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Questioning The Role Of Gene Duplication-Based Evolution In Monarch Migration

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Each year about 100 million Monarch butterflies from Canada and northeastern United States make their journey to the Mexican Sierra Madre mountains in an astonishing two-month long migration (Ref 1).  They fly 2500 miles to a remote area that is only 60 square miles in size (Ref 1).  No one fully understands what triggers this mass movement of Lepidopterans.  But there is no getting away from the fact that this is a phenomenon that, as one review summed up, “staggers the mind”, especially when one considers that these butterflies are freshly-hatched (Ref 1).  In short, Monarch migrants are always “on their maiden voyage” (Ref 2).  The location they fly to is home to a forest of broad-trunked trees that effectively retain warmth and keep out rain- factors that are essential for the Monarchs’ survival (Ref 1).
 
With a four-inch wingspan and a weight of less than 1/5th of an ounce, it is remarkable that the Monarchs survive the odyssey (Ref 1).  Making frequent stops for nectar and water, they fly approximately 50 miles a day avoiding all manner of predator.  Rapidly shifting winds over the great lakes and scorching desert temperatures in the southern states provide formidable obstacles (Ref 1).  Nevertheless the Monarchs’ finely-tuned sense of direction gets most of them across.
 
It was not until 1975 that scientists first uncovered the full extent of the Monarch’s migration (Ref 1).  What has become clear since then is that only Monarchs travel such distances to avoid the “certain death of a cold winter”.   According to University of Toronto zoologist David Gibo, soaring is the key to making it to Mexico (Ref 1). Indeed flapping wings is about the most energy inefficient way of getting anywhere.  Other aspects of the Monarch’s migration-linked behaviors, such as the reproductive diapause that halts energy-draining reproductive activity during its journey, continue to fascinate scientists worldwide (Ref 2).  Both diapause and the 6-month longevity characteristic of Monarchs are caused by decreased levels of Juvenile Hormone which is itself regulated by four genes (Ref 2).
 
Exactly how Monarchs navigate so precisely to such a specific location is a subject of intense debate.  One theory suggests that they respond to the sun’s location, another that they are somehow sensitive to the earth’s magnetic field (Ref 1).  Recent molecular studies have shown that Monarchs have specialized cells in their brains that regulate their daily ‘clock’ and help keep them on course (Ref 3).  Biologist Chip Taylor from the University of Kansas has done some remarkable tagging experiments demonstrating that even if Monarchs are moved to different locations during the course of their journey south, they are still able to re-orient themselves and continue onwards to their final destination (Ref 1). 
 
A study headed by Stephen Rappert at the University of Massachusetts has elucidated much of the biological basis of the timing-component of Monarch migration (Ref 3).  Through a process better known as time-compensated sun compass orientation, proteins with names such as Period, Timeless, Cryptochrome 1 and Cryptochrome 2 provide Monarchs with a well-regulated light responsiveness during both day and night (Ref 3).  While Cryptochrome 1 is a photoreceptor that responds specifically to blue light, Cryptochrome 2 is a repressor of transcription, efficiently regulating the period and timeless genes during the course of a 24-hour light cycle (Ref 3).  Investigations using Monarch heads have not only provided exquisite detail of the daily, light-dependent oscillations in the amounts of these proteins but have also revealed a ‘complex relationship’ of molecular happenings. 
 
Indeed, the activities of both Cryptochrome 2 and Timeless are intertwined with at least two other timing proteins called ‘Clock’ and ‘Cycle’ (Ref 3).  Preliminary results suggest that Period, Timeless and Cryptochrome 2 form a large protein complex, with Cryptochrome 2 being a repressor of Clock and Cycle transcription.  Cryptochrome 2 is also intimately involved with an area of the Monarch’s brain called the Central Cortex that likely houses the light-dependent ‘sun compass’, so critical for accurate navigation (Ref 3).
 
Rappert’s team have speculated that the Monarch’s dual Cryptochrome light response system evolved into the single Cryptochrome systems found in other insects through a hypothetical gene loss event (Ref 3).  Furthermore they have suggested that the dual Cryptochrome system itself arose through a duplication of an ancestral gene (Ref 3).  Biologist Christopher Wills wrote of gene duplication as a ‘rare occurrence’ in which “an extra copy of a gene gets placed elsewhere in the genome” (Ref 4, p.95).  Seen from an evolutionary perspective, these two gene copies are then “free to evolve separately…shaped by selection and chance to take on different tasks” (Ref 4, p.95).
 
