No free lunch for Darwinists - no substance to false claims of "progress" in the field of abiogenesis
Here is another common fallacy: "Everyone agrees that abiogeneis had to happen, that non-life developed somehow into life."
The primary difference between ID proponents and Creationists is that Creationists are willing to identify the Designer as the Creator God whereas many ID scientists do not take the findings of operational science and deduce anything but simply study the world using the actual scientific method that involves methodological investigation. Naturalism is not part of the scientific method.
credit
From Biologic Institute:
An introduction to the Biologic Institute from me to you... A Christmas present for the scientific minded...I suppose if you are hoping to illustrate the hopelessness of abiogenesis this would be considered "progress" but otherwise it is just a few more shovelfuls of evidence thrown upon the coffin of Darwinism. We are going to have that thing dead and buried before anyone gets around to holding a funeral!
~~~~~~~
So as usual another attempt by Darwinists to identify a source of information for life is a failure. Natural selection chooses FROM information, mutation is broken information that was already there in one way or another and all these computer-modeled information sources turn out to be provided with "help" finding information.
So we again reference the dictionaries to remind everyone:
Definitions of information on the Web from Merriam Webster
Other sources...
No, the Law of Biogenesis remains unchallenged. Never has life come from non-life and real scientists are throwing up their hands at the thought of finding a natural means of producing life. It is the same situation with the Laws of Thermodynamic. Naturalism is helpless to explain existence, information and life.
Only a supernatural Creator can explain these things.
From Biologic Institute:
Evolutionary Algorithms: Are We There Yet?
— December 17th, 2010 by Ann Gauger
In the recent past, several papers have been published that claim to demonstrate that biological evolution can readily produce new genetic information, using as their evidence the ability of various evolutionary algorithms to find a specific target. This is a rather large claim.
It has thus fallen to others in the scientific or engineering community to evaluate these published claims. How well do these algorithms model biology? How exactly was the work done? Do the results make sense? Are there unexamined variables that might affect the interpretation of results? Are there hidden sources of bias? Are the conclusions justified or do they go beyond the scope of what has been shown?
A new paper by Montañez et al. [1], just published in the journal BIO-Complexity, answers some of these questions for the evolutionary algorithm ev [2], one of the computer programs proposed to simulate biological evolution. As perhaps should be no surprise, the authors found that ev uses sources of active information (meaning information added to the search to improve its chances of success compared to a blind search) to help it find its target. Indeed, the algorithm is predisposed toward success because information about the search is built into its very structure.
(This aforementioned paper is available for download as a pdf right here.)
These same authors have previously reported on the hidden sources of information that allowed another evolutionary algorithm, AVIDA [3-5], to find its target. Once again, active information introduced by the structure of the algorithm was what allowed it to be successful.
These results confirm that there is no free lunch for evolutionary algorithms. Active information is needed to guide any search that does better than a random walk.
[1] doi:10.5048/BIO-C.2010.3
[2] doi:10.1093/nar/28.14.2794
[3] doi:10.1038/nature01568
[4] doi:10.1109/SSST.2010.5442816
[5] doi:10.1109/ICSMC.2009.5345941
It has thus fallen to others in the scientific or engineering community to evaluate these published claims. How well do these algorithms model biology? How exactly was the work done? Do the results make sense? Are there unexamined variables that might affect the interpretation of results? Are there hidden sources of bias? Are the conclusions justified or do they go beyond the scope of what has been shown?
A new paper by Montañez et al. [1], just published in the journal BIO-Complexity, answers some of these questions for the evolutionary algorithm ev [2], one of the computer programs proposed to simulate biological evolution. As perhaps should be no surprise, the authors found that ev uses sources of active information (meaning information added to the search to improve its chances of success compared to a blind search) to help it find its target. Indeed, the algorithm is predisposed toward success because information about the search is built into its very structure.
(This aforementioned paper is available for download as a pdf right here.)
These same authors have previously reported on the hidden sources of information that allowed another evolutionary algorithm, AVIDA [3-5], to find its target. Once again, active information introduced by the structure of the algorithm was what allowed it to be successful.
These results confirm that there is no free lunch for evolutionary algorithms. Active information is needed to guide any search that does better than a random walk.
