himself? The Origin? Did you perversely read the first edition, which doesn't include Darwin's attempts to strengthen his position and correct deficiencies?
I can think of no other purely scientific field where I would be chastised for not reading a mid-19th century textbook in full. I have in fact read excerpts from it, but why should I waste time reading in full a 19th century author who was not even a trained biologist, and in any case had a vastly inferior knowledge compared to today. Darwin knew nothing about inner cell functions and biochemical machines, genes and genetic functions, scanning electron microscopes and the structure of DNA, and every other piece of biological knowledge subsequently won by hard scientific progress.
I get my knowledge of present-day Darwinism from reading Richard Dawkins, studying the web (especially the Talk.Origins web site, which is scientifically competent and strongly pro-Darwinist), and listening to competent Darwinist critiques of the ID fraternity, such as Glenn Oldham's above. I have also read the critiques of Darwinism made by other evolutionary schools of thought.
quote:
Apparent to whom Neil?
Never? Not even once? How do you know? Did you even check?
Used the phrase "survival of the fittest". You mean like this
quote:
This preservation of favourable individual differences and variations, and the destruction of those which are injurious, I have called Natural Selection, or the Survival of the Fittest. The Origin of Species
Forget about Darwin's The Origin of Species, death to Darwinism rah rah rah!
So Darwin did use that phrase afer all , then? Perhaps you might care to tell me how he defined fitness in measurable scientific terms, and how he proposed to measure fitness independently of those who survive?
I hadn't realised that Darwin himself fell into this tautological trap. The Endler syllogism above that I quoted was an explicit attempt to break out of a hopelessly circular tautology, but in so doing ended up in a very different place to Darwinism.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Glenn Oldham
Shipmate
# 47
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Posted
Neil,
I feel compelled to continue to challenge what I see as a continued confusion about this question of information and its implications. To add to the short reply I posted to you this morning I offer this by way of trying to get clear about what is meant and what is going on.
Information Theory
Let me explain my point about information another way.
Harry has asked Fred to get something from Harry’s house. Fred asks ‘how do I get into your house?’
Harry then makes statement A:
A ‘To get in you must push the buttons on the combination lock on the door. There are ten buttons numbered 0 to 9 and you must enter five numbers in the right order. Start with 00000 then try 00001 and so on until it opens. Given the lock and this statement you have all the information you need to open the door.’
And of course he is right that Fred does indeed have enough information to open the door. Like our algorithms he is going to try a trial an error approach, but he will get there sooner or later.
But Harry also makes statement B:
B ‘The first 5 numbers are 2, 9, 1, and 1 in that order.’
Has Harry given Fred new information that he has not already given him?
In information theory the amount of information associated with a statement or a state of affairs or an event is measures in terms of the amount by which it reduces uncertainty, that is by the amount it reduces the range of possible answers to a question, or possible states of a system.
Statement A reduces Fred’s uncertainty by limiting the range of possibilities considerably. In fact the possibilities are reduced to 100,000 possible code entries for opening the door (00000 to 99999).
But the addition of statement B reduces Fred’s uncertainty even more by reducing the possibilities from 100,000 down to 10 (29110 to 29119). Statement B clearly eliminates 99,990 possibilities or, better, reduces the uncertainty to one ten thousandth of what they were. The information content of statement B is therefore log to the base 2 of 10,000 (about 13.3 bits). The information content of statement A is thus 13.3 bits less than A plus B.
NOW, suppose that Fred only had A and went to Harry’s house and after several weeks of punching button found that the code to get in was 29112. Would he have more information than he did at the beginning when he just had A? Of course he would because his uncertainty would have been reduced from the 100,000 possibilities down to 1 a drop by a factor of 100,000 (or about 16.6 bits). He would have more information than he had at the start.
So it is with the chip experiment. The uncertainty is reduced. At the end we are no longer wholly uncertain as to what configurations will produce the desired function, we know that at least one will.
Now Neil and Dembski will doubtless say that the analogy fails since the lock is not a computer program. But suppose it is. Suppose that it is a little black box programmed something like ‘if input = 29112 open door, else print ‘WRONG AGAIN!’ ‘ Well there you are, Dembski would say there is the number itself given to Fred as part of the information contained in the lock! He does have the information at the start so no new information is gained at the end after all.
But this is incorrect. It is not true to say that 29112 is amongst the information that Fred is provided with in terms of information theory. This is because at the start of the process 29112 is NOT provided to Fred in a form that reduces his uncertainty. as a result IT DOES NOT COUNT AS INFORMATION TO HIM.