While experiments have shown that transgenic Monarch Cryptochrome 1 can rescue Cryptochrome deficiency in other insects such as fruit flies, what still remains elusive is how exactly gene duplication could have lead to two proteins with such widely-differing functions as those found in the two Monarch Cryptochromes.  Indeed biochemist Michael Behe has been instrumental in revealing the explanatory insufficiencies of terms such as gene duplication and genetic shuffling within the context of molecular evolution.  As Behe expounded:
 
“The hypothesis of gene duplication and shuffling says nothing about how any particular protein or protein system was first produced- whether slowly or suddenly, or whether by natural selection or some other mechanism….. In order to say that a system developed gradually by a Darwinian mechanism a person must show that the function of the system could “have formed by numerous, successive slight modifications”…If a factory for making bicycles were duplicated it would make bicycles, not motorcycles; that’s what is meant by the word duplication.  A gene for a protein might be duplicated by a random mutation, but it does not just “happen” to also have sophisticated new properties” (Ref 5, pp.90, 94).
 
When it comes to supplying a plausible mechanism for how gene duplication and subsequent natural selection led to two distinctly functioning Cryptochromes and how these then integrated with other time-regulatory proteins in Monarch brains, there is a noticeable absence of detail.  Each successive slight modification of a duplicated gene would have had to confer an advantage, for selection and chance to get anywhere.  Furthermore the newly duplicated Cryptochrome would have had to have become successfully incorporated into a novel scheme of daylight processing for migration patterns to begin. 
 
Evolutionary biology must move beyond its hand-waving generalizations if it is to truly gain the title of a rigorous scientific discipline.  In the meantime, protein systems such as the Monarch’s Cryptochromes will continue to challenge what we claim to know about evolutionary origins.
     
References
1. NOVA: The Incredible Journey Of The Butterflies, Aired on PBS on the 27th January, 2009, See http://www.pbs.org/wgbh/nova/butterflies/program.html
 
2. Haisun Zhu, Amy Casselman, Steven M. Reppert (2008), Chasing Migration Genes: A Brain Expressed SequenceTag Resource for Summer and Migratory Monarch Butterflies (Danaus plexippus), PLoS One, Volume 3 (1), p. e1345
 
3. Haisun Zhu, Ivo Sauman, Quan Yuan, Amy Casselman, Myai Emery-Le, Patrick Emery, Steven M. Reppert (2008), Cryptochromes Define a Novel Circadian Clock Mechanism in Monarch Butterflies That May Underlie Sun Compass Navigation, PLoS Biology, Volume 6 (1), pp. 0138-0155
 
4. Christomper Wills (1991), Exons, Introns & Talking Genes: The Science Behind The Human Genome Project, Oxford University Press, Oxford UK
 
5. Michael Behe (1996), Darwin’s Black Box, The Biochemical Challenge To Evolution,  A Touchstone Book Published By Simon & Schuster, New York

 