[1] doi:10.5048/BIO-C.2010.3
[2] doi:10.1093/nar/28.14.2794
[3] doi:10.1038/nature01568
[4] doi:10.1109/SSST.2010.5442816
[5] doi:10.1109/ICSMC.2009.5345941
~~~~~~~
So we again reference the dictionaries to remind everyone:
Definitions of information on the Web from Merriam Webster
in·for·ma·tion
noun \ˌin-fər-ˈmā-shən\Definition of INFORMATION
1
: the communication or reception of knowledge or intelligence
2
a (1) : knowledge obtained from investigation, study, or instruction (2) : intelligence, news (3) : facts, data b : the attribute inherent in and communicated by one of two or more alternative sequences or arrangements of something (as nucleotides in DNA or binary digits in a computer program) that produce specific effects c (1) : a signal or character (as in a communication system or computer) representing data (2) : something (as a message, experimental data, or a picture) which justifies change in a construct (as a plan or theory) that represents physical or mental experience or another construct d : a quantitative measure of the content of information; specifically : a numerical quantity that measures the uncertainty in the outcome of an experiment to be performed
3
: the act of informing against a person
4
: a formal accusation of a crime made by a prosecuting officer as distinguished from an indictment presented by a grand jury
— in·for·ma·tion·al \-shnəl, -shə-nəl\ adjective
— in·for·ma·tion·al·ly adverb
Other sources...
- a message received and understood
- knowledge acquired through study or experience or instruction
- formal accusation of a crime
- data: a collection of facts from which conclusions may be drawn; "statistical data"
- (communication theory) a numerical measure of the uncertainty of an outcome; "the signal contained thousands of bits of information"
wordnetweb.princeton.edu/perl/webwn - Information as a concept has many meanings, from everyday usage to technical settings. The concept of information is closely related to notions of constraint, communication, control, data, , instruction, knowledge, meaning, mental stimulus, pattern, perception, and representation. ...
en.wikipedia.org/wiki/Information
The Science of Denial
— October 6th, 2009 by Douglas Axe
Scientists sometimes find themselves wishing things were different. In one sense that’s a thoroughly unremarkable observation. After all, scientists are human, and humans have always found themselves wishing things were different.
But what if some of the things scientists wish were different are the very things they have devoted themselves to studying? In other words, forget about salaries, teaching loads, and grant funding. What if some scientists want the brute facts of their own field of study to be other than what they really are?
As odd as it may seem, particularly to non-scientists, that tension between preference and reality has always been a part of doing science. Like everyone else, scientists don’t just have ideas—they favor them… even promote them. And for scientists, as for everyone else, sometimes those cherished ideas are just plain wrong.
For decades now, a growing minority of scientists have argued that the standard explanations of biological origins are prime examples this—cherished ideas that are spectacularly wrong. That raises an interesting question. If these ideas are really so wrong, why do so many experts affirm them?
Some, of course, would call this a false paradox. By their way of thinking, the mere fact that so many experts accept these ideas shows that they can’t be badly wrong. But paradigm shifts do happen in science, and every time they do the world is treated to the memorable spectacle of lots of experts being badly wrong.
Even experts have ways of avoiding reality. When it comes to the improbabilities that plague naturalistic origins stories, the avoidance often takes the form of what I’ve called the ‘divide and conquer’ fallacy. [1] It works like this. Instead of asking what needs to be explained naturalistically, you concentrate on what can be so explained. Specifically, you look for some small piece of the real problem for which you can propose even a sketchy naturalistic solution. Then, once you have this mini-solution, you present it as a small but significant step toward the ultimate goal of a full credible story.
But the only way to tell whether small steps of this kind are taking us toward that ultimate goal or away from it is to examine them carefully in the context of the whole problem. If that analysis doesn’t give the intended result, it’s tempting to skip it and end on a happy note.
Consider the work that Lehmann, Cibils, and Libchaber recently published on the origin of the genetic code. [2] By one account they have “generated the first theoretical model that shows how a coded genetic system can emerge from an ancestral broth of simple molecules.” [3]
That would be huge alright. And huge claims always call for caution.
Let’s start with some background. The “broth” that Lehmann et al. are thinking of is sometimes called the “RNA world”—a hypothetical early stage in the evolution of life when RNA served both the genetic role that DNA now serves and the catalytic role that proteins now serve.