It is quite clear that the system as a whole has the 29112 in it and it is quite clear that its presence will play a part in the correct result being reached. But it is not information in information theory terms that Fred has at the start.
In natural selection the organism acquires information that it did not previously possess. The information is, of course, acquired form the system and is, therefore inherent (‘inherent’ is NOT meant as a weak word at all!) in the system in some way from the start. But Darwinian theory does not deny that the system is the source of the new information in the organism. If this is what Dembski means by front-loading it does not contradict the neo-Darwinian theory of natural selection.
Glenn
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Glenn Oldham
Shipmate
# 47
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Posted
I said "statement B:
B ‘The first 5 numbers are 2, 9, 1, and 1"
I meant the first 4 numbers not five of course - sorry. The 2 minute edit only works if you have broad band!
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Originally posted by Glenn Oldham:
Neil,
I feel compelled to continue to challenge what I see as a continued confusion about this question of information and its implications. To add to the short reply I posted to you this morning I offer this by way of trying to get clear about what is meant and what is going on.
<snip>
So it is with the chip experiment. The uncertainty is reduced. At the end we are no longer wholly uncertain as to what configurations will produce the desired function, we know that at least one will.
<snip>
But this is incorrect. It is not true to say that 29112 is amongst the information that Fred is provided with in terms of information theory. This is because at the start of the process 29112 is NOT provided to Fred in a form that reduces his uncertainty. as a result IT DOES NOT COUNT AS INFORMATION TO HIM.
It is quite clear that the system as a whole has the 29112 in it and it is quite clear that its presence will play a part in the correct result being reached. But it is not information in information theory terms that Fred has at the start.
<snip>
Glenn, I much appreciated your post – a thought experiment on “information” was just what was needed – I have certainly had to do a lot of head scratching in response.
Information can be difficult and slippery concept to define accurately, so it is useful to spend some time on this. Dembski certainly agrees with you that “information typically measures the reduction in uncertainty that results from knowledge that an event has occurred”.
I think that part of the response to your thought experiment must be that what counts as information for a human Fred is very different to what would count as information for a cybernetic android Fred (i.e. a computer). Human psychology intervenes at this point and adds its own unique touch. We have self-awareness and can make conscious choices, but computers can do neither.
In both scenarios there are several important differences between the electronics experiment and your thought experiment. Harry knows that the specified functionality can be achieved (his door will open), and he also knows the right configuration parameters (the correct lock code). Furthermore, both Harry and Fred are human.
Fred always gets to know that Harry’s door will open, and that the lock requires a five-digit code. This statement contains significant information in its own right, since it narrows the possibilities down considerably. The problem concerns Harry’s door, and not any other door. The relevant code is a 5-figure number, and not any other number.
The problem thus becomes a deterministic search-and-find mission for a specific door with only one correct lock code. Thus Scenario A is very far from being information free, even for a human. For a computer the problem is completely specified at this point, and it will get to open the door.
For a human, we must add the psychological dimension, since of course Fred doesn’t yet know the exact code. He rightly deduces that Harry is not expecting him to spend days pushing buttons. Instead, he deduces that Harry is being passive-aggressive and winding him up. Nevertheless the information Harry has passed over is true, and is theoretically adequate to open the door.
Unhappily for Harry, Fred is an awkward so-and-so with something akin to obsessive-compulsive disorder ![[Frown]](frown.gif) , and so he spends umpteen weeks camped outside Harry’s door trying up to 100,000 options in order to get it to open. Eventually he succeeds, since he has been given adequate information to open the door eventually by performing a search algorithm.
In scenario B, Harry has written the code down for Fred, but one number has accidentally become illegible. Fred’s deterministic search and find mission is therefore much easier in this case. Fred rapidly tries all ten possible options for the missing digit, succeeding within a few minutes to open the door.
The easiest case of all is when Harry properly gives Fred the full code. Fred just types the 5 correct numbers and he is in.
We notice that in all cases the physical result is the same: Fred gets to open Harry’s door. The only difference is the timescale involved, and whether they are still friends at the end of it. In scenario A Fred’s doctor may also wish to see him.
METHODOLOGY OF ANALYSIS
Given the psychological games that Harry is playing, we have to separate the probability of Fred ever trying to open the door, maybe after a long period of key tapping, from the probability associated with his having the correct lock code.
