Fitness surfaces and searches: Dembski, Ewert, and Marks’s search for design

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This post is by Joe Felsenstein and Tom English

Back in October, one of us (JF) commented at Panda’s Thumb on William Dembski’s seminar presentation at the University of Chicago, Conservation of Information in Evolutionary Search. In his reply at the Discovery Institute’s Evolution News and Views blog, Dembski pointed out that he had referred to three of his own papers, and that Joe had mentioned only two. He generously characterized Joe’s post as an “argument by misdirection”, the sort of thing magicians do when they are deliberately trying to fool you. (Thanks, how kind).

Dembski is right that Joe did not cite his most recent paper, and that he should have. The paper, “A General Theory of Information Cost Incurred by Successful Search”, by Dembski, Winston Ewert, and Robert J. Marks II (henceforth DEM), defines search differently than do the other papers. However, it does not jibe with the “Seven Components of Search” slide of the presentation (details here). One of us (TE) asked Dembski for technical clarification. He responded only that he simplified for the talk, and stands by the approach of DEM.

Whatever our skills at prestidigitation, we will not try to untangle the differences between the talk and the DEM paper. Rather than guess how Dembski simplified, we will regard the DEM paper as his authoritative source. Studying that paper, we found that:

  1. They address “search” in a space of points. To make this less abstract, and to have an example for discussing evolution, we assume a space of possible genotypes. For example, we may have a stretch of 1000 bases of DNA in a haploid organism, so that the points in the space are all 41000 possible sequences.

  2. A “search” generates a sequence of genotypes, and then chooses one of them as the final result. The process is random to some degree, so each genotype has a probability of being the outcome. DEM ultimately describe the search in terms of its results, as a probability distribution on the space of genotypes.

  3. A set of genotypes is designated the “target”. A “search” is said to succeed when its outcome is in the target. Because the outcome is random, the search has some probability of success.

  4. DEM assume that there is a baseline “search” that does not favor any particular “target”. For our space of genotypes, the baseline search generates all outcomes with equal probability. DEM in fact note that on average over all possible searches, the probability of success is the same as if we simply drew randomly (uniformly) from the space of genotypes.

  5. They calculate the “active information” of a “search” by taking the ratio of its probability of success to that of the baseline search, and then taking the logarithm of the ratio. The logarithm is not essential to their argument.

  6. Contrary to what Joe said in his previous post, DEM do not explicitly consider all possible fitness surfaces. He was certainly wrong about that. But as we will show, the situation is even worse than he thought. There are “searches” that go downhill on the fitness surface, ones that go sideways, and ones that pay no attention at all to fitnesses.

  7. If we make a simplified model of a “greedy” uphill-climbing algorithm that looks at the neighboring genotypes in the space, and which prefers to move to a nearby genotype if that genotype has higher fitness than the current one, its search will do a lot better than the baseline search, and thus a lot better than the average over all possible searches. Such processes will be in an extremely small fraction of all of DEM’s possible searches, the small fraction that does a lot better than picking a genotype at random.

  8. So just by having genotypes that have different fitnesses, evolutionary processes will do considerably better than random choice, and will be considered by DEM to use substantial values of Active Information. That is simply a result of having fitnesses, and does not require that a Designer choose the fitness surface. This shows that even a search which is evolution on a white-noise fitness surface is very special by DEM’s standards.

  9. Searches that are like real evolutionary processes do have fitness surfaces. Furthermore, these fitness surfaces are smoother than white-noise surfaces “because physics”. That too increases the probability of success, and by a large amount.

  10. Arguing whether a Designer has acted by setting up the laws of physics themselves is an argument one should have with cosmologists, not with biologists. Evolutionary biologists are concerned with how an evolving system will behave in our present universe, with the laws of physics that we have now. These predispose to fitness surfaces substantially smoother than white-noise surfaces.

  11. Although moving uphill on a fitness surface is helpful to the organism, evolution is not actually a search for a particular small set of target genotypes; it is not only successful when it finds the absolutely most-fit genotypes in the space. We almost certainly do not reach optimal genotypes or phenotypes, and that’s OK. Evolution may not have made us optimal, but it has at least made us fit enough to survive and flourish, and smart enough to be capable of evaluating DEM’s arguments, and seeing that they do not make a case that evolution is a search actively chosen by a Designer.

This is the essence of our argument. It is a lot to consider, so let’s explain this in more detail below:

As usual I will pa-troll the comments, and send off-topic stuff by our usual trolls and replies to their off-topic stuff to the Bathroom Wall

The target

DEM have a “target” for which the search is searching. Except that they don’t actually require that the “search” actually search for something that makes sense. The target can be any set of points. If each point is a genotype and each of them has a fitness, the target can be genotypes with unusually high fitnesses, with unusually low fitnesses, mediocre fitnesses, or any mixture of them. They do not have to be points that are “specified” by fitness or by any other criterion. DEM do not require that the “search” even consider the fitnesses. They calculate the fraction of all M points that are in the target. If |T| is the size of the target, for this fraction If we divide that by the number of points in the space, N, we get p = |T|/|N|. This of course is also the probability that a random point drawn uniformly from the space hits the target.

Searches as distributions on the space of points

DEM consider the probability distribution of all outcomes of a search. Different instances of the search can find different results, either because they choose different starting points, or because of random processes later during the search. They assume very little about the machinery of the search – they simply identify the search with the distribution of results that it gets. Suppose that two searches lead to the same distribution of outcomes, say a probability 0.6 of coming up with point x1, probability 0.4 of being coming up with x12, and probability 0 of everything else. They consider these two processes to be the same identical search. They don’t consider what intermediate steps the searches go through. Correspondingly, two searches that lead to different probability distributions of outcomes are considered to be different searches. All distributions that you can make can apparently be found by one or another of DEM’s search processes. From this point on they talk about the set of possible distributions, which to them represent the set of possible searches.

Note that this means that they are including “searches” that might either fail to be influenced by the fitnesses of the genotypes, and even ones that deliberately move away from highly fit genotypes, and seek out worse ones. Anything that gets results is a “search”, no matter how badly it performs.

Are “searches” search algorithms?

Mathematicians and computer scientists working on optimization are accustomed to investigating the properties of algorithms that try to maximize a function. Once an algorithm is given, its behavior on different functions can be studied mathematically or numerically. DEM do not make this separation between the algorithm and the function. Their definition of a “search” includes both the algorithm and the function it encounters. As an evolutionary algorithm may have different results on different fitness surfaces, in their argument the same evolutionary model can be two different “searches” if it encounters two different fitness surfaces. As we have noted, even “searches” that do not try to maximize the fitness are included in their space.

DEM’s “Search For a Search”

A probability distribution on a set of N points simply assigns probabilities to each of them. These probabilities can be positive or zero, but not negative, and they must add up to 1. So DEM consider the N probabilities a1, a2, …, aN. The conditions that they be nonnegative and add up to 1 forces them to lie in a region of N-dimensional space called a simplex. For example, if N is 3, the numbers must lie in an equilateral triangle in a 3-dimensional space of points (x,y,z), where x+y+z = 1, with its corners on the points (1,0,0), (0,1,0), and (0,0,1). For that small case, each probability distribution would have three probabilities, and be a point in the triangle such as (0.2344, 0.6815, 0.0841).

Now DEM discuss the distribution of searches – that is, the distribution of probability distributions. Since each probability distribution is a point in the simplex, the distribution of searches is a distribution on that simplex. This is the probability distribution from which the search is said to be chosen. They go to a fair amount of effort, in this paper and in earlier papers by Dembski and Marks and by Dembski, to argue that a uniform distribution of searches on the simplex is a natural starting point from which the searches can be regarded as chosen. They also consider, in the DEM paper, initial distributions that are nonuniform. That does not make much difference for the argument made here. We’re not going to argue with the details of their mathematics, but instead concentrate on what in evolutionary biology corresponds to such a choice of a search.