In modern life, most RNA performs a cellular function analogous to the function of the clipboard on your computer. It enables sections of ‘text’ to be lifted from a larger ‘document’ for temporary use. These sections are genes and the document is the genome. By providing in this way temporary working copies of genetic text, RNA contributes to the central purpose of genes, which is to provide the sequence specifications for manufacturing the functional proteins that do the molecular work of life.
This is where the genetic code comes in, and with it the daunting problem it poses for naturalistic accounts of origins. The key thing to grasp is that genes are as unlike proteins as successions of dots and dashes are unlike written text. Only when a convention is established, like Morse code, and a system put in place to implement that convention, can dots and dashes be translated into written text. And then, only meaningful arrangements of dots and dashes will do. Likewise, only a system implementing a code for translating gene sequences (made from the four nucleotides) into protein sequences (made from the twenty amino acids) can enable genes to represent functional proteins, as they do in life.
What makes it so hard to imagine how this system could have evolved is the need for it to be complete in order for it to work, coupled with the need for it to be complex in order to be complete. To agree that “•” stands for e is relatively simple, but not in itself very helpful. Only when a whole functional alphabet is encoded in this way do we have something useful. Similarly, it seems that an apparatus for decoding genes, and thereby implementing a genetic code, would have to physically match each of the twenty biological amino acids to a different nucleotide pattern. Whatever else that apparatus might be, it can’t be simple. Moreover, it can’t be useful without some meaningful genes (encoding useful proteins) to go with it.
This realization is enough to make even a committed to materialist give up on the idea of an evolutionary explanation. Evolutionary biologist Eugene Koonin appears to have done just that. In his words, “How such a system could evolve is a puzzle that defeats conventional evolutionary thinking.” [4] Accordingly, he proposes the unconventional solution of an infinite universe (a multiverse) in which even the seemingly impossible becomes certain.
I think it’s fair to say that most biologists are uncomfortable with Koonin’s proposal. Part of what bothers them is the tacit abandonment of more conventional solutions, as though these have no hope of ever succeeding. In the wake of this, Lehmann, Cibils, and Libchaber are, in effect, refusing to throw in the towel, and that merits attention in itself.
Instead of making the universe bigger, they propose a way of making the genetic code smaller, hoping that this downsized version might feasibly arise in a conventional evolutionary way. But there’s a risk. Their efforts to simplify could easily lead to oversimplification.
They presuppose an RNA-world endowed with two kinds of tRNA molecules, each of which has dual functional capacities: at one end they attach an amino acid, and at the other they pair with a specific base triplet (codon) on an RNA gene. Their world also has steady supplies of two kinds of amino acid, at least one kind of RNA gene that restricts itself to the two codons recognized by the tRNAs, and “a ribosome-like cofactor” that cradles the complex formed between the tRNA that caries the new protein chain and the codon to which it is paired.
The immediate question is, how could a world that has never encoded proteins have done so much preparation to become a world that does encode proteins? We seem to be left with the familiar alternatives of extraordinary improbability or guided design. Here it has to be conceded that Koonin’s proposal is at least commendably frank, in that it acknowledges the improbabilities. Lehmann et al., like everyone else, prefer not to go there.
Maybe that’s because, like everyone else, they find themselves between a rock and a hard place. Since the modern system for implementing the genetic code is way too complicated to have appeared by accident, they know they need to look for not just a simplification, but a radical simplification. But if it’s hard to explain how even a modest simplification could leave the basic function intact, imagine how hard it becomes for a radical simplification.
Their efforts to find a workable compromise between sterile simplicity and complex functionality are both laudable and instructive, but unsuccessful nonetheless.
Their simplified proteins are built from two amino acids instead of twenty. People have tried to fish out life-like proteins from pools of random chains made from just a few amino acids, but nothing impressive has ever come of it. That’s not surprising when you consider how fussy real-life proteins are about their amino-acid sequences. The idea of forcing them to hand over eighteen of their constituent amino acids without so much as a complaint is just plain unrealistic.
Lehmann, Cibils, and Libchaber attempt to push their proteins even further. Their translation mechanism has an extraordinarily high error rate, resulting in about one wrong amino acid for every six added to a new chain. And that’s under ideal conditions. Things get much worse if the conditions deteriorate.