I am going to look at the informational content of scenarios A and B using the equations on pages 3 and 4 of this paper by Dembski. These equations involve the informational content of correlated events. Having the correct lock code and trying to open the door are the correlated events, but of course Fred may still try to open the door without first having the full code.
Thus we have prior event X – Fred ever trying to open the door - and we have subsequent event Y, Fred having the correct lock code given prior event X (Fred trying to open the door).
Restructuring these probabilities in information terms as per Dembski (page 4), we get the information that Harry needs to pass over for Fred to open the door as: I(X&Y)=I(X) + I(Y/X).
That is, the information associated with Fred [both opening the door X and also having the correct lock code Y] equals the sum of [the information associated with Fred trying to open the door X] and [the information associated with the correct lock code, given that Fred tries to open the door Y/X].
SCENARIO A
Since there are 100,000 possibilities associated with the lock code, the probability of Y is 10E-5. Therefore I(Y/X) would equal 16.6 bits if Harry had handed over the correct code, but since Fred does not yet have this information, I(Y/X) is zero for now.
Now we know that the door will physically open with the correct code, but in scenario A Harry has no true intention that Fred should ever open the door. He is playing unpleasant games, and calling Fred’s bluff.
Thus the probability of X (Fred trying to open the door) in scenario A is very low, but it is not zero. Fred does theoretically have enough information to do this, and may yet call Harry’s bluff. So the probability of X is certainly greater than 0, but of course it is far less than 1, a certainty.
So what is the information associated with X? For the sake of argument let’s grab a completely arbitrary figure out of thin air and assume that in Scenario A the probability of Fred ever trying to open the door is 10E-5, i.e. I(X) = 16.6 bits. (We could make this figure less arbitrary by reference to data for various psychiatric conditions – not many healthy people would take up Harry’s bluff.)
So at the start, the information passed over to Fred is I(X + Y) = I(X) + I(Y/X) = 16.6 + 0 = 16.6 bits – all in the form of the low but finite probability associated with the just-adequate information to do the job. Note however that it is a different 16.6 bits to the information he needs to open the door directly.
Previously Fred had no possibility of a solution, but the just-adequate information has now brought one within his grasp. So when Fred gets down to work, Harry is horrified and thinks Fred is going mad . Of course, if Fred is a not a mad human being, but a cybernetic android, he is as good as through Harry’s door already.
After his long tapping session, Fred finally discovers the correct lock code. The door opening has now become a certainty, and at the same time Harry’s bluff has been well and truly called. Fred now has the correct 16.6 bits of information. The door opens and he is in.
SCENARIO B
In scenario B Harry was definite that he wanted Fred to open the door, so the prior probability P(X) of Fred trying to open the door is a certainty, and therefore I(X) is 0. Four correct digits have a probability of 10E-4, so the information content I(Y/X) is 13.3 bits.
So Fred starts with 0 + 13.3 = 13.3 bits. Fred quickly finds by a blind search the 1 missing digit of value 3.3 bits. He now has the full 16.6 bits of information and he is in.
CHECK ANALYSIS
Suppose Harry clearly wants Fred to open the door and gives him the full lock code straightaway. Hence the probability of Fred trying to open the door is 1, so I(X)= 0. Fred has the correct 5 digit code of probability 10E-5, so I(Y/X) = 16.6 bits. Therefore I(X+Y) = 0 + 16.6 = 16.6 bits. Fred gets in quickly.
CONCLUSION
In scenario A, Harry provides the just-adequate information for Fred to eventually open the door. However, scenario A causes Fred a great deal of trouble, and destroys the friendship between Harry and Fred. Fred also ends up in a psychiatric hospital.
In scenario B Harry provides Fred with additional information that saves Fred a huge amount of time, and so he opens the door much more quickly. This preserves both the friendship and Fred’s sanity.
Note that in both cases Fred manages to find the correct lock code and opens Harry’s door. The human consequences vary markedly, but for a computer there would be no difference.
You may wish to comment on my informational analysis. I think it demonstrates that your thought experiment is more subtle and complex than you think, but I won’t be upset if you say it is fallacious . I will return to the electronics experiment in due course.
Neil
[minor typo]
[ 26. July 2004, 11:32: Message edited by: Faithful Sheepdog ]
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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Faithful Sheepdog
Shipmate
# 2305
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Posted
Whoops, just to clarify, in the last paragraph of my post I was using the the word "fallacious" as being possibly applicable to my informational analysis, and not to Glenn Oldham's thought experiment.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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ken
Ship's Roundhead
# 2460
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Posted
Well, Darwin's book isn't a textbook, it was a combination of a popularisation and a persuasion. And one reason to read it is that he's quite a good writer. It's fun.