Their theorem

When one draws a probability distribution, which is one of the points in the simplex, one might get one that assigns a higher probability to the target, or one that assigns a lower probability of the target. On average, they argue, one gets one that has the probability p of hitting the target. DEM show that, in the original uniform distribution of searches, at most a fraction p/q of them will have a probability of finding the target as large as, or larger than q.

They then calculate a quantity that they call “active information” by taking the negative logarithm of this ratio and conclude that this is the amount of information that is built in by the choice of that search. In their argument it is implied that the improved success is due to some Designer having made choices that built that information in.

Mostly not using the fitness.

In Joe’s earlier post, he argued that Dembski and Marks were examining the choice of a fitness surfaces from among all possible fitness surfaces. He was wrong. In fact, most of the searches in their distribution of searches cannot involve going uphill on any fitness surface. One is already in a very small portion of their distribution of searches as soon as the process is doing that. In that case one has an evolutionary search, and that is drawn from a very small fraction of all of their searches. Here is how we can see that.

A simple “greedy” search algorithm

Evolutionary processes occur in populations of organisms that have genotypes and fitnesses. Will a situation like that do as badly as a randomly-chosen search, where the probability of hitting the target is the same as it would be for random draws from the space? We can make a simple model, which easily shows that it is not the same.

Consider a space of DNA sequences, say all possible sequences of a stretch of 1000 nucleotides. The organism has one of these DNA sequences. In each generation it looks at all of its neighbor DNA sequences that have just one of these 1000 bases changed from the present sequence. There are 3000 of these, since each of the 1000 bases has one of the four bases A, C, G, and T and this means that there are 3 others possible at that site. Each DNA sequence has a fitness. Let’s assume that the organism has just one DNA sequence, so it is located at one point in the genotype space. If the most fit of these 3000 neighbors has a higher fitness than the present DNA sequence, let’s assume that the organism changes its DNA sequence to that DNA sequence. Otherwise it stays the same. It goes through m-1 generations of this.

This of course is a very simpleminded model of an evolving population, one that looks only at the neighbors of one genotype, but which also responds perfectly to any fitness differences. The question is not whether this is fully realistic, but whether this simple biasing by natural selection has a major effect on the probability of hitting the target. Let’s call this beast a Greedy Uphill Climber “bug”. We introduce it because it is easy to see what it will do.

Searching for a small target

To make the case even simpler, let’s assume that all the genotypes have different fitness values – there are no ties. There is then only one genotype that has the highest fitness. For our test case, let’s define that one as the target T. In DEM’s argument, the target can be defined in any way you want. It could even be a set of genotypes of unusually low fitness. But as the issue for evolution is whether natural selection can find highly-fit adaptations, it does not make sense to have a target that has unusually low fitness, especially since natural selection will actively move away from it.

Let’s also simplify things by choosing the starting genotype at random from among all possibilities. Our GUC Bug then makes m steps, each time to the most fit of the 3001 sequences that consist of its own genotype, plus the genotypes of its 3000 current neighbors.

Probability of the GUC Bug finding the target

Remember that if we drew at random from a distribution (a “search”) which itself was randomly chosen from the simplex of all probability distributions, we would have only a probability p of hitting the target. That is the same as if we just drew the outcome randomly from the set of possible DNA sequences. In the case of our GUC Bug, we start out with a randomly sampled genotype, and if that were all we did, we would have that small probability of hitting the target.

But if we let the bug do just one more step, so m = 2, it will move to the fittest of the 3001 immediate neighbors. This mimics the effect of natural selection, and that makes us much more likely to hit the target. The GUC Bug will find the target if it starts with the genotype which is the target, or if it starts with any genotype that is an immediate neighbor of the target. As there are 3000 neighbors of each of these DNA sequences, the probability of hitting the target will be about 3001 times greater than p.

If we take more steps, it is not clear how much larger is the set of starting points that will allow us to arrive at the target. It depends on how smooth the fitness surface is. At its smoothest, the fitness surface has no local peaks. For each genotype outside the target, there is a best neighbor of higher fitness, so the GUC Bug will move to that neighbor. If m = 50, there will be a great many neighbor genotypes that are less than 50 steps away from the target. In fact, there will be 1.211×10107 of those neighbors in all. That’s a lot. All of those genotypes are starting points that will lead to T in 49 steps or less. So the probability of a GUC Bug reaching the target is not just p, in the most favorable case it is vastly larger than that.

Behavior on a “white noise” fitness surface

One of us (TE) has carried out computer simulations of this case. He considered 1000-base nucleotide sequences and a GUC Bug started at a random sequence. Running the bug until it reached a local peak of the fitness surface, where no immediate neighbor is more fit, he found that these peaks were typically higher than 99.98% of all points. So even on one of the worst possible fitness surfaces, a GUC Bug does far better than choosing a DNA sequence at random.

Can DEM’s “searches” all be carried out by a greedy search bug?

This immediately establishes that most of the searches in DEM’s space of searches are much worse at finding the target T than any search that has a GUC Bug and a fitness surface. In our case the average chance of success of one of their searches is only p, which is more than 3000 times lower than the average for a GUC Bug that looks at neighbors on a fitness surface once. So a GUC Bug moving on a fitness surface must be far more successful than a random one of DEM’s searches. This is true no matter what the fitness surface is. Simply by having a process that moves to more fit neighbors, we immediately narrow down DEM’s searches to a tiny fraction of all possible searches.

But what about more realistic models of evolution?

These have the same property. In the GUC Bug model, we had only one DNA sequence in the species. If instead there is a population of sequences, then the genotypes of the species have multiple DNA sequences, and by multiple mutations and recombination parts of the space further afield can be reached. On the other hand the GUC Bug is more efficient in moving uphill to more fit genotypes than actual evolutionary processes are. So more realistic models of evolution might be either better or worse at climbing the fitness surface. But all of them move to the target from some reasonably large set of points in the neighborhood of the target. All such models will end up at the target far more often that a blind search will, and that immediately signals that these processes are far different from most of the searches in DEM’s space of searches.

What causes smooth fitness surfaces?

We can see that evolutionary processes are not typical members of DEM’s space of searches, because all of them, no matter what the shape of their fitness surface, do much better than blind search. Within the class of evolutionary processes those that have smoother fitness surfaces do better yet – enormously better. DEM acknowledge this but do not discuss what makes fitness surfaces smooth. As one of us (JF) argued in his previous posts (here, here, here, and here), the ordinary laws of physics, with their weakness of long-range interactions, lead to fitness surfaces much smoother than white-noise fitness surfaces.

In the white-noise surfaces, changing one base in the DNA brings us to a fitness that is in effect randomly chosen from all possible fitnesses. In fact, it brings us to a fitness that is just as bad as if all bases in the DNA were changed simultaneously. That is not like actual biology. Furthermore in a white-noise fitness surface interactions among changes in different sites in the DNA are ubiquitous and incredibly strong. Changing one base leads to a randomly-different fitness. So does changing another. Changing both of those leads to a fitness that is also randomly-chosen, without regard to what the effects of the two earlier changes were. Combining two deleterious changes will then make no prediction that the result will be even more deleterious. Similarly, combining two advantageous changes will make no prediction that the result will be even more advantageous. But with real physics, those predictions can often be made.

Thus we can see that simply having genotypes with different fitnesses leads to results much better than most of the searches in DEM’s space. Considering that “because physics” the fitness surfaces will be nonrandomly smooth brings us to an even tinier fraction of all possible searches, ones that are even more successful. Dembski and Marks would consider these smooth fitness surfaces to have large amounts of “active information”, because they lead to much greater success at reaching any target which includes the genotypes of highest fitness. So these two effects do not require any intervention of a Designer, just the presence of genotypes that have fitnesses, and the action of ordinary laws of physics. Some, quite possibly all, of Dembski and Marks’s “active information” is present as soon as we have genotypes that have different fitnesses, and genotypes whose phenotypes are determined using the ordinary laws of physics.