Let’s experiment with this. If you haven’t read the title of their paper, hold off and we’ll see if you can read a version of it that has been simplified along the lines of their proposal. Protein functions would have to be remarkably relaxed about protein sequences for their simplifications to have worked in early life. The test will be to see whether you are comparably relaxed about spelling when you read.
The most common vowel in the title of their paper is e, and the most common consonant is n. To mimic their proposed simplification of proteins, let’s replace all the vowels in their title with e and all the consonants with n, randomly mistaking vowels and consonants about one sixth of the time. The random errors make many versions of the title possible, but you don’t have to see many examples to convince yourself that this isn’t going to work:
This isn’t meant to be a proof, of course, just an illustration. It approximates the scale of simplification that Lehmann et al. have proposed for protein sequences, and in so doing it provides very reasonable grounds for suspecting they have oversimplified. Something closer to proof can be had by examining how fussy real protein functions are about protein sequences. That whole field of work, as I see it anyway, seems to confirm the suspicion.
So in the end, Lehmann, Cibils and Libchaber seem to have taken us a step further from a naturalistic explanation for life rather than a step closer. Some people will be more pleased with that conclusion than others, and that’s okay. From the standpoint of science, every step is progress.
[1] Perspectives, 1 April 2009
[2] Lehmann J, Cibils M, Libchaber A (2009)
[3] ScienceDaily
[4] Koonin EV (2007)
"As odd as it may seem, particularly to non-scientists, that tension between preference and reality has always been a part of doing science. Like everyone else, scientists don’t just have ideas—they favor them… even promote them. And for scientists, as for everyone else, sometimes those cherished ideas are just plain wrong."
Merry Christmas, Darwinists! Here is your present...a chance to understand the error of your ways and adjust to 21st Century discoveries about life and existence. Evidence, my friends, not fairy tales....And with that thought in mind, Darwinists are invited to take part in the discussion of complexity in the cell. No need to deny it or hide it, but rather face it and explore it!
Now, I usually sympathize with those who want troublemakers to stop making trouble. Trouble has a bad name for good reasons. But on the other hand, we often find ourselves looking back with gratitude at certain troublemakers of the past—people who persisted in shaking things up, usually at great personal cost, until their cause won the day.
It seems to me that the trouble ID has brought on the science academy is of this more noble kind. Like all scientific controversies, this one is about ideas. And while ideas can be very powerful, they only become dangerous when no one is allowed to critique them openly. Where scrutiny is encouraged, the worst that an idea can be is false. Where it is forbidden, things can get much worse (as history shows).
With that in mind, if you examine the way scientists on both sides of the ID debate are conducting themselves, which side would you say is generally doing a better job of inviting critical scrutiny? Which side is earnestly seeking the strongest critique that the other side can offer? The answer should be obvious. It has to be the side that is promoting the debate, right? Or conversely, which side has little tolerance for dissent? That’s equally obvious. It’s the conflicted side—the one that is constantly switching between denying that the debate exists, trying to win it, and trying to shut it down.
Of those three conflicting options, only one—the desire to be proven right—has a legitimate place in science. The greatest moments in the history of scientific discourse happened when people were so committed to getting it right and so sure of being right that they welcomed critical scrutiny. They weren’t always right, of course, but there is nothing shameful in that. Quite the opposite, in fact. This contest of ideas, this rigorous exchange, is precisely how science is meant to work.
And that’s exactly what BIO-Complexity is about. Unlike most science journals, this one is founded on critical scientific exchange. That commitment began with an inclusive approach to recruiting scientists to serve as editors. As one of the people involved in the process, I can assure you that whatever the Editorial Board [2] ends up looking like when all the replies are in, the invitations went out to everyone we could think of with the expertise and the interest to make a useful contribution, regardless of their perspective on ID. Inevitably some will have been overlooked, and these too will be welcome later additions, pending board approval.
BIO-Complexity demonstrates its commitment to critical exchange in other ways as well. For every peer-reviewed article it publishes, it seeks a well-informed Critique of that article. And for each of these it seeks a Response from the original authors. Unlike the original articles they comment on, Critiques and Responses won’t be peer reviewed. The reason for this is that we want to give people appropriate freedom to state informed opinions boldly, without the level of caution that peer review tends to enforce. And on the subject of peer review, the policy of BIO-Complexity is to seek evaluation from experts who fall on both sides of the ID controversy.
