Uncommon Descent Serving The Intelligent Design Community

Aurelio Smith’s Analysis of Active Information

Categories
Intelligent Design
Share
Facebook
Twitter/X
LinkedIn
Flipboard
Print
Email

Recently, Aurelio Smith had a guest publication here at Uncommon Descent entitled Signal to Noise: A Critical Analysis of Active Information. Most of the post is taken up by a recounting of the history of active information. He also quotes the criticisms of Felsentein and English which have responded to at Evolution News and Views: These Critics of Intelligent Design Agree with Us More Than They Seem to Realize. Smith then does spend a few paragraphs developing his own objections to active information.

Smith argues that viewing evolution as a search is incorrect, because organisms/individuals aren’t searching, they are being acted upon by the environment:

Individual organisms or populations are not searching for optimal solutions to the task of survival. Organisms are passive in the process, merely affording themselves of the opportunity that existing and new niche environments provide. If anything is designing, it is the environment. I could suggest an anthropomorphism: the environment and its effects on the change in allele frequency are “a voice in the sky” whispering “warmer” or “colder”.

When we say search we simply mean a process that can be modeled as a probability distribution. Smith’s concern is irrelevent to that question. However, even if we are trying to model evolution as a optimization or solution-search problem Smith’s objection doesn’t