Is evolution a search?

The modeling of evolutionary processes as searches is of limited help. It is generally not best to regard evolutionary processes as carrying out a search for a target which is an optimal organism.

Evolution does not withhold its approval until it sees whether the single most-fit possible phenotype is found. Whether a species goes extinct depends on its fitnesses along the way, and a species can be quite successful without ever finding the most-fit genotypes. It is almost certain that we are not as fit as the best organism possible anywhere in in our space of genotypes. Requiring that evolution find that optimum result is unreasonable; we may always be stuck in some isolated region of genome space, and all of our wonderful adaptations may be the ones found there. But that is good enough for us to have developed remarkable abilities, including being capable of analyzing arguments about the evolutionary process, and seeing whether they imply the existence of the intervention of a Designer in the evolutionary process. Or whether they do not.

167 Comments

For those who were viewing PT in the first hour after I posted this, apologies for the chaos, which was due to my own mishandling of the editing, plus WordPress’s wierdness.

Now it seems to be as Tom and I wanted it. It is a big, long, somewhat tedious argument, but it is our fairly-serious evaluation of Dembski, Ewert. and Marks’s recent arguments, so we think it is appropriate here.

Let me abstract the whole post quickly, for those readers who are busy:

Dembski, Ewert and Marks have presented a general theory of “search” that has a theorem that, averaged over all possible searches, one does not do better than uninformed guessing (choosing a genotype at random, say). The implication is that one needs a Designer who chooses a search in order to have an evolutionary process that succeeds in finding genotypes of improved fitness.

But there are two things wrong with that argument:

1. Their space of “searches” includes all sorts of crazy searches that do not prefer to go to genotypes of higher fitness – most of them may prefer genotypes of lower fitness or just ignore fitness when searching. Once you require that there be genotypes that have different fitnesses, so that fitness affects their reproduction, you have narrowed down their “searches” to ones that have a much higher probability of finding genotypes that have higher fitness.

2. In addition, the laws of physics will mandate that small changes in genotype will usually not cause huge changes in fitness. This is true because the weakness of action at a distance means that many genes will not interact strongly with each other. So the fitness surface is smoother than a random assignment of fitnesses to genotypes. That makes it much more possible to find genotypes that have higher fitness.

Taking these two considerations into account – that an evolutionary search has genotypes whose fitnesses affect their reproduction, and that the laws of physics militate against strong interactions being typical – we see that Dembski, Ewert, and Marks’s argument does not show that Design is needed to have an evolutionary system that can improve fitness.

It is ironic that Dembski seems to demand that evolution work as though it is an intelligent designer, searching for an optimal solution. It is not. Why must he continue to display his ignorance of basic biological principles? Why must he continue to ignore those who ;point out his errors? What does he hope to gain by continued obfuscation? Does he really think that he is fooling anyone? Why must he misrepresent the way in which natural selection works? Is it because he knows that an accurate representation would eviscerate his argument? Does he really think that assuming your conclusions and trying desperately to develop some twisted mathematical mumbo jumbo to vindicate your preconceptions is productive in any way? Give it up Bill, you has been outed!

I’m responsible for several months’ delay in this post. Joe was ready to go in mid-December. There’s been no substantive change since then.

Anything that Dembski, Ewert, and Marks can come up with is excruciatingly boring, amateurish, and totally irrelevant compared with the really interesting things that are going on in chemistry, biology, and physics.

ID/creationists always start with sectarian dogma as an implicit, if not explicit, goal of their “science;” everything else is bent and broken to fit dogma. Atoms and molecules are modeled by inert objects such as ASCII characters, dice, junkyard and battleship parts, and coin flips. It never seems to occur to any of them that atoms and molecules have electric charge and interact strongly according to quantum mechanical rules. It never seems to occur to them that biological organisms interact strongly with environments that constrain what they can become.

“Advanced mathematics” to an ID/creationist is high school logarithms to base two; with the result labeled as “information” to obscure the fact that a simple multiplication is taking place. Taking log2 of the product Np of the number of trials, N, by a probability per trial, p, and calling it “information” doesn’t suddenly change the product or the concept into something “advanced and profound” and “impossible.” It’s an amateurish bastardization of and misrepresentation of other work going on in the areas of computer science.

In the real world of science, calculations start with the well-studied properties of atoms and molecules, or with the well-studied properties of complex organisms interacting with their environments. The fact that supercomputers are required to do these kinds of calculations at the level of chemistry and physics should be a reminder of the vast differences between what scientists actually do and what people like Dembski, Ewert, and Marks are doing.

Joe Felsenstein said:

Let me abstract the whole post quickly, for those readers who are busy:

Dembski, Ewert and Marks have presented a general theory of “search” that has a theorem that, averaged over all possible searches, one does not do better than uninformed guessing (choosing a genotype at random, say). The implication is that one needs a Designer who chooses a search in order to have an evolutionary process that succeeds in finding genotypes of improved fitness.

But there are two things wrong with that argument:

1. Their space of “searches” includes all sorts of crazy searches that do not prefer to go to genotypes of higher fitness – most of them may prefer genotypes of lower fitness or just ignore fitness when searching. Once you require that there be genotypes that have different fitnesses, so that fitness affects their reproduction, you have narrowed down their “searches” to ones that have a much higher probability of finding genotypes that have higher fitness.

2. In addition, the laws of physics will mandate that small changes in genotype will usually not cause huge changes in fitness. This is true because the weakness of action at a distance means that many genes will not interact strongly with each other. So the fitness surface is smoother than a random assignment of fitnesses to genotypes. That makes it much more possible to find genotypes that have higher fitness.

Taking these two considerations into account – that an evolutionary search has genotypes whose fitnesses affect their reproduction, and that the laws of physics militate against strong interactions being typical – we see that Dembski, Ewert, and Marks’s argument does not show that Design is needed to have an evolutionary system that can improve fitness.

It’s extremely valuable that you had the energy and persistence to do this great review.

I will add that you have reviewed is yet another example of creationists trying to avoid reality and “disprove evolution from above”. And yes, they are trying to deny biological evolution. Saying that it can only work with magic is denying it.

We know how DNA replicates, we know why there are mutations, we can’t predict exactly which mutations will occur when but we have an excellent idea of the frequency of certain types of mutations, and we know that most mutations don’t affect phenotype but some do. When phenotype is affected that may or may not impact on relative reproductive success within a given environment. If so, this will lead to selection for or against the given allele. (In addition some individuals will randomly encounter greater or less reproductive success for a wide number of reasons. There is also a randomness to how alleles are distributed, at least with diploid and polyploidy organisms.) I’m oversimplifying very slightly but basically accurate here.

The primary reason people deny this is to, for ideological reasons, pander to the idea that all species were created in their present form and the Earth is only a few thousand years old. Because if those things are true, the theory of evolution cannot be true. But if you don’t insist on those pre-suppositions the theory of evolution makes a lot of sense. Hence leaders of religions that don’t make those pre-suppositions seldom deny evolution.

The Biblical literacy claim has a political significance in the US. During the civil rights era of the 1950’s and 1960’s, mainstream religion was predominantly on the “liberal” side of that issue. Therefore a version of religion was created that could ostensibly “reclaim morality” for the right wing. This involved cherry picking and emphasizing Biblical passages related to consensual sexual behavior between adults. These passages had to be claimed to be “literally true”; otherwise the argument that consensual behavior that hurts no-one else is not wrong and the passages should not be interpreted to say so would be raised. Therefore the whole thing has to be literally true, therefore science that casts doubt on a “literal” interpretation must be denied.