Copyright (c) Robert Deyes, 2009

Comments
Tim:
Well, I don’t know much about computers, but how hard would it be to demonstrate this? I mean, just take “Deep Blue” and his nasty cousin “Even Deeper Blue”, remove any software concerning the rules concerning games that are draws, and see what happens.
You seem to be saying, "Remove the software necessary for calling a draw, and see if the computer calls a draw." I don't see how this demonstrates anything.
I’d suggest that it is because the Turing Machine is, by definition, responding to the tape (or input).
I'm afraid I don't follow your reasoning at all here.
The problem is not that the chess board positions are finite, the problem is that computer chess programs have no idea what to do with that information.
I don't understand. Who said that the finitude of a chess board is a problem? And whatever information you're referring to, why can't chess programs be designed to know what to do with it?
Trust me, ROb, if you put a king of each color on a chess board and tell two computers to play until checkmate, that is an infinite system. Truth be told, I don’t even know what you mean by infinite system, but I have watched two nine year olds play chess.
Infinite refers to the number of possible states, as in the previous sentence. Sorry I wasn't more clear on that. Again, it's quite trivial to program a computer to detect all non-halting situations in an 8x8 chess board. Having it detect some some of those situations in a reasonably efficient manner is non-trivial, but certainly doable.
John Searle takes it seriously. (I’ve been doing a little reading — a dangerous thing.)
Searle's Chinese Room thought experiment actually argues against functionalism, a philosophical notion. One can theoretically reject functionalism without rejecting the computability of human mental activity. To the extent that Searle's argument is interpreted as an argument against such computability, it's not taken seriously by computing theorists. I don't recall ever seeing a defense of it by anyone in a computer field.
...I found evidence that humans can think “off the tape” in ways that are not simply input/compute/output that suggest no diffulties with the halting problem that computers face...
Then let me be the first to congratulate you, and I expect to see your name in lights soon.
“In fact, if you could prove that humans are capable of anything that computers are in principle incapable of, you would be quite famous.”–ROb Aw shucks, ok, here are several things that computers are incapable of doing in principle that humans find quite easy to do:
Asserting isn't proving. Saying that computers are in principle incapable of doing something means that they are logically, not just technologically (currently), incapable. So you should be able to provide a logical proof.R0b
March 12, 2009
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ROb (and the chess problem) I wrote that two computers (king v king) will never stop chasing each other around a board and say (insert HAL voice here), "How about a draw, Dave?" unless it is part of their program. I wrote: Two computers NEVER will. BOb responded: "If you could prove that, you would revolutionize the world of computing theory." Well, I don't know much about computers, but how hard would it be to demonstrate this? I mean, just take "Deep Blue" and his nasty cousin "Even Deeper Blue", remove any software concerning the rules concerning games that are draws, and see what happens. Now, before we go down the path of computers that are far more complex and thus may have a fighting chance of coming up with, "how about a draw?" (Right ROb?) I mentioned the halting problem. More specifically I mentioned applying the halting problem solution over Turing Machines. ROb correctly stated, "The halting problem simply says that no computer can detect all conceivable non-halting situations." Here is where I would ask onlookers to consider the reasoning that underlies that difficulty. I'd suggest that it is because the Turing Machine is, by definition, responding to the tape (or input). "In fact, it’s trivial to write a program that will detect (albeit inefficiently) any non-halting situation for any system with a finite number of possible states, like a chess board."--ROb The problem is not that the chess board positions are finite, the problem is that computer chess programs have no idea what to do with that information. "Halting problem issues come into play only if . . . it needs to handle infinite systems."--ROb Trust me, ROb, if you put a king of each color on a chess board and tell two computers to play until checkmate, that is an infinite system. Truth be told, I don't even know what you mean by infinite system, but I have watched two nine year olds play chess. "And there is no evidence that humans can do better than computers in this regard."--ROb Well, there is some evidence. See, years ago very soon after chess was invented, someone invented the idea of drawing a chess game. "More succinctly stated, your claim is that humans are not computers in the computing theoretic sense. That is a claim that nobody has been able to validate and is not taken seriously in computing theory."--ROb John Searle takes it seriously. (I've been doing a little reading -- a dangerous thing.) "That’s one of the reasons that the ID dichotomy of intelligence vs. chance+law is either poorly conceived or poorly stated."--ROb Because I still don't agree with what you've written about my chess game example, and because I found evidence that humans can think "off the tape" in ways that are not simply input/compute/output that suggest no diffulties with the halting problem that computers face, I simply don't believe that the ID position on intelligence is ill-conceived. I know I haven't linked the innovation that humans exhibit to a type of solution for the halting problem in a rigorous matter, but that's because I haven't fully understood it's application to human thought and how that would work. Never-the-less, two nine year olds knew to offer each other a draw and it only took twenty minutes of trash-talking to figure it out. Let's see a computer do that!!! "In fact, if you could prove that humans are capable of anything that computers are in principle incapable of, you would be quite famous."--ROb Aw shucks, ok, here are several things that computers are incapable of doing in principle that humans find quite easy to do: Prefer buffalo wings over chicken fingers. Write crummy poetry while believing it is quite good. Tie shoelaces while thinking about something else. Hope. Computers are in principle incapable of prefering, believing, doing something they are not thinking about, thinking itself, or hoping, and these are all things I do fairly often. Oh and one more, If I am not mistaken, computers can't, in principle, rebel.Tim