Finally, you can have your say as well, because everyone who agrees to abide by three common-sense rules can post comments on anything and everything that BIO-Complexity publishes [3]. The rules are known as the three Rs: real names, respectful tone, and relevant focus. Published articles will be technical, so you’ll want to have some familiarity with their subject matter in order to post comments, but we guarantee there won’t be any viewpoint discrimination here. If you can find a polite way to say that someone’s conclusions look completely wrong, then go ahead and say it (and don’t be offended if someone politely returns the favor).
Enough said. Go explore. I can’t think of anything bad to say about BIO-Complexity, so I’ll leave that to others. Let them have their say, and then come back to the question of what science is all about. If you’re a big fan of science, I think you’ll end up being a big fan of BIO-Complexity.
[1] http://bio-complexity.org
[2] BIO-Complexity Editors
[3] See registration information.
But what if some of the things scientists wish were different are the very things they have devoted themselves to studying? In other words, forget about salaries, teaching loads, and grant funding. What if some scientists want the brute facts of their own field of study to be other than what they really are?
As odd as it may seem, particularly to non-scientists, that tension between preference and reality has always been a part of doing science. Like everyone else, scientists don’t just have ideas—they favor them… even promote them. And for scientists, as for everyone else, sometimes those cherished ideas are just plain wrong.
For decades now, a growing minority of scientists have argued that the standard explanations of biological origins are prime examples this—cherished ideas that are spectacularly wrong. That raises an interesting question. If these ideas are really so wrong, why do so many experts affirm them?
Some, of course, would call this a false paradox. By their way of thinking, the mere fact that so many experts accept these ideas shows that they can’t be badly wrong. But paradigm shifts do happen in science, and every time they do the world is treated to the memorable spectacle of lots of experts being badly wrong.
Even experts have ways of avoiding reality. When it comes to the improbabilities that plague naturalistic origins stories, the avoidance often takes the form of what I’ve called the ‘divide and conquer’ fallacy. [1] It works like this. Instead of asking what needs to be explained naturalistically, you concentrate on what can be so explained. Specifically, you look for some small piece of the real problem for which you can propose even a sketchy naturalistic solution. Then, once you have this mini-solution, you present it as a small but significant step toward the ultimate goal of a full credible story.
But the only way to tell whether small steps of this kind are taking us toward that ultimate goal or away from it is to examine them carefully in the context of the whole problem. If that analysis doesn’t give the intended result, it’s tempting to skip it and end on a happy note.
Consider the work that Lehmann, Cibils, and Libchaber recently published on the origin of the genetic code. [2] By one account they have “generated the first theoretical model that shows how a coded genetic system can emerge from an ancestral broth of simple molecules.” [3]
That would be huge alright. And huge claims always call for caution.
Let’s start with some background. The “broth” that Lehmann et al. are thinking of is sometimes called the “RNA world”—a hypothetical early stage in the evolution of life when RNA served both the genetic role that DNA now serves and the catalytic role that proteins now serve.
In modern life, most RNA performs a cellular function analogous to the function of the clipboard on your computer. It enables sections of ‘text’ to be lifted from a larger ‘document’ for temporary use. These sections are genes and the document is the genome. By providing in this way temporary working copies of genetic text, RNA contributes to the central purpose of genes, which is to provide the sequence specifications for manufacturing the functional proteins that do the molecular work of life.
This is where the genetic code comes in, and with it the daunting problem it poses for naturalistic accounts of origins. The key thing to grasp is that genes are as unlike proteins as successions of dots and dashes are unlike written text. Only when a convention is established, like Morse code, and a system put in place to implement that convention, can dots and dashes be translated into written text. And then, only meaningful arrangements of dots and dashes will do. Likewise, only a system implementing a code for translating gene sequences (made from the four nucleotides) into protein sequences (made from the twenty amino acids) can enable genes to represent functional proteins, as they do in life.
What makes it so hard to imagine how this system could have evolved is the need for it to be complete in order for it to work, coupled with the need for it to be complex in order to be complete. To agree that “•” stands for e is relatively simple, but not in itself very helpful. Only when a whole functional alphabet is encoded in this way do we have something useful. Similarly, it seems that an apparatus for decoding genes, and thereby implementing a genetic code, would have to physically match each of the twenty biological amino acids to a different nucleotide pattern. Whatever else that apparatus might be, it can’t be simple. Moreover, it can’t be useful without some meaningful genes (encoding useful proteins) to go with it.