Dembski works at a high level of abstraction. First “creation science” was invented to deny science and give “moral” justification to right wing policy. Then ID was created to “court proof” creation science. Then the first wave of ID was massively discredited at Dover. Dembski now works on arcane models that can be superficially distanced from first wave ID.

But it’s all the same thing. It’s all denial of evolution because evolution is evidence against a “literal” interpretation of the Bible and a “literal” interpretation of the Bible is associated with a powerful political ideology.

I wrote this a while back: http://www.skepticink.com/smilodons[…]-not-losing/

Basically, that last paragraph. The optimum gene doesn’t necessarily matter… it’s just an allele that is good enough so that the organism doesn’t die and can reproduce.

Tom English said:

I’m responsible for several months’ delay in this post. Joe was ready to go in mid-December. There’s been no substantive change since then.

It takes two to make a delay that long. I was a bit busy with my Winter Quarter course too. Anyway we finally got it out the door.

An interesting distinction is between DEM’s “searches” and the more conventional notion of a “search algorithm”. I can define the latter as a series of operations we do to move in a space of points, each of which has numbers that arise from some function evaluated at those points. Given a search algorithm, we can ask what its behavior is on a given function (a given fitness surface, for example).

But DEM’s “searches” have the unusual property that they are the result of applying a given search algorithm to a given surface. Thus when we consider a different surface, we may have to call the result a different “search”. So the “searches” encompass all possible algorithms used on all possible fitness surfaces. They describe the “search” only in terms of the distribution of results, so it is also possible that two different search algorithms, on two different surfaces, get the same distribution of results and thus are the same “search”.

It is important to keep this in mind when trying to understand their set of possibilities and when trying to relate it to more conventional search algorithms.

Mike Elzinga said:

“Advanced mathematics” to an ID/creationist is high school logarithms to base two; with the result labeled as “information” to obscure the fact that a simple multiplication is taking place.

And double integrals. Don’t forget double integrals.

Is there any hint as to what sort of algorithm would work better in the world of life on Earth?

I gather that DEM’s investigations are about searches which are limited by obeying the laws of nature. If they were to include in their analysis searches with more freedom than the fine-tuned parameters of nature allow, would there be a different result?

fnxtr said:

Mike Elzinga said:

“Advanced mathematics” to an ID/creationist is high school logarithms to base two; with the result labeled as “information” to obscure the fact that a simple multiplication is taking place.

And double integrals. Don’t forget double integrals.

By far the “most advanced” mathematics I have seen from the ID/creationist community was some third semester calculus with the del operator in Granville Sewell’s “paper” about the second law of thermodynamics. Unfortunately PhD mathematician Sewell, after something like 12 years of trying, can’t even get units right when plugging his “X-entropies” into a diffusion equation; let alone get the concepts of entropy and the second law correct. It doesn’t take normal people 12 years to learn thermodynamics and statistical mechanics.

And the poor jokers over at UD are still defending him at this very moment without having a clue about what is in Sewell’s paper or about what the real science is all about.

The Dembski, Ewert, Marks paper is no different. They are just trying to word-game their way to a “convincing argument” against evolution and the origin of life. Each attempt simply sews more confused “certainty” in the “arguments” of their followers. It remains basically log2(Np) and relabeled as various types of “information.” So Dembski, et. al. have advanced no farther than Sewell, Abel, or any of the other ID/creationists. They have no clue what a fitness landscape is, what its properties are, and why it exists

The problems and misconceptions in ID/creationist papers usually show up in the abstracts; so there is no need to actually waste time reading the rest of their papers. Further reading - which I have often done, unfortunately, and have always ended up regretting the wasted time - simply confirms in spades what is already evident in the abstracts to these papers.

After something like 50 years of reading ID/creationist crap just to be sure I haven’t missed any of their misconceptions and misrepresentations, I don’t think I have missed anything important; but I suspect I may have lost a few brain cells as a result.

TomS said:

Is there any hint as to what sort of algorithm would work better in the world of life on Earth?

I gather that DEM’s investigations are about searches which are limited by obeying the laws of nature. If they were to include in their analysis searches with more freedom than the fine-tuned parameters of nature allow, would there be a different result?

Searches in the computer programs doing real science are constrained. Such programs are constrained by including the observed and tested laws of nature in the algorithms; not by asserting - implicitly or explicitly - that the particles or organisms have properties that must comport with sectarian dogma.

Joe Felsenstein said: But there are two things wrong with that argument:

1. Their space of “searches” includes all sorts of crazy searches that do not prefer to go to genotypes of higher fitness…

2. In addition, the laws of physics will mandate that small changes in genotype will usually not cause huge changes in fitness…

…we see that Dembski, Ewert, and Marks’s argument does not show that Design is needed to have an evolutionary system that can improve fitness.

While I appreciate the fact that you guys have updated Joe’s initial crticism as a matter of correctness, this version of their argument doesn’t seem all that substantially different from the earlier versions. It just seems to be the longer more boring version. If I understand correctly, they are still ignoring how the physical world and the surrounding ecology will impact the success/failure of (the set of all possible) genetic reproductive mechanisms.

Moreover, regarding #11 and “is evolution a search,” DEM seems to have forgotten the old joke of the two people running from the bear. No search and no search outcome has to meet some objective measure of goodness to survive; it only has to outrun its competitors. Nor does it even need to outrun the set of all possible competitors, it merely has to outrun the actually present ones.

Keep in mind that having an adequate fitness is not what natural selection favors. A genotype for having a fitness, say, 10% more than that will be favored by natural selection, even if the former genotype was in some sense good enough.

However DEM in their papers have a target (T) for evolution and count whether or not that target is reached. An organism can do quite well without finding the best possible genotype. Which is fortunate for us, since we’re almost certainly not that optimal genotype.

Mike Elzinga said:

TomS said:

Is there any hint as to what sort of algorithm would work better in the world of life on Earth?

I gather that DEM’s investigations are about searches which are limited by obeying the laws of nature. If they were to include in their analysis searches with more freedom than the fine-tuned parameters of nature allow, would there be a different result?

Searches in the computer programs doing real science are constrained. Such programs are constrained by including the observed and tested laws of nature in the algorithms; not by asserting - implicitly or explicitly - that the particles or organisms have properties that must comport with sectarian dogma.

What I was suggesting is that one doesn’t get a more efficient algorithm by having it search more possibilities.

What little we can infer about “Intelligent Design” is that it is not constrained by the laws of nature, which means more possibilities to be searched.

However inefficient evolution - or any search based on natural law - may be, a better way is not to be found by loosening the constraints.

The advocates of ID ought to be searching for more constraints, if they find evolution too inefficient.

”harold” Wrote:

Saying that it can only work with magic is denying it.

It’s worse than denying it. It’s trying to have it both ways. Which would be completely unnecessary if “DEM” had the slightest bit of evidence for one of the popular, mutually-contradictory pseudoscientific “alternatives.” If DEM were right - and they are certainly not – they are tacitly admitting – though 99% of their target audience, and even many critics, will completely miss it – that it would still be evolution as science defines it, ~4 billion years of common descent with modification and all. At most it would require an occasional change in the laws of physics, not necessarily real time designer intervention. At most they would have found another “deviation,” such as when quantum mechanics caused scientists to rethink Newtonian physics.

That they have steadfastly refused for 13+ years (Dembski’s pathetic “it’s not ID’s task…” comment) to even speculate on the where’s and whens of such “deviations,” ought to make it perfectly clear that they know they’re wrong even about that part. But they know that (1) millions need only the slightest uncertainly of evolution as an excuse to fall back on comfortable childhood myths, and (2) most critics will be preoccupied with how DEM enable those myths (very true) or even believe them (almost certainly not true). What DEM want is nothing less than for “X and ‘not X’ to be true at the same time.”