March 11, 2009
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One other thing - he says his formula showed "approximately 0" FITS for the RSC and OSC sequences, but in the table its exactly 0. And how it could be "approximately" rather than exactly 0 is unclear, given how he's measuring it.JT
March 11, 2009
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KF: Just to review, you provided a link to a table from the Durston paper, presumably in reply to comments by me to the effect that no one had formalized the concept of FCSI. So I do stand corrected in that regard. Also, I need to mention now that I also said no one had offered a proof as to the percentage of strings exhibiting FCSI as has been done for CSI. I am now aware however of that video by Durston where he provides some sort of proof pertaining to FSCI and evolution. However, I have not watched that yet, as I have been focussed on understanding the original paper on measuring FSC, from which the table you provided was taken. And what is of interest to me the most now is Durston's statement to the effect that his measure can distinguish between RSC OSC and FSC (i.e. randomness, necessity, and intelligent design). This is of interest because in the Abel paper (to which Durstons alludes repeatedly) and elsewhere in Durston's own writings are assertions regarding the inability of OSC sequences to exhibit functionality (the implication being that nondeterminstic agents are required to produce FSC.) Durston for his part seems unequivocal in the paper that his formula distinguishes FSC from RSC and OSC:
The results for the array of random sequences and for a 50-mer polyadenosine sequence formed on Montmorillonite show that ?Hf distinguishes FSC from RSC and OSC. The results for the array of random sequences are shown in the second from the last row of Table , and indicate that random sequences, which are an example of RSC, tend to have an FSC of approximately 0 Fits. The results of the highly ordered 50-mer polyadenosine, which is an example of OSC, are shown in the last row of Table , and indicate an FSC of approximately 0 Fits. This is consistent with Abel and Trevors' prediction that neither OSC nor RSC can contain the functional sequence complexity observed in biosequences. [emphasis added]
and then again in the conclusion:
This method successfully distinguishes between FSC and OSC, RSC, thus, distinguishing between order, randomness, and biological function.
These statements seem quite unequivocal, and yet there is no further elaboration in the paper itself. All the rest of the discussion concerns the functional sequences. But upon closer inspection his claims to be able to distinguish RSC and OSC from FSC seem to be blatantly false: Durston measures FSC relative to a "ground state":
The measure of Functional Sequence Complexity, denoted as ?, is defined as the change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti)), or ? = ?H (Xg(ti), Xf(tj)).(6) The resulting unit of measure is defined on the joint data and functionality variable, which we call Fits (or Functional bits).
Earlier Durston says there are two alternatives for a ground state, either a highly ordered ground state or a "null state" that is a ground state that is not highly ordered, but rather completely random. Apparently, it is merely a matter of convenience as to which ground state you choose. The following is his justification for choosing the null state as the ground state for measuring FSC in functional sequences:
for proteins, the data indicates that, although amino acids may naturally form a nonrandom sequence when polymerized in a dilute solution of amino acids [30], actual dipeptide frequencies and single nucleotide frequencies in proteins are closer to random than ordered [31]. For this reason, the ground state for biosequences can be approximated by the null state
However, what is being used as a ground state for a random sequence or ordered sequence? We find that in the footnotes of the table:
All values, except for the OSC example, which was calculated from the constrained ground state required to produce OSC, were computed from the null state
IOW, For both functional sequences and the random sequences the ground state is a random sequence. So this explains why the FSC for randomness is 0 as the ground state its measured relative to is also random. (And furthermore functional uncertainty for a random sequence is independent of the actual sequence, i.e. all random sequences will have the same functional uncertainty.) For the one ordered sequence, the ground state is evidently that same ordered sequence and that is why its FSC is also 0. SO we know now how he measures random sequences and the ordered sequence as both 0 in FSC. Its completely arbitrary. So to compare that to positive values for a functional sequence and then say you've distinguished functional complexity from randomness and order is ludicrous, IMO. At this point I sort of feel like I'm piling on, but the truth is the truth. Note: I said his choice of a ground state was arbitary, but presumably his rationale might be that he was choosing the ground state closest to what he was measuring. So he said he chose randomness as the ground state for a functional sequence because randomness was the closer to a functional sequence than an ordered ground state. And so for measuring FSC in the random string he chose a random string as ground state, and for the ordered string, the same ordered string as a ground state. This is the best I as a laymen could come up with after devoting 2 hours or so to the paper. If I had some glaring oversight or misunderstanding, please some one do point it out.JT