This realization is enough to make even a committed to materialist give up on the idea of an evolutionary explanation. Evolutionary biologist Eugene Koonin appears to have done just that. In his words, “How such a system could evolve is a puzzle that defeats conventional evolutionary thinking.” [4] Accordingly, he proposes the unconventional solution of an infinite universe (a multiverse) in which even the seemingly impossible becomes certain.
I think it’s fair to say that most biologists are uncomfortable with Koonin’s proposal. Part of what bothers them is the tacit abandonment of more conventional solutions, as though these have no hope of ever succeeding. In the wake of this, Lehmann, Cibils, and Libchaber are, in effect, refusing to throw in the towel, and that merits attention in itself.
Instead of making the universe bigger, they propose a way of making the genetic code smaller, hoping that this downsized version might feasibly arise in a conventional evolutionary way. But there’s a risk. Their efforts to simplify could easily lead to oversimplification.
They presuppose an RNA-world endowed with two kinds of tRNA molecules, each of which has dual functional capacities: at one end they attach an amino acid, and at the other they pair with a specific base triplet (codon) on an RNA gene. Their world also has steady supplies of two kinds of amino acid, at least one kind of RNA gene that restricts itself to the two codons recognized by the tRNAs, and “a ribosome-like cofactor” that cradles the complex formed between the tRNA that caries the new protein chain and the codon to which it is paired.
The immediate question is, how could a world that has never encoded proteins have done so much preparation to become a world that does encode proteins? We seem to be left with the familiar alternatives of extraordinary improbability or guided design. Here it has to be conceded that Koonin’s proposal is at least commendably frank, in that it acknowledges the improbabilities. Lehmann et al., like everyone else, prefer not to go there.
Maybe that’s because, like everyone else, they find themselves between a rock and a hard place. Since the modern system for implementing the genetic code is way too complicated to have appeared by accident, they know they need to look for not just a simplification, but a radical simplification. But if it’s hard to explain how even a modest simplification could leave the basic function intact, imagine how hard it becomes for a radical simplification.
Their efforts to find a workable compromise between sterile simplicity and complex functionality are both laudable and instructive, but unsuccessful nonetheless.
Their simplified proteins are built from two amino acids instead of twenty. People have tried to fish out life-like proteins from pools of random chains made from just a few amino acids, but nothing impressive has ever come of it. That’s not surprising when you consider how fussy real-life proteins are about their amino-acid sequences. The idea of forcing them to hand over eighteen of their constituent amino acids without so much as a complaint is just plain unrealistic.
Lehmann, Cibils, and Libchaber attempt to push their proteins even further. Their translation mechanism has an extraordinarily high error rate, resulting in about one wrong amino acid for every six added to a new chain. And that’s under ideal conditions. Things get much worse if the conditions deteriorate.
Let’s experiment with this. If you haven’t read the title of their paper, hold off and we’ll see if you can read a version of it that has been simplified along the lines of their proposal. Protein functions would have to be remarkably relaxed about protein sequences for their simplifications to have worked in early life. The test will be to see whether you are comparably relaxed about spelling when you read.
The most common vowel in the title of their paper is e, and the most common consonant is n. To mimic their proposed simplification of proteins, let’s replace all the vowels in their title with e and all the consonants with n, randomly mistaking vowels and consonants about one sixth of the time. The random errors make many versions of the title possible, but you don’t have to see many examples to convince yourself that this isn’t going to work:
This isn’t meant to be a proof, of course, just an illustration. It approximates the scale of simplification that Lehmann et al. have proposed for protein sequences, and in so doing it provides very reasonable grounds for suspecting they have oversimplified. Something closer to proof can be had by examining how fussy real protein functions are about protein sequences. That whole field of work, as I see it anyway, seems to confirm the suspicion.
So in the end, Lehmann, Cibils and Libchaber seem to have taken us a step further from a naturalistic explanation for life rather than a step closer. Some people will be more pleased with that conclusion than others, and that’s okay. From the standpoint of science, every step is progress.