”harold” Wrote:

The primary reason people deny this is to, for ideological reasons, pander to the idea that all species were created in their present form and the Earth is only a few thousand years old.

I would say the only reason is ideological. But pardon the broken record, there’s nothing special about that particular one of the mutually-contradictory alternatives, especially since the majority of rank and file evolution-deniers don’t really buy it, but are merely politically sympathetic to it. Big-tent activists like DEM are certainly not going to criticize YEC, but they also wish that it had never been concocted in the first place.

TomS said:

Mike Elzinga said:

TomS said:

Is there any hint as to what sort of algorithm would work better in the world of life on Earth?

I gather that DEM’s investigations are about searches which are limited by obeying the laws of nature. If they were to include in their analysis searches with more freedom than the fine-tuned parameters of nature allow, would there be a different result?

Searches in the computer programs doing real science are constrained. Such programs are constrained by including the observed and tested laws of nature in the algorithms; not by asserting - implicitly or explicitly - that the particles or organisms have properties that must comport with sectarian dogma.

What I was suggesting is that one doesn’t get a more efficient algorithm by having it search more possibilities.

What little we can infer about “Intelligent Design” is that it is not constrained by the laws of nature, which means more possibilities to be searched.

However inefficient evolution - or any search based on natural law - may be, a better way is not to be found by loosening the constraints.

The advocates of ID ought to be searching for more constraints, if they find evolution too inefficient.

This is certainly true for DEM’s theorems. As theorems they may be mathematically true, but the average poor performance of searches is true only because so many irrelevant and downright crazy searches are included among the set of possible searches. The constraints that are needed arise from simply having genotypes that differ in fitnesses, and constraining the searches to those where the fitnesses affect the reproduction of the genotypes. When you add constraints that make the fitness surfaces smooth “because physics”, evolutionary searches do even better.

The same issue rose in Dembski’s earlier use of the “No Free Lunch” argument. Dembski used Wolpert and Macready’s NFL theorem, which is mathematically OK. But in applying it to evolution, Dembski tacitly assumed that a typical fitness surface was a “white noise” surface which has no correlation of fitness of adjacent genotypes. That infinitely-jaggy fitness surface is a very bad one for evolution, but again “because physics” it is not typical in the real world. This was immediately pointed out by many critics of Dembski (Richard Wein and Jason Rosenhouse in 2002 being two of the first).

Recently Denyse O’Leary at Uncommon Descent quoted with approval an invocation of Dembski’s NFL argument. She has apparently not gotten the word that the NFL argument is dead as a refutation of evolution, and has been dead for some years.

So the constraints needed are not mysterious or controversial – they are simple conditions that are easily visible. Genotypes have fitnesses, and physics implies that closely similar genotypes often have similar fitnesses. DEM’s Active Information argument can have force only if we ignore those straightforward constraints.

typo in here somewhere: “This shows that even a search which has is evolution”

Nick Matzke said:

typo in here somewhere: “This shows that even a search which has is evolution”

Thanks, Nick. I have corrected this (point 8 in the post). “has” was not supposed to be there, so it now reads “… which is evolution”.

Joe Felsenstein said:

TomS said:

Mike Elzinga said:

TomS said:

Is there any hint as to what sort of algorithm would work better in the world of life on Earth?

I gather that DEM’s investigations are about searches which are limited by obeying the laws of nature. If they were to include in their analysis searches with more freedom than the fine-tuned parameters of nature allow, would there be a different result?

Searches in the computer programs doing real science are constrained. Such programs are constrained by including the observed and tested laws of nature in the algorithms; not by asserting - implicitly or explicitly - that the particles or organisms have properties that must comport with sectarian dogma.

What I was suggesting is that one doesn’t get a more efficient algorithm by having it search more possibilities.

What little we can infer about “Intelligent Design” is that it is not constrained by the laws of nature, which means more possibilities to be searched.

However inefficient evolution - or any search based on natural law - may be, a better way is not to be found by loosening the constraints.

The advocates of ID ought to be searching for more constraints, if they find evolution too inefficient.

This is certainly true for DEM’s theorems. As theorems they may be mathematically true, but the average poor performance of searches is true only because so many irrelevant and downright crazy searches are included among the set of possible searches. The constraints that are needed arise from simply having genotypes that differ in fitnesses, and constraining the searches to those where the fitnesses affect the reproduction of the genotypes. When you add constraints that make the fitness surfaces smooth “because physics”, evolutionary searches do even better.

The same issue rose in Dembski’s earlier use of the “No Free Lunch” argument. Dembski used Wolpert and Macready’s NFL theorem, which is mathematically OK. But in applying it to evolution, Dembski tacitly assumed that a typical fitness surface was a “white noise” surface which has no correlation of fitness of adjacent genotypes. That infinitely-jaggy fitness surface is a very bad one for evolution, but again “because physics” it is not typical in the real world. This was immediately pointed out by many critics of Dembski (Richard Wein and Jason Rosenhouse in 2002 being two of the first).

Recently Denyse O’Leary at Uncommon Descent quoted with approval an invocation of Dembski’s NFL argument. She has apparently not gotten the word that the NFL argument is dead as a refutation of evolution, and has been dead for some years.

So the constraints needed are not mysterious or controversial – they are simple conditions that are easily visible. Genotypes have fitnesses, and physics implies that closely similar genotypes often have similar fitnesses. DEM’s Active Information argument can have force only if we ignore those straightforward constraints.

OK, but I was approaching this from another angle.

Supposing, for the sake of the argument, that they have shown that a certain search which is constrained by the laws of nature is exceedingly inefficient.

How does one get a more efficient search?

ISTM that what one does is to make a narrower search. That is, that one makes more constraints, over and above those laws of nature which were specified at first. Something like what you said, if I understand you correctly.

It is totally wrong-headed to loosen the constraints. That makes the search worse.

“Intelligent Design”, as far as I can tell, operates beyond the laws of nature. The whole point of ID is that it can do everything that nature can do, and more. That is, ID loosens the constraints imposed by the laws of nature. ID is precisely the wrong way to solve the supposed problem of inefficiency of natural searches.

Supernatural (or whatever they have in mind) searches are less efficient than natural searches.

I assume that the ID solution is to say that there is some secret way that supernatural searches work, that aren’t captured by mathematics, or else that we poor mortals are not privy to, or something about all of this is just some pathetic detail.

TomS said:

OK, but I was approaching this from another angle.

Supposing, for the sake of the argument, that they have shown that a certain search which is constrained by the laws of nature is exceedingly inefficient.

How does one get a more efficient search?

ISTM that what one does is to make a narrower search. That is, that one makes more constraints, over and above those laws of nature which were specified at first. Something like what you said, if I understand you correctly.

It is totally wrong-headed to loosen the constraints. That makes the search worse.

“Intelligent Design”, as far as I can tell, operates beyond the laws of nature. The whole point of ID is that it can do everything that nature can do, and more. That is, ID loosens the constraints imposed by the laws of nature. ID is precisely the wrong way to solve the supposed problem of inefficiency of natural searches.

Supernatural (or whatever they have in mind) searches are less efficient than natural searches.

I assume that the ID solution is to say that there is some secret way that supernatural searches work, that aren’t captured by mathematics, or else that we poor mortals are not privy to, or something about all of this is just some pathetic detail.

I am not sure that ID is supposed to work by narrowing the possibilities down so a natural process can more efficiently search.

I suppose the natural processes could be listening to the Voice Of The Designer which says “warmer, warmer, now colder …”

Joe Felsenstein said: I am not sure that ID is supposed to work by narrowing the possibilities down so a natural process can more efficiently search.