And he wasn't a "trained biologist" but that doesn't stop him being a brilliant one.
And whats wrong with the business about "tautology"? That just goes to show its true.
Moaning about "circular reasoning" here is just another bit of physics-envy, an attempt to constrain biology into the straitjacket of 20th-century "philosophy of science" based on the idea that mathematical physics is the only true science. Natural Philosophy vs. Natural History again.
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Ken
L’amor che move il sole e l’altre stelle.
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Ley Druid
Ship's chemist
# 3246
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Posted
quote:
Originally posted by Faithful Sheepdog concerning The Origin of Species, by Charles Darwin:
I have in fact read excerpts from it, but why should I waste time reading in full a 19th century author who was not even a trained biologist, and in any case had a vastly inferior knowledge compared to today.
I have read many things written by Evangelicals on the ship of fools, but none cements the stereotypes quite as well as this summary dismissal as "a waste of time" of an eminently readable yet seminal classic of modern science. Evangelical scholarship, excelling in the virtues of time management; perhaps not thorough, but who has the time?
[quote]I hadn't realised that Darwin himself fell into this tautological trap. The Endler syllogism above that I quoted was an explicit attempt to break out of a hopelessly circular tautology, but in so doing ended up in a very different place to Darwinism.
I assume the tautology you make reference to is the one you cited of Nelseon quoting Endler
quote:
To say that a new adaptation necessarily arose through natural selection is an incomplete description, a tautology, and a misrepresentation of natural selection, adaptation and evolution.
I provided you a link to Darwin's The origin of species to prove just how lazy your "scholarship" is. If you had followed the link and wasted your precious time reading the very next sentence, you would have seen that Darwin (Darwinists and neo-Darwinists) do not suggest the tautology that all adaptation necessarily arose through natural selection.
quote:
Variations neither useful nor injurious would not be affected by natural selection, and would be left either a fluctuating element, as perhaps we see in certain polymorphic species, or would ultimately become fixed, owing to the nature of the organism and the nature of the conditions.
Let's do a thought experiment.
Suppose you had a bacteria that had a gene for antibiotic resistance. However one base pair had been changed so the protein needed for confering the antiobiotic resistance was ineffective.
What would happen if you allow the bacteria to grow for years in a medium that had a concentration of antibiotic that kills 99% of bacteria that don't have effective antibiotic proteins?
Despite your suggestion that the theory of the survival of the fittest is not predictive, I would use the theory to make predictions.
What would you predict?
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Ley Druid said:
I have read many things written by Evangelicals on the ship of fools, but none cements the stereotypes quite as well as this summary dismissal as "a waste of time" of an eminently readable yet seminal classic of modern science. Evangelical scholarship, excelling in the virtues of time management; perhaps not thorough, but who has the time?
I am still chuckling over your description of Darwin’s Origin of Species as a “seminal classic of modern science”. Now if you’d said “an important classic of historical scientific literature that was unfavourably received by Darwin’s immediate scientific colleagues, but subsequently became the fountainhead of some profoundly influential thought, both within and without the world of science”, then we would have been in agreement.
You have a strange concept of modern, but then it is a slippery and vague word at the best of times. Richard Dawkins is arguably far more deserving of the description “modern science”, and I certainly find him to be a very good writer. His descriptions of wildlife behaviour are a joy to read, but his “just-so” stories of evolutionary history should be filed under entertainment, not science.
quote:
Ley Druid said:
Let's do a thought experiment.
Suppose you had a bacteria that had a gene for antibiotic resistance. However one base pair had been changed so the protein needed for confering the antibiotic resistance was ineffective.
What would happen if you allow the bacteria to grow for years in a medium that had a concentration of antibiotic that kills 99% of bacteria that don't have effective antibiotic proteins?
Despite your suggestion that the theory of the survival of the fittest is not predictive, I would use the theory to make predictions.
What would you predict?
You also have a strange concept of prediction. The phenomenon of antibiotic resistance is long-established and well-understood. So I have no qualms in saying that the bacteria will reacquire the resistance that they lost due to the genetic engineering.
The scientific explanation of the resistance involves a change to the shape of the site where the antibiotic would normally bind to the bacteria. Some bacteria in the wild are already shaped in a way that will not accept the antibiotic, thus giving them a natural form of protection. Hence they are antibiotic resistant already.