March 11, 2009
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CJYMan:
ROb:
“By the same token, the question of whether a system is capable of foresight is not the same as the question of whether foresight is required to originate the system.”
That is correct and that is the question upon which this debate revolves.
I assume you're referring to the second question, not the first. None of my points in this thread pertain to the second question, so apparently I'm in the wrong debate. WRT the first question, your answer is that computers can have artificial foresight. You seem to differentiate artificial from non-artificial foresight on the basis of consciousness. If this is the ID position, then the onus is on the ID camp to define consciousness and show that computers are in principle incapable of it. That's a pretty tough row to hoe.R0b
March 11, 2009
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KF: I had said I was going to study Durston's paper and the Abel Paper [143], (to which Durston refers to repeatedly) before getting back to you. Durston actually presents his paper as being an extension of the one from Abel and he makes it clear from the outset that he ascribes completely with the former. So I did study the Abel paper in detail last night. There are no proofs as such in it. Rather, Its essentially a challenge, "Here's some assertions we're making - now prove us wrong." And they do make repeated assertions to the effect that law-like determinism cannot create functional information. And it is absolutely clear that the sticking point for them is the determinism aspect of it, that is that a law-like process cannot make "choices". There are repeated reference to agents making "choices". And it is patently clear that they mean "nondeterminstic" agents. I have several quotes from the paper but decided not to list them here. I am still going over the Durston paper. The strongest statement he makes is in the conclusion where he says he has successfully distinguished RSC OSC and FSC via his method. If he meant to imply that he can distinguish something created via a determinsitic process vs. something created by a nondeterminstic agent, that is not actually possible (or else he would be world famous by now). As the table you provided shows, he measured one "ordered" seqeunce, 50-mer polyadenosine, using his method and got a result of 0 fits. He also measured some random sequences and got approximately 0 fits for those as well. However, what I'm not clear on, is whether it was simply a matter of him bringing background knowledge to the table that the ordered sequence and the random sequence had no known function and thus got a 0 via his method. Or, otoh, were these results essentially inevitable because of his own defintions. He states, "The measure of Functional Sequence Complexity, denoted as ?, is defined as the change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti))..." However he previously defines the ground state as being either a random sequence or a higly ordered sequence. So if he's defining FSC as the change from the ground state, then it would seem a foregone conclusion that a random or ordered sequence would show 0 fits.JT
March 11, 2009
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CJYMan [168]: So, have you ever wanted to go to a location that you have never been (obviously are not at in the present)? Did you then pull out a map and plan your present actions based on a future destination? This is a perfect example of teleology in action. So those Monarch butterflies are all saying "Whoohoooo! We're going to Mexico! Ole!" Do we presume they even have conscious awareness of being on a journey?JT
March 11, 2009
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ROb: "We need to be careful not to conflate causation with characterization. The question of whether a system reduces to matter, energy, and physical laws, is not the same as the question of whether it originated by matter, energy, and physical laws." That is exactly the point which I have been trying to make for months and especially since I commented on that post in this blog re: Dembski and Marks paper on active info. ROb: "By the same token, the question of whether a system is capable of foresight is not the same as the question of whether foresight is required to originate the system." That is correct and that is the question upon which this debate revolves. Is there a way to solve it? Can we form a falsifiable hypothesis one way or the other and then test it and potentially gather evidence in favor of it? I believe the answer to that question is "yes" and that ID Theory is one way to do so. In fact, the papers on active info (By Dembski and Marks) are extremely relevant to this question, but I'd rather not go here quite yet. Let's lay some groundwork first. JT and I are presently discussing the groundwork and you are obviously free to join in. Oh, and if you are going to *adamantly* take the opposing position, please provide evidence for it. It is much easier to be a critic (pointing out any little hole) than to defend a position. Scientific discussion after all usually revolve around finding the best of two positions, not merely poking little holes in one position. That is exactly why an ID Theory which attempts to merely poke holes in "evolution" is doomed to failure; and also why I would appreciate you defending the opposing position with evidence -- if indeed you are going to defend the opposing position as "more likely to be true" -- instead of merely poking little holes in everything I state. ROb: "Reading the above quoted paragraph, it seems to me that CJYMan is okay with the concept that a computer is capable of foresight, with the caveat that this capability must be designed into the computer by a foresighted designer. Is that correct, CJYMan, or is a computer’s foresight necessarily not real foresight?" A computer is capable of artificial foresight or the application of previous foresight since they are not yet capable of being aware of future goals yet they can produce some of the same patterns that true foresight realizes by artificially modeling a foresight process -- modeling future possibilities and harnessing law, chance and previous instructional information to accomplish future targets. However, take out the instructional information (which is neither defined by law or chance) and you are left with only law and chance and there is no evidence that these will produce anything resembling a model of foresight. So is there a way to mathematically characterize this instructional information? Is there a way to discover the best cause for this instructional information? For now, let's go back to JT and my discussion to discover the fundamentals of ID Theory. P.S. Of course a key point is that every example of artificial foresight that we are aware of has true foresight in a complete causal chain.CJYman