I suppose the natural processes could be listening to the Voice Of The Designer which says “warmer, warmer, now colder …”

I am not making myself clear. (Not the first time, unfortunately.)

I am sure that ID is not supposed to work by narrowing the possibilities. How ID does work, that is pathetic detail.

I am sure that ID is supposed to widen the possibilities. By opening up the possibilities to things that are not available to natural events.

How ID is supposed to work when it is widening the possibilities, when widening the possibilities only makes things more difficult?

Well, we do know that there is a reason that we are not ask about pathetic detail.

TomS said:

How ID is supposed to work when it is widening the possibilities, when widening the possibilities only makes things more difficult?

More difficult for who? Evolutionary search? No, it does not need that search.

ID says “Zap! You are better! And don’t ask me for the pathetic details!”

However DEM in their papers have a target (T) for evolution and count whether or not that target is reached. An organism can do quite well without finding the best possible genotype. Which is fortunate for us, since we’re almost certainly not that optimal genotype.

So the whole thing is meaningless.

This is, of course, one of the fundamental problems that Biblical literalism has with evolution, and a common misunderstanding by honest lay people as well.

The first big problem is that 6000 years isn’t long enough, but the other big problem is that if you see evolution in terms trying to reach a foreseen target, it doesn’t make a lot of sense.

(If you’re a sophisticated Ken Miller type, you can always argue that even though there is no appearance of aiming for a target from the human perspective, a deity “ultimately intended” the current biosphere or some such thing. But you argue that only in philosophy and theology class. In science class, evolution does NOT represent a search for a foreseen target.)

Anything that models evolution as a search for a predetermined target is 100% wrong.

That is NOT to say that we can’t broadly predict some outcomes of evolution. Put a group of fully characterized ancestors in a controlled environment, and we can make solid predictions about what may evolve, either in a model or in an experiment.

But I can also broadly predict outcomes of a lightening strike. That doesn’t mean that Thor planned that outcome and consciously used a lightening strike to achieve it.

Evolution is a “random variation first” process, not a planned search for a target.

Joe Felsenstein said:

TomS said:

How ID is supposed to work when it is widening the possibilities, when widening the possibilities only makes things more difficult?

More difficult for who? Evolutionary search? No, it does not need that search.

ID says “Zap! You are better! And don’t ask me for the pathetic details!”

Exactly. That is the flaw in my reasoning. ID cuts the Gordian Knot. It doesn’t search for the way to untie it.

TomS said:

It is totally wrong-headed to loosen the constraints. That makes the search worse.

I think I understand your point; relaxing constraints to “allow more possibilities” would indeed make a search more inefficient by allowing more ridiculous results that aren’t observed in nature. It is equivalent to denying that there are laws of physics and chemistry that play a central role in the properties and behaviors of atoms and molecules.

From what I have seen of ID/creationist thinking, however, they already believe that literally every molecular arrangement is possible, meaning therefore, that observed biological structures are an infinitesimally small subset of all imaginable configurations.

The direct assertion is that the probabilities of molecular assemblies of living organisms are less than (1/2)500 because the number of trials that have taken place in the observable universe is supposed to have been 2500 (a figure Dembski stole from the abstract of a paper by Seth Lloyd in Physical Review Letters).

The product, Np is then less than one. If they take the logarithm to base 2 of this product and call it “information”, then Dembski et. al. claim that there has to be some “active information” to overcome the odds against the specified - i.e., specified in advance - “information” in the molecular assemblies of living organisms.

The molecular assemblies of living organisms are called “Complex Specified Information” because, in the ID/creationist mind, they are so improbable that they can’t happen in the lifetime of the universe. “Active information” implies some kind of intelligence has stepped into the process and produced what we see. That is their ultimate objective.

Underlying all of this is the tornado-in-a-junkyard argument that has as its foundation the erroneous notion that the second law of thermodynamics is about everything coming all apart and requiring intelligence to assemble and hold atoms and molecules together.

ID/creationists argue explicitly that the genetic algorithms of science are unfair because they put the answer into the algorithm. They actually want to remove all constraints to “prove” just how improbable the molecular assemblies of biology are in ID/creationist “reality.”

From what I have observed of them over the years, ID/creationists can’t do high school level math without extreme difficulty; and those that struggle their way through a calculation have no clue what it all means. But they already “know” ahead of time that biological structures are too improbable to have happened without the intervention of a deity; and that is what they want taught in public education under the bamboozlement of their pseudomath.

As I have said on other occasions, the life’s work of Dembski et. al.. can be summarized in a sentence; “N is 2500, the probability of this specified molecular assembly is less than the probability of a specified string of ASCII characters in a Shakespearean sonnet, making Np less than 1; therefore evolution and abiogenisis can’t be explained by natural means.”

This is ID in a nutcase. Stripped down to its fundamental essence, it is pretty kooky.

TomS said:

What I was suggesting is that one doesn’t get a more efficient algorithm by having it search more possibilities.

What little we can infer about “Intelligent Design” is that it is not constrained by the laws of nature, which means more possibilities to be searched.

However inefficient evolution - or any search based on natural law - may be, a better way is not to be found by loosening the constraints.

The advocates of ID ought to be searching for more constraints, if they find evolution too inefficient.

I don’t want to give aid and comfort to buffoons like DEM, but I don’t think I agree with your point, or maybe I find it too easy to misinterpret.

You can definitely improve some optimizations by loosening constraints–by which I mean allowing the search to explore parts of the space that do “worse” according to the objective function. In fact, if you don’t do this, you have hill-climbing, and get stuck in a local optimum. Think about something as simple as solving a maze in which the objective is based on distance to the exit. You will rapidly get stuck in a dead-end unless you can explore locations that take you farther from the exit.

Anyway, I am probably missing your point. I’m not that interested in NFL arguments, so I may be missing some subtleties. I just wanted to disagree with the statement (perhaps taken out of context) that having more constraints will always make a search faster. Loosening constraints (in a very vague sense) makes more parts of the search space accessible, and may result in a shorter number of steps to other local optima that improve on the current one.

I may be missing all the nuances here, but what I’m reading boils down to “let’s assume evolution works according to some silly and unrealistic assumptions. Then let’s show that it can’t work that way. Then let’s conclude that the Designer must have done it.”

And what this says (as has been pointed out), untangles as “Let’s assume the Designer did it. Then let’s confect a hopelessly misguided model of how it might work without the Designer. Then let’s show that this stupid model must be wrong.”

I personally suspect that few normal creationists would bother trying to make any sense of DEM or anything similar. Their approach is probably tougher to counter: “Goddidit, I believe it, go away.”

Flint said:

And what this says (as has been pointed out), untangles as “Let’s assume the Designer did it. Then let’s confect a hopelessly misguided model of how it might work without the Designer. Then let’s show that this stupid model must be wrong.”

Or in other words, it’s a long and convoluted strawman argument. I think “strawman” covers the vast majority of attempted attacks against evolution.

It is not exhaustive. “Hitler said that too.” is another line of attack though, but really minor by comparison.

Richard B. Hoppe said:

Coming late to this discussion, I’ll merely repeat what I’ve been saying for years now: Treating biological evolution as a formal search process is a snare and a deception. DEM are both snared and (self-)deceived.

As you know, I agree fully. I gave a brief explanation, somewhere up the thread, of the difference between modeling and and problem solving.

callahanpb said:

But the term itself was coined purely as a thermodynamic concept (by Rudolph Clausius in 1865 if I can trust Wiktionary).

This is from Rudolf Clausius in Annalen der Physik und Chemie, Vol. 125, p. 353, 1865, under the title “Ueber verschiedene für de Anwendung bequeme Formen der Hauptgleichungen der mechanischen Wärmetheorie.” (“On Several Convenient Forms of the Fundamental Equations of the Mechanical Theory of Heat.”)