Because some bacteria have always had the relevant genetic information, there is some evidence of penicillin-resistant bacteria in ancient Egypt, for example, possibly due to penicillin mould growth on wheat. The 1% who initially survive in your thought experiment are also evidence of this.
The growth of antibiotic resistance is, as Endler put it, “simply a directional shift in the trait frequencies of a species”. There is no need for the creation of new genetic information, nor any requirement for fortuitous random mutations followed by natural selection.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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ken
Ship's Roundhead
# 2460
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Posted
Sorry Neil, bacteria really do work the way LD said they do.
You don't need the gene present, mutations can bring it along.
I've got downloaded copies of nearly all the currently known bacterial genomes on my other computer right now & I'm writing programs to try to predict expression levels by codon usage... so bacterial genetics is near the front of my brain at the moment. Been reading a lot of papers about the things as well.
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Ken
L’amor che move il sole e l’altre stelle.
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Ley Druid
Ship's chemist
# 3246
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Posted
quote:
Originally posted by Faithful Sheepdog:
So I have no qualms in saying that the bacteria will reacquire the resistance that they lost due to the genetic engineering.
...
There is no need for the creation of new genetic information, nor any requirement for fortuitous random mutations followed by natural selection.
I'm sure you have no qualms saying the bacteria will reacquire the resistance, because that allows you to say there is no need for the creation of new genetic information.
However I never said the bacteria ever had resistance. If they never had resistance, logically they cannot reacquire it. Such a prediction would be wrong.
It would also be wrong to predict that the 1% of bacteria that survived was evidence that "some bacteria have always had the relevant genetic information". The effect of the antibiotic follows a dose response. At sufficiently low concentration very few bacteria will be killed and the population would not be noticeably effected. At sufficiently high concentrations essentially all the bacteria are killed (remember they don't have resistance). At a somewhat lower concentration only 99% are killed. The bacteria do not have, nor ever had resistance.
I also never specified how the changed base pair rendered the resistance protein ineffective. Therefore it would be wrong to predict it "involves a change in the shape of the site where the antibiotic would normally bind to the bacteria." It might not involve this at all.
You have made three incorrect predictions.
Let me help you to avoid further errors by being more explicit.
The bacteria in question do not have antibiotic resistance. They have never had antibiotic resistance. They were grown from one bacterium which never had resistance. However, they do have a gene which is identical to an antibiotic resistance gene, except for one base pair. The base pair that the bacteria have causes a stop in the production of protein, resulting in a very short protein incapable of conferring antibiotic resistance. The bacteria are allowed to grow for many years in a medium which has a concentration which consistently kills only 99% of the bacteria.
This would be a trivial experiment with today's technology.
What would you predict might be the results?
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Ley Druid
Ship's chemist
# 3246
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Posted
Sorry. That should read:
The bacteria are allowed to grow for many years in a medium which has a concentration of antibiotic which consistently kills only 99% of the bacteria that do not have resistance (that is, don't produce an effective protein that prevents the killing action of the antibiotic). If the base pair in question were changed, the gene could produce a protein which would confer resistance to the antibiotic. That is, the same concentration of antibiotic would kill much less than 99% of bacteria with the gene that produces this protein.
Any predictions?
[ 26. July 2004, 21:27: Message edited by: Ley Druid ]
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Originally posted by Ley Druid:
You have made three incorrect predictions.
Let me help you to avoid further errors by being more explicit.
My predictions are only as good as the information you give me. In your first post the bacteria originally had antibiotic resistance until the relevant base pair was changed. Since this is an experiment after all, I had assumed that the base pair change was by genetic engineering.
If you want to start claiming errors on my part, then you should have been a lot clearer in setting up your thought experiment - I see the goalposts moving wildly here.
I'm currently reading this paper to get some more scientific background to your query. I''ll respond in due course.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
Posts: 1097 | From: Scotland | Registered: Feb 2002
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Ley Druid
Ship's chemist
# 3246
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Posted
quote:
Originally posted by Faithful Sheepdog:
quote:
Originally posted by Ley Druid:
You have made three incorrect predictions.
Let me help you to avoid further errors by being more explicit.
My predictions are only as good as the information you give me. In your first post the bacteria originally had antibiotic resistance until the relevant base pair was changed. Since this is an experiment after all, I had assumed that the base pair change was by genetic engineering.