March 11, 2009
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JT, it seems that we may finally begin to make progress in the discussion. Foresight = Awareness of future goals which do no yet exist (whether those goals are the result of free will or any form of determinism or not) Application of foresight = The generation of those goals by harnessing law and chance to engineer a solution to those goals. So, have you ever wanted to go to a location that you have never been (obviously are not at in the present)? Did you then pull out a map and plan your present actions based on a future destination? This is a perfect example of teleology in action. Remember when I discussed teleology above in comment #136 and how that is what this debate has been revolving around for centuries (determinism and free will being merely secondary questions and not fundamental to the discussion). Are you aware of a future goal (destination) which you have presently not obtained? Do you use the location of this future goal to plan your present course of action? Another example would be: Do you ever have a future goal of getting across a concept to someone? You will notice that at the point of that thought to explain the concept, you have not yet accomplished your goal [to explain the concept]. At this point that is merely a future target which does not yet exist, yet you are aware of it. You can think about it and you can begin to plan to make it a reality, which of course would be your next step -- planning. Ultimately though, you will apply your foresight to harness law and randomness *in the present* to engineer a paragraph or two on this blog in order to hopefully accomplish your goal *in the future* (convincing someone of your position or merely informing someone of your position). Still following? Have you ever done this before? Do you possess foresight?CJYman
March 11, 2009
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CJYMan:
Actually, that assumption is not necessary, since even if foresight can be the result of a program, it has been shown above that program would also need previous foresight in its full causal chain (or else exist eternally). Thus foresight would breed further foresight, CSI, etc etc etc; and *only* law and chance would again not be the best explanation.
We need to be careful not to conflate causation with characterization. The question of whether a system reduces to matter, energy, and physical laws, is not the same as the question of whether it originated by matter, energy, and physical laws. By the same token, the question of whether a system is capable of foresight is not the same as the question of whether foresight is required to originate the system. Reading the above quoted paragraph, it seems to me that CJYMan is okay with the concept that a computer is capable of foresight, with the caveat that this capability must be designed into the computer by a foresighted designer. Is that correct, CJYMan, or is a computer's foresight necessarily not real foresight?R0b
March 10, 2009
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Tim:
Two computers NEVER will.
If you could prove that, you would revolutionize the world of computing theory. In fact, if you could prove that humans are capable of anything that computers are in principle incapable of, you would be quite famous. More succinctly stated, your claim is that humans are not computers in the computing theoretic sense. That is a claim that nobody has been able to validate and is not taken seriously in computing theory. That's one of the reasons that the ID dichotomy of intelligence vs. chance+law is either poorly conceived or poorly stated.
Yes, never is a strong word, but I’ll rely on an application of Turing’s proof over Turing machines.
Unfortunately, the halting problem proof doesn't say that. Computers are routinely used to detect non-halting situations. The halting problem simply says that no computer can detect all conceivable non-halting situations. In fact, it's trivial to write a program that will detect (albeit inefficiently) any non-halting situation for any system with a finite number of possible states, like a chess board. Halting problem issues come into play only if the program needs to achieve a certain efficiency for any finite system of arbitrary size, or if it needs to handle infinite systems. And there is no evidence that humans can do better than computers in this regard.R0b
March 10, 2009
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JYT - if you could just provide your definition of foresight now and disavow MacNeil’s characterization that would be helpful. JYT = CJYManJT
March 10, 2009
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CJYMan: Do I use foresight when reading a map? Depending on what you mean by foresight - yes.JT
March 10, 2009