The coining of the word entropy appears on Page 390 of that paper; which, by the way, can be obtained off the internet.

It is also available in A Source Book in Physics, Edited by William Francis Magie, Harvard University Press, 1963, page 234. Magie’s translation appears here, and it is a very smooth and accurate translation of the original German; which I have also checked.

(Note: Q represents the quantity of heat, T the absolute temperature, and S will be what Clausius names as entropy)

…….

We obtain the equation

dQ/T = S - S0

which, while somewhat differently arranged, is the same as that which was formerly used to determine S.

If we wish to designate S by a proper name we can say of it that it is the transformation content of the body, in the same way that we say of the quantity U that it is the heat and work content of the body.

However, since I think it is better to take the names of such quantities as these, which are important for science, from the ancient languages, so that they can be introduced without change into all the modern languages, I propose to name the magnitude S the entropy of the body, from the Greek word η τροπη, a transformation.

I have intentionally formed the word entropy so as to be as similar as possible to the word energy, since both these quantities, which are to be known by these names, are so nearly related to each other in their physical significance that a certain similarity in their names seemed to me advantageous.

…….

Clausius translates η τροπη from the Greek as die Verwandlung (transformation) and not Umdrehung. However, this doesn’t matter because he modified the word to entropy for the reasons he indicated.

That’s it, there is nothing about order or disorder anywhere in this coining of the term entropy. It has never been otherwise.

On the other hand, here is Henry Morris’ pseudo-scholarship back in 1973.

…..

The very terms themselves express contradictory concepts. The word “evolution” is of course derived from a Latin word meaning “out-rolling”. The picture is of an outward-progressing spiral, an unrolling from an infinitesimal beginning through ever broadening circles, until finally all reality is embraced within.

“Entropy,” on the other hand, means literally “in-turning.” It is derived from the two Greek words en (meaning “in”) and trope (meaning “turning”). The concept is of something spiraling inward upon itself, exactly the opposite concept to “evolution.” Evolution is change outward and upward, entropy is change inward and downward.

….. And it’s been downhill ever since with the ID/creationists.

Richard B. Hoppe said:

Coming late to this discussion, I’ll merely repeat what I’ve been saying for years now: Treating biological evolution as a formal search process is a snare and a deception. DEM are both snared and (self-)deceived.

Let me agree only partially. Search for a defined ultimate goal, no. I agree that biologists would not want to make model evolution as doing that.

But Sewall Wright in his famous 1932 paper at the International Congress of Genetics modeled evolution as change on a fitness surface, with natural selection tending to push the population uphill (and other evolutionary forces doing other things, such as genetic drift causing random walks. This usually reaches a local optimum but not the global optimum. When people like Dembski and Marks argue that evolutionary biologists have used models of search, that is the literature that they invoke. And use of genetic algorithms by nonbiologists to solve nonbiological optimization problems is motivated by a distinct interest in finding the global optimum.

callahanpb said:

Joe Felsenstein said:

So I guess I join all of nature, including all the hippopotamai and all the octopodes, in approving this usage.

My favorite crime against etymology is the term “mentee” meaning a “person who is advised, trained, or counseled by a mentor”, but language is ultimately determined by usage in practice and I now find things like this more amusing than troublesome.

“Attendee” - ‘I went to the conference and got attended on. The dry cleaning bill isgoing to be awful!’

As regards ‘mentee’ (I didn’t know ISIS were targetting language as well as every other aspect of culture!) - you could always take the position that ‘mentor’ is derive from the ‘mentir’ - to lie. The mentor is the one who lies, the mentee the person lied to. You know it makes sense…

It looks like Ewert over at Evolution Snooze and Ooze is still getting the basic science wrong and attributing to the ID/creationists’ enemies (i.e., the scientific community) views that no scientists hold. He asserts:

“To put the subject in a specific context, consider the example of birds. Birds are biological marvels. They are in constant struggle against the laws of physics. Entropy is perpetually trying to break birds apart, but they remain alive. A chaotic environment tries to prevent successful reproduction, yet birds reproduce copiously. Gravity tries to keep birds on the ground, yet they fly. This is not to say that birds violate the laws of physics; rather, they live, reproduce, and fly even though the laws of physics make these tasks rather difficult.”

and the rest of the complaint is all downhill from there.

I doubt that we will ever see the day when ID/creationists start picking up basic science textbooks and start learning from the beginning; like, say, back in middle school and high school. It remains a stunning feature of ID/creationism that ID/creationists never take the time to learn the basic physics and chemistry. Only their own pseudoscience satisfies them.

From the very next paragraph by Ewert:

“Clearly, some configurations of matter are birds. However, almost all configurations of matter are not birds. If one were to pick randomly from all possible configurations of matter, the probability of obtaining a bird would be infinitesimally small. It is almost impossible to obtain a bird by random sampling uniformly from all configurations of matter.

(Emphasis added)

Dembski, Ewert, and Marks - like all ID/creationists - haven’t advanced beyond Henry Morris and Duane Gish. They are still using misconceptions and misrepresentations of basic physics, chemistry, and biology as the premises of all their tirades. It is still the tornado-in-a-junkyard argument that they are making; and, to them, everything comes all apart unless some intelligence intervenes.

It gets worse. a little later Ewert drops this dog turd:

“Ultimately, the fact that birds exist has to be explained in terms of the initial configuration of the universe. The universe must have begun with a large amount of active information with respect to the target of birds”

How in the world did he decide that extant birds were one of evolution’s “targets”? His logic means that every of the 50 million or so extant species, and the 100X that number now extinct must have also been “targets” predefined by his “active information”. Not only that, the “active information” for extant species had to account for all the major mass extinction events including the Earth getting clobbered by a honkin’ big asteroid 66 MYA. That’s one heck of a lot of “active information”. I wonder where it all resided for the last 4.5 billion years?

That post is so full of misconceptions and misrepresentations that it is totally irrelevant to anything science has to say. Look at this one, for example.

” The use of the term “search” has led some to argue over whether or not Darwinian evolution can be considered a search. After all, Darwinian evolution is not a teleological process and does not search for a goal. However, all that we mean by search is a process that can be represented as a probability distribution. That means that all processes reducible to chance and necessity qualify as searches.

(Emphasis again added)

So the fact that there are asteroids out there in our solar system that each have some probability of hitting Earth means that the asteroids are “searching” for Earth?

Does it mean that a mixture of hydrogen and oxygen are “searching” for a water molecule configuration? Are oxygen atoms “searching” for a diatomic molecule or a triatomic molecule (ozone)? Is the “tunneling” of an electron through a potential barrier to an adjacent potential well evidence that the electron is “searching” for the other well?

And furthermore, even if one attempts to portray such phenomena as “searches,” what in the world justifies the assumption of a “random sampling uniformly from all configurations of matter distribution”?

Sheesh; high school physics and chemistry, Ewert! Atoms and molecules interact strongly. Go read a book about it.

The entire article is pure gibberish. It is nothing more than the typical crackpot characteristic of trying to climb onto the back of working scientists in order to leverage recognition and legitimacy for crackpot ideas. All crackpots do it. ID/creationists have been doing this ever since Morris and Gish started doing it back in the 1970s.

Look at this mischaracterization.

” Felsenstein and English argue along similar lines. They point to the weakness of long-range physics effects to produce what they argue will be a good landscape for Darwinian evolution. Wagner, English, and Felsenstein thus actually accept the conclusion of conservation of information. “

(Emphasis again added)

Reading for comprehension is not a trait found in ID/creationists; they quote mine for effect and affect.

Distant weak interactions produce smooth landscapes (potential wells). No spiky landscapes or potential well distributions really exist in nature.