[1] Perspectives, 1 April 2009
[2] Lehmann J, Cibils M, Libchaber A (2009)
[3] ScienceDaily
[4] Koonin EV (2007)
"As odd as it may seem, particularly to non-scientists, that tension between preference and reality has always been a part of doing science. Like everyone else, scientists don’t just have ideas—they favor them… even promote them. And for scientists, as for everyone else, sometimes those cherished ideas are just plain wrong."
Merry Christmas, Darwinists! Here is your present...a chance to understand the error of your ways and adjust to 21st Century discoveries about life and existence. Evidence, my friends, not fairy tales....And with that thought in mind, Darwinists are invited to take part in the discussion of complexity in the cell. No need to deny it or hide it, but rather face it and explore it!
The Debate Over Design Gains Momentum with a New Peer-Reviewed Science Journal: BIO-Complexity
— April 30th, 2010 by Douglas Axe
It’s no secret that the scientific establishment is decidedly against not just the idea of intelligent design but also the idea of debating that idea. They just wish the whole subject would go away. That being the case, most establishment-minded scientists will, I suspect, thoroughly disapprove of BIO-Complexity, a new science journal that positively welcomes the scientific debate [1].Now, I usually sympathize with those who want troublemakers to stop making trouble. Trouble has a bad name for good reasons. But on the other hand, we often find ourselves looking back with gratitude at certain troublemakers of the past—people who persisted in shaking things up, usually at great personal cost, until their cause won the day.
It seems to me that the trouble ID has brought on the science academy is of this more noble kind. Like all scientific controversies, this one is about ideas. And while ideas can be very powerful, they only become dangerous when no one is allowed to critique them openly. Where scrutiny is encouraged, the worst that an idea can be is false. Where it is forbidden, things can get much worse (as history shows).
With that in mind, if you examine the way scientists on both sides of the ID debate are conducting themselves, which side would you say is generally doing a better job of inviting critical scrutiny? Which side is earnestly seeking the strongest critique that the other side can offer? The answer should be obvious. It has to be the side that is promoting the debate, right? Or conversely, which side has little tolerance for dissent? That’s equally obvious. It’s the conflicted side—the one that is constantly switching between denying that the debate exists, trying to win it, and trying to shut it down.
Of those three conflicting options, only one—the desire to be proven right—has a legitimate place in science. The greatest moments in the history of scientific discourse happened when people were so committed to getting it right and so sure of being right that they welcomed critical scrutiny. They weren’t always right, of course, but there is nothing shameful in that. Quite the opposite, in fact. This contest of ideas, this rigorous exchange, is precisely how science is meant to work.
And that’s exactly what BIO-Complexity is about. Unlike most science journals, this one is founded on critical scientific exchange. That commitment began with an inclusive approach to recruiting scientists to serve as editors. As one of the people involved in the process, I can assure you that whatever the Editorial Board [2] ends up looking like when all the replies are in, the invitations went out to everyone we could think of with the expertise and the interest to make a useful contribution, regardless of their perspective on ID. Inevitably some will have been overlooked, and these too will be welcome later additions, pending board approval.
BIO-Complexity demonstrates its commitment to critical exchange in other ways as well. For every peer-reviewed article it publishes, it seeks a well-informed Critique of that article. And for each of these it seeks a Response from the original authors. Unlike the original articles they comment on, Critiques and Responses won’t be peer reviewed. The reason for this is that we want to give people appropriate freedom to state informed opinions boldly, without the level of caution that peer review tends to enforce. And on the subject of peer review, the policy of BIO-Complexity is to seek evaluation from experts who fall on both sides of the ID controversy.
Finally, you can have your say as well, because everyone who agrees to abide by three common-sense rules can post comments on anything and everything that BIO-Complexity publishes [3]. The rules are known as the three Rs: real names, respectful tone, and relevant focus. Published articles will be technical, so you’ll want to have some familiarity with their subject matter in order to post comments, but we guarantee there won’t be any viewpoint discrimination here. If you can find a polite way to say that someone’s conclusions look completely wrong, then go ahead and say it (and don’t be offended if someone politely returns the favor).
Enough said. Go explore. I can’t think of anything bad to say about BIO-Complexity, so I’ll leave that to others. Let them have their say, and then come back to the question of what science is all about. If you’re a big fan of science, I think you’ll end up being a big fan of BIO-Complexity.
[1] http://bio-complexity.org
[2] BIO-Complexity Editors
[3] See registration information.