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CJYMan: This is about as succinct as I can be as to where I stand (quoting myself from [143]): A trivial proof that one program can generate another: I just zipped a program on my hard drive. it reduced the size from 722k to 220k. (This also indicates that functional information is “highly compressible”, BTW). So the unzip program plus a 220K random string not identifiable as anything results in a very complex functional program. You could say that the real program was “already there” in the compressed version. But there is nothing there in that random 220K string to indicate that. So why couldn’t you look out in nature prior to life and find a lot of diffuse and disparate things out there that don’t look anything like life, but were in fact transformed into life. And note that our unzip program did not have any “foresight” either. Of course, you could absolutely note that all those factors out in nature that resulted in life equated to life, just as our zipped file of random data + the unzip program equals our complex functional program. But it shows what should be obvious - that life can emerge via blind physical processes from something that does not look like life at all. And of course, you can absolutely say that this implies something existing at the beginning of the universe that exceeds the power of chance to create. However, that observation does not enlighten us as to the actual naturalistic method of how life actually emerged after the universe began.JT
March 10, 2009
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Or, are you merely stating that everything can be described by a program. If so, I have no contention with that That should have been in quotes.JT
March 10, 2009
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So are you trying to say that everything can be described by randomness/programming, therefore no foresight is necessary in the generation of certain patterns. I am saying everything can be described by randomness/programs, that is randomness/laws. Certainly there has been a random component to it. But the majority of it could not be explained by randomness. Considering Dawkin's weasel, we do of course understand if you have laws to the effect, "If a mutation gets me closer to a sentence about weasels then accept else reject." That randomness can accomplish quite a bit with such a set of laws. If so, then please go ahead and provide some evidence for your position and show me a program guided by no previous foresight — based on only background noise (chance) and law (arbitrary collection of laws with no consideration for future results) — and let me know when CSI is produced. At some point, Dembski or someone started address the notion of "arbitarily chosen laws" and the inability of such to accomplish anything. Such a characterization has muddied the waters. I don't think "arbitrary" laws will accomplish anything any more than pure randomness will. I don't think anyone would ever affirm that "arbitary" anything could be expected to accomplish something specific. But I don't think the laws had to be "chosen" as such. (I know you didn't use the term "chosen" yourself here, but someone did in a previous exchange with me, so I think that's the standard format for that phrase. If the implication is that someone has to "choose" the correct laws that's imposing on the discussion some metaphysical assumptions through rhetoric. Or, are you merely stating that everything can be described by a program. If so, I have no contention with that I apologize to whatever extent we've been arguing past each other (if that is the case).JT
March 10, 2009
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JYT - if you could just provide your definition of foresight now and disavow MacNeil's characterization that would be helpful.JT
March 10, 2009
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CJYMan [154]: "The problem is that, sure, randomness can be summoned to explain away anything … even law like behavior. The question is “what is the best explanation?” You are completely misunderstanding and mischaracterizing my point about randomness. I said there were classes of strings that would be extremely unlikely to occur by randomness. Actually I have said randomness is not an explanation. I have said many times the explanation is LAW (not "intelligence", not randomness either).JT
March 10, 2009
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JT: Trevors and Abel were the ones who identified the 3-D contrasts OSC, RSC, FSC. Durston is lead author on tthe paper in which the measurements of FSC were published. GEM of TKIkairosfocus
March 10, 2009
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CJYMan [155]: I am sorry if I missed your defintion of foresight- why not just repeat it, and specifically disavow Allan_Macneil's characterization.JT
March 10, 2009
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CJYMan: If I can attempt to close the loop here - So if foresight (at least in some transcendent sense) is not necessary to generate any string, what are we left with? Namely the following: Conservation of Information - at least how I would use that term. I don't know how Dembski specifically defines that, But obviously if you have some process F(X) to generate string Y, then F(X) cannot be less complex than Y, and F(X) equates to Y which means you're just pushing back what needs to be explained. If this was already your understanding, then I do sincerely apologize for belaboring the obvious. But most ID'ers do seem to have an assumption about intelligence transcending chance and law or some sort of notion of transcendent conscious foresight being necessary to create FCSI.JT
March 10, 2009
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P.S. JT, I have already defined "foresight" for you a few times, yet you continued to ignore it. Why should I think that things will now change?CJYman
March 10, 2009
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JT, your comments re: programs. Are they merely another way of you stating what you states earlier when you stated that ... "JT: “There is no binary string that cannot be the result of pure randomness either.” ... and I responded with ... "Technically … you’re right. Practically … you’re wrong. The problem is that, sure, randomness can be summoned to explain away anything … even law like behavior. The question is “what is the best explanation?” In fact, if we took your premise here and ran with it then science, as the discovery of laws of nature would not exist as there would be no concept of law. It could just all be explained by chaotic randomness. “Planets orbiting the sun?” … easily computable as a random string; nothing to see here. Randomness did it. No true correlation to a fundamental principle at the foundation of our universe. “Chemicals bonding regularly?” … easily computable as a random string; nothing to see here. Randomness did it." So are you trying to say that everything can be described by randomness/programming, therefore no foresight is necessary in the generation of certain patterns. If so, then please go ahead and provide some evidence for your position and show me a program guided by no previous foresight -- based on only background noise (chance) and law (arbitrary collection of laws with no consideration for future results) -- and let me know when CSI is produced. Or, are you merely stating that everything can be described by a program. If so, I have no contention with that and I don't know quite enough about QM to understand the implications of many of its possible interpretations. As I have shown, it makes no difference, so are you going to answer the question or are we going to agree to disagree and not continue to broaden both of our understanding of the fundamentals of ID Theory?CJYman