Joe Felsenstein said:

And use of genetic algorithms by nonbiologists to solve nonbiological optimization problems is motivated by a distinct interest in finding the global optimum.

In fact, having used genetic algorithms for 20 years to model world markets (among other things) to drive derivatives trading, my group never once fooled itself into believing that we were searching for some chimerical “global optimum.” We were satisfied with satisficing (in Simon’s sense) solutions. In the old joke, we didn’t have to outrun the bear; we just had to outrun (some of? most of?) the other players in the game.

Mike, thanks for the updates. Wow you and Timothy picked out some real whoppers. Vince Torley is also discussing the Douglas Axe’s work on the same subject over at UD, and they are both (Axe and Torley) using the same bad ‘tornado in a junkyard’ math. Here’s a quote. Note for clarity: the first part is Torley paraphrasing Axe:

If we compare the number of 150-amino-acid sequences that correspond to some sort of functional protein to the total number of possible 150-amino-acid sequences, we find that only a tiny proportion of possible amino acid sequences are capable of performing a function of any kind. The vast majority of amino-acid sequences are good for nothing. So, what proportion are we talking about here? An astronomically low proportion: 1 in 10 to the power of 74, according to work done by Dr. Douglas Axe. When we add the requirement that a protein has to be made up of amino acids that are either all left-handed or all right-handed, and when we finally add the requirement that the amino acids have to be held together by peptide bonds, we find that only 1 in 10 to the power of 164 amino-acid sequences of that length are suitable proteins. 1 in 10 to the power of 164 is 1 in 1 followed by 164 zeroes.

Just like Ewert, they’re still modeling the probability of some positive adaptation or genetic sequence arising as [set of sequences that give it] / [set of all possible sequences]. Ignoring descent with modification, ignoring selection, and thus ignoring the fact that this mechanism renders their model denominator completely invalid.

Richard B. Hoppe said:

Joe Felsenstein said:

And use of genetic algorithms by nonbiologists to solve nonbiological optimization problems is motivated by a distinct interest in finding the global optimum.

In fact, having used genetic algorithms for 20 years to model world markets (among other things) to drive derivatives trading, my group never once fooled itself into believing that we were searching for some chimerical “global optimum.” We were satisfied with satisficing (in Simon’s sense) solutions. In the old joke, we didn’t have to outrun the bear; we just had to outrun (some of? most of?) the other players in the game.

This sounds interesting, both in its own right, and as a put-down to creationist arguments. Does anyone have some accessible literature on this?

eric said:

Just like Ewert, they’re still modeling the probability of some positive adaptation or genetic sequence arising as [set of sequences that give it] / [set of all possible sequences]. Ignoring descent with modification, ignoring selection, and thus ignoring the fact that this mechanism renders their model denominator completely invalid.

This particular bit of IDiocy still makes me crazy. Despite being corrected on the fatal flaw literally hundreds of times the IDiots keep making the same dumb mistake. You can’t calculate output probability of a long term iterative feedback process like evolution by taking a one time snapshot of the result. You have to take into account the feedback driven changes.

A good example is in 5 card poker. Say you walk into a room and see someone is holding a royal straight flush. The probability of getting dealt those 5 cards directly is approx. 1 in 650,000. But suppose the player was allowed to discard and redraw three times before holding the hand? Then the probability goes up. Suppose the player was allowed to discard and redraw up to a thousand times? Then the probability begins to approach 1.0. Just looking at the current cards tells you nothing about the probability. You have to take into account the rules and history of the game to get an accurate estimate.

Even now - after something like 50 years of watching ID/creationists - I still am amazed at how resistant ID/creationists are to getting a proper education in science. It isn’t just that they are ignorant of basic scientific concepts and facts; it’s that the crap they believe is dead wrong at even the most basic level. And they work at getting it wrong; one can actually watch the process of bending and breaking concepts in order to support sectarian beliefs.

It may seem humorous in some sense; but in fact, these people are serious about wrecking science education through political action and repeated harassment of school boards and state boards of education. It is no coincidence that people like Casey Luskin show up frequently at school boards, state boards of education, state legislatures, and other places to hawk ID/creationist wares.

ID/creationists portray themselves as persecuted, beleaguered martyrs bucking an evil and corrupt cabal of scientists who are keeping them from achieving the fame and adulation they crave. It’s the typical crackpot persecution complex.

Andreas Wagner, author of Arrival of the Fittest had a rather succinct way of describing them, especially the YECs; “Half literate and wholly ignorant.”

I think Wagner is being a bit too kind. I don’t see how people who routinely scan for quote mines and who distort well-known, basic concepts as they go can be considered literate at any level. Literacy is more than just mouthing words; any computer text reader can do that. Literacy is not about selective scanning for debating points.

Mike Elzinga said:

Even now - after something like 50 years of watching ID/creationists - I still am amazed at how resistant ID/creationists are to getting a proper education in science. It isn’t just that they are ignorant of basic scientific concepts and facts; it’s that the crap they believe is dead wrong at even the most basic level. And they work at getting it wrong; one can actually watch the process of bending and breaking concepts in order to support sectarian beliefs.

It may seem humorous in some sense; but in fact, these people are serious about wrecking science education through political action and repeated harassment of school boards and state boards of education. It is no coincidence that people like Casey Luskin show up frequently at school boards, state boards of education, state legislatures, and other places to hawk ID/creationist wares.

ID/creationists portray themselves as persecuted, beleaguered martyrs bucking an evil and corrupt cabal of scientists who are keeping them from achieving the fame and adulation they crave. It’s the typical crackpot persecution complex.

Andreas Wagner, author of Arrival of the Fittest had a rather succinct way of describing them, especially the YECs; “Half literate and wholly ignorant.”

I think Wagner is being a bit too kind. I don’t see how people who routinely scan for quote mines and who distort well-known, basic concepts as they go can be considered literate at any level. Literacy is more than just mouthing words; any computer text reader can do that. Literacy is not about selective scanning for debating points.

It isn’t only about science that they parade their illiteracy. It extends so far as to being able to read the Bible. When I began to become acquainted with creationism, it surprised me how superficial was their knowledge of the Bible. I wasn’t expecting them to be at ease with Hebrew, Aramaic and Greek. (Although it did amuse me to see them refer to the glossary in Strong’s Concordance.) What became clear is that they relied on what somebody telling them what is in the Bible. Apparently when they open their Bible and let their eyes pass over the words, that has no relevance to what they are thinking. (I admit that I have some sympathy for someone who lets one’s attention wander when negotiating vast dry tracts of the Bible. No wonder that the survival skills that they have thus acquired are carried over elsewhere.)

(disclosure: was posting as callahanpb until Google dropped OpenId 2.0)

I have often wondered that creationists (particulary the YE variety) manage to dress themselves each morning let alone hold down paying employment. Now, inspired by “Tornado in a Junkyard”, I realize that I have a mathematical proof that they cannot.

Let’s start by considering socks. A sock should go on a foot. It doesn’t matter if it is the left or right foot, but it has a uniform probability of being somewhere entirely different, such as the creationist’s ear or nose. For that matter, could hang from any one of ten fingers, and so on. It might simply fall to the floor or hover in the air. It might not even be a sock. Thus, the probability of one sock actually being on the creationist’s foot is already quite low. The probability of each sock being on a distinct foot is vanishingly small. Extend this to other articles of clothing, and after pages of additional analysis, taking logs and adding them to make it much more scientific than mere multiplication, we determine that the CSI of a properly dressed creationist cannot be explained by chance. Indeed, only by divine will could any one of them make it out of the house each morning (granting that some may stay at home and type randomly on the nearest available keyboard).

For my next trick, I will explain how it is impossible for light to travel in a straight line.

Isn’t that only if it drank too much?

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This page contains a single entry by Joe Felsenstein published on March 29, 2015 8:02 AM.

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