If you want to start claiming errors on my part, then you should have been a lot clearer in setting up your thought experiment - I see the goalposts moving wildly here.
I try to be precise with my posts. I said
quote:
Suppose you had a bacteria that had a gene for antibiotic resistance. However one base pair had been changed so the protein needed for conferring the antiobiotic resistance was ineffective.
I never said the bacteria ever had antibiotic resistance. I said it had the gene, but with a base pair changed, so the protein was ineffective at conferring antibiotic resistance.
It would be wrong to predict the bacteria would reacquire resistance because it would be wrong to suggest from the information that I provided that the bacteria necessarily previously had resistance.
I anticipated you inability to see why this would be wrong. I didn't move the goalpost. I merely stated something explicitly, which was only a possibility before. Namely, that the bacteria never had resistance. In the present experiment, as in the first, it is wrong for you to suggest that the bacteria will reacquire resistance, previously because you didn't know they necessarily had it, now because you know they didn't.
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Glenn Oldham
Shipmate
# 47
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Posted
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Originally posted by ken:
Darwin ... wasn't a "trained biologist" but that doesn't stop him being a brilliant one.
Indeed so. I think 'genius' is not an unwarranted term for Darwin. The more I read him, and the more I read about him, the more impressed I am with his abilities. To master such large areas of information, to imagine and conduct such relevant experiments, to make observations, to collect information, and to have such a good grasp of how theorising in biology works.
Neil,
Thanks for your last on the information question. I will reply. I owe you one on the subjects of Fitness, Natural Selection and Teleology as well.
Glenn
[ 27. July 2004, 08:03: Message edited by: Glenn Oldham ]
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This entire doctrine is worthless except as a subject of dispute. (G. C. Lichtenberg 1742-1799 Aphorism 60 in notebook J of The Waste Books)
Posts: 910 | From: London, England | Registered: May 2001
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Faithful Sheepdog
Shipmate
# 2305
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Posted
Before I reply further to Ley Druid, here is some scientific background on antibiotic-resistant bacteria taken from this paper published in the scientific journal “Nature”.
Antibiotics destroy bacteria by getting inside the cell and interfering with vital cell functions (especially protein manufacture). If the antibiotics are present in sufficient concentration this subsequently causes death to the bacteria.
With regard to the phenomenon of antibiotic resistance, the paper makes the following statement:
quote:
Development of resistance is not a matter of if but only a matter of when. Given the large number of bacteria in an infection cycle, the rapid generation time, and the intrinsic rate of mutation of about 1 in 10E7, then a pool of 10E10 bacteria would have mutations on average in a thousand loci.
Thus we might almost say that the development of antibiotic resistance is deterministic, that is, given certain conditions, it will certainly develop.
The paper identifies three basic mechanisms for resistance, as follows:
1. PUMP OUT THE ANTIBIOTIC.
The concentration of the antibiotic inside the cell must reach a critical level to be effective and kill the bacterium. However, according to the paper, all bacteria have pumps that can remove unwanted materials from the cell interior. If these pumps are efficient enough, then the concentration of antibiotic never reaches a critical level. The antibiotic is simply removed faster than it can enter.
As the paper puts it, with my emphasis:
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As schematized in Fig. 3a, the drug is pumped out faster than it can diffuse in, so intrabacterial concentrations are kept low and ineffectual; bacterial protein synthesis proceeds at largely unimpeded rates. The pumps are variants of membrane pumps possessed by all bacteria to move lipophilic or amphipathic molecules in and out of the cells. Some are used by antibiotic producers to pump antibiotics out of the cells as fast as they are made and so constitute an immunity or protective mechanism for the bacteria to prevent being killed by their own chemical weapons.
This certainly sounds like a mechanism where the genes are pre-existent. Of course not all bacteria are equal, and some have better pumps than others. Hence the development of the resistant strain with heavy-duty pumps.
2. DESTROY THE ANTIBIOTIC WARHEAD
Certain bacteria produce a deactivating enzyme which attacks the antibiotic in the space between the outer and inner membranes of the cell wall. In effect, the enzymes are border guards, destroying the antibiotic as it tries to enter.
There are variations on this mechanism, depending on which bacteria and which enzyme are involved. The paper includes the following interesting comment:
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The X-ray structure of an antibiotic phosphotransferase indicates an evolutionary relationship to a protein kinase, defining a route by which bacteria may have recruited an enzyme for the resistance brigade.
Phosphotransferase is one of the enzymes now acting as a border guard, but evolved originally from the protein kinase. So again, it sounds like the raw material was available to be recruited and retrained.
3.REPROGRAMME THE TARGET STRUCTURE
This is the mechanism to which I alluded above, albeit somewhat inaccurately. The shape modification occurs to crucial biochemicals within the bacterial cell, rather than to the bacterium itself. As a result the target areas are reprogrammed or camouflaged, and now have a “low affinity for antibiotic recognition”.
Note also the following comment:
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This modification is carried out by a methyl transferase enzyme Erm that does not impair protein biosynthesis but does lower the affinity of all the members of the erythromycin class of drugs for the RNA, as well as for the pristinamycin class described below.
So in this case the antibiotic resistance comes with a price of a reduced affinity for RNA. That may be a problem in some circumstances.
Note also the comment:
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The Erm mechanism is the main resistance route in drug-resistant clinical isolates of S. aureus and is present in erythromycin-producing organisms as a self-immunity mechanism.
So this resistance mechanism already exists in the wild. Organisms that produce erythromycin have a natural immunity to this antibiotic.
The three mechanisms outlined above are undoubtedly simplifications. There will always be more complex variations applicable to specific bacteria and specific antibiotics. But these three mechanisms will do me for now.
So, before I get back to Ley Druid’s thought experiment, does anyone wish to comment on the basic science of antibiotic resistance? Have I missed anything?
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
Posts: 1097 | From: Scotland | Registered: Feb 2002
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Ley Druid
Ship's chemist
# 3246
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Posted
quote:
Originally posted by Faithful Sheepdog:
Before I reply further to Ley Druid, here is some scientific background on antibiotic-resistant bacteria taken from this paper published in the scientific journal “Nature”.
Antibiotics destroy bacteria by getting inside the cell and interfering with vital cell functions (especially protein manufacture). If the antibiotics are present in sufficient concentration this subsequently causes death to the bacteria.
With regard to the phenomenon of antibiotic resistance, the paper makes the following statement:
quote:
Development of resistance is not a matter of if but only a matter of when. Given the large number of bacteria in an infection cycle, the rapid generation time, and the intrinsic rate of mutation of about 1 in 10E7, then a pool of 10E10 bacteria would have mutations on average in a thousand loci.
Thus we might almost say that the development of antibiotic resistance is deterministic, that is, given certain conditions, it will certainly develop.
Dear Neil,
Thanks for the paper, it is a nice review.
Development of antibiotic resistance is not determinstic in the sense that "given certain conditions, it will certainly develop". The article explicitly says it is a matter of "when", that is, given enough time, the probability becomes very great. Just like flipping a coin, if you flip long enough you are "practically guaranteed" to see heads. However, if you only flip a few times, even with all the conditions required to see heads, you might only see tails. If the conditions are present immediately, why does it take time for many generations of bacteria to pass before the development of resistance to a new antibiotic? Why is it a matter of "when" as the article says?
I wonder if you noticed that the article assumes the validity of "natural selection", also called "survival of the fittest"? As you are want to do, your selective quotation avoided a nice description of non-random selection
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...If one of those mutations confers resistance to an applied antibiotic, whereas all sensitive bacteria are killed, the resistant one will grow, fill the space vacated by its dead neighbours and become the domninant variant in the population.
The article also talks about "selective pressures" and how bacteria are "selected". I am very curious as to what you think these ideas might mean.
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HenryT
Canadian Anglican
# 3722
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Posted
quote:
Originally posted by Faithful Sheepdog:
...So, before I get back to Ley Druid’s thought experiment, does anyone wish to comment on the basic science of antibiotic resistance? Have I missed anything?
Neil
One fine point that has real world consequences - antibiotic resistance disappears again (through the same mechanisms) if the bacteria cease to encounter the antibiotic. All in accord with Darwin.
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"Perhaps an invincible attachment to the dearest rights of man may, in these refined, enlightened days, be deemed old-fashioned" P. Henry, 1788
Posts: 7231 | From: Ottawa, Ontario, Canada | Registered: Dec 2002
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Faithful Sheepdog
Shipmate
# 2305
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Posted
quote:
Ley Druid said:
The article also talks about "selective pressures" and how bacteria are "selected". I am very curious as to what you think these ideas might mean.
Since you may possibly have missed it, here is the Endler syllogism that I quoted earlier on the thread. This is his understanding of what natural selection means:
quote:
If, within a species or population, the individuals:
a) vary in some attribute or trait q (physiological, morphological, or behavioural) – the condition of variation;
b) leave different numbers of offspring in consistent relationship to the presence or absence of trait q – the condition of selection differences;
c) transmit the trait q faithfully between parents and offspring – the condition of heredity;
d) then the frequency of trait q will differ predictably between the population of all parents and the population of all offspring.
Now as far an antibiotic-resistant bacteria are concerned, we know that the earlier generation did not have the resistance (trait q). However, we can verify that, in the few resistant parents, mechanisms 1 or 2 or 3 are either already mobilised by the existing genetic endowment or freshly provided by a fortuitous point mutation. So we satisfy the condition of variation.
We are able to count the relative number of offspring left by bacteria, both with and without the trait q. Those with trait q consistently leave more offspring, by a large margin. So we satisfy the condition of selection differences.
We know that bacteria reproduce asexually and transmit these differences faithfully to their offspring. Trait q is duly transmitted to the offspring, so we satisfy the condition of heredity.
And since we can demonstrate that most or all of the offspring subsequently possess trait q (the antibiotic resistance), then, according to Endler, it is at this point that we can say that this is due to natural selection.
For another example of natural selection, consider red deer. In medieval Scotland they were forest animals, but with the destruction of so much native forest, the deer were forced instead to become creatures of open moorland and mountains. Since they now live in more demanding country, and no longer have the protection of large forests against the climate, the present generation have become physically bigger and more muscled than their medieval forebears. This too is an example of natural selection.
So back to your thought experiment for a second attempt. I will assume that the bacteria have never had any resistance, but like all bacteria, they do have the basic cell pump (mechanism 1). They are also one base pair away from another mechanism, which could be 2 (enzyme border guards) or 3 (reshaped molecules), assuming that point mutations are needed for these.
Placed in the hostile antibiotic environment, our first problem is to make sure that we don’t kill all the bacteria, but maintain 1% alive. If we were more liberal with the quantities of antibiotic, we might succeed in killing them all, bringing the experiment to a premature halt.
Hence the control of the antibiotic quantity is an important factor in the experiment. This controlled dosage is mimicking the use of antibiotics in medicine where the dosage is inadequate. To my mind it is questionable whether such a controlled environment should be called “natural”, but that’s probably quibbling.
Given that 1% of the bacteria do survive by some means, the acquisition of antibiotic resistance is then “not a matter of if, but when”. I predict the growth of resistance through a process of selective death.
In the first stages we may generate an antibiotic resistant strain with the enhanced pump mechanism (1). This is not dissimilar to the selective breeding of farm and domestic animals for size or whatever. All our bacteria originally had pumps, and now they have been bred to have butch pumps. However, there is a limit to how effective the pump mechanism can become. We can still kill them all if we are not careful.
In later stages, since our bacteria is one base pair away from some other helpful mechanism, we may get some fortuitous point mutations. This leads to the growth of a strain with resistance mechanisms 2 and/or 3 as backup to mechanism 1. At this point our bacteria have acquired very substantial resistance to the antibiotic.
Any further control of the bacteria would require a different form of antibiotic. The Nature paper outlined some of the techniques being used in pharmaceutical engineering for bacteria that have become resistant to present-day antibiotics. All this is in the realm of demonstrable science, ably documented in the Nature article.
Bacteria are a highly successful species, having remained as bacteria for 3.5 billion years or thereabouts. And bacterial resistance to antibiotics is an important scientific and medical questions. However, to suggest that the adaptive mechanism behind this phenomenon (natural selection) throws light on all evolutionary mechanisms is to claim far too much, I think.
quote:
Henry Troup said:
One fine point that has real world consequences - antibiotic resistance disappears again (through the same mechanisms) if the bacteria cease to encounter the antibiotic. All in accord with Darwin.
I am particularly intrigued by this comment. So, if you remove the hostile antibiotic environment, the bacteria lose the acquired resistance, and that is in accordance with Darwinian theory? How are the bacteria going to evolve complex adaptations if they cannot build on previous selective choices? Does this not undermine Darwinian theory completely?
Henry Troup’s comment suggests to me that the adaptive mechanism responsible for antibiotic resistance is distinctly limited in the changes it can bring about. The bacteria can cycle about some form of mean, but can do no more than that. My understanding of the fruit fly evidence suggests the same.
Neil
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"Random mutation/natural selection works great in folks’ imaginations, but it’s a bust in the real world." ~ Michael J. Behe
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