March 10, 2009
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CJYMan, my point is there are multitudinous and disparate methods for generating any string (whether it contains FCSI or not). How is foresight necessary for any string (if foresight means something specific).JT
March 10, 2009
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KF, I want to review the Durston paper and Abels and Trevor paper in much greater detail today before getting back to you. I will stand by my previous comment that Durston has a qualititative understanding of order (revolving around the idea of something being generated by a small program) and his paper was not intended to further clarify this notion of order.JT
March 10, 2009
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JT, So re: the first part of your last comment, do we just agree to disagree or are you going to answer the question and continue the discussion to discover if ID Theory has merit and/or is scientific? JT: "For any binary string (one containing functional info or not) there are an infinite number of programs that will output it" Sure. Your point is ... ? JT: "By program I would mean “program-input” meaning that crucial aspects of the solution could of course come from what is fed into the process. But there are an unending array of methods by which some binary string could be arrived at." Uhuh ... and ...CJYman
March 10, 2009
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By program I would mean “program-input” meaning that crucial aspects of the solution could of course come from what is fed into the process. But just to be clear for any given binary string there are an infinite number of programs that receive no input that can output it.JT
March 10, 2009
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JYT Since you may have many misconceptions of ID Theory You could of course always enumerate succinctly what you percieve to be my misconceptions of I.D. and provides quotes of mine as proof. “foresight is foresight whether it is determined to use its foresight in a certain way or not; whether it is determined to exist or not. We experience and use our foresight every day, thus we know it exists whether we have free will or not; whether the universe has a deterministic structure or not. Have you ever used a map and your foresight to plan a route to a future destination you wished to travel to?” As I stated, I can’t continue this discussion until you answer that very simple question, since it is the type of question which begins the foray into ID Theory." As I mentioned Allan_MacNeil (at TT) gave a description of foresight thaty seemed pretty bizarre:
Furthermore, it seems clear from previous discussions in this forum that IDers assume that information can be "foresighted"; that is, it can somehow anticipate future outcomes, not by "induction" from the past but by some kind of "deduction" from the future. ... whether any form of information transfer can be genuinely "foresighted" (i.e. can be modified by events that have not yet happened, rather than simply predicting future events based on events that have happened in the past).
As I also mentioned I was incredulous that ID'ers actually thought that, but then on Sunday in reviewing your comments it slowly dawned on me that you probably did think that. If by foresight you have additional baggage associated with it about conscious awareness of future states of reality or some such, and saying that that's necessary to create complex functional info I would disagree with that. And if you're just saying you think its possible for a determinstic mechanism to have this type of transcendent foresight, but that sort of transcendent foresight is still necessary, I disagree with that as well. For any binary string (one containing functional info or not) there are an infinite number of programs that will output it. By program I would mean "program-input" meaning that crucial aspects of the solution could of course come from what is fed into the process. But there are an unending array of methods by which some binary string could be arrived at.JT
March 10, 2009
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One warning to you, JT. My version of ID Theory may be slightly different from the majority of ID proponents. However, that is the beauty of science -- many ideas competing and the best one winning. However, all ID hypothesis are the same in that they answer in the affirmative that the effects of intelligence are detectable and are not best explained by either chance or law. That is ... they agree on the fundamentals, which is what I wish to begin to discuss with you.CJYman
March 10, 2009
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JT, actually reading through my last comment, I guess that *would* mean that I am implying that you are splitting hairs over the issue of determinism vs. non-determinism. But, as I said, that is not to say that it is not an interesting question that may arise as a secondary issue; I merely have shown that it is not fundamental to ID Theory. Since you may have many misconceptions of ID Theory, I have decided to try to explain a non-strawman variation [understood by myself, an ID proponent] to you from the ground up. This has been started in my comments #136-138 as I just stated in my last comment.CJYman
March 10, 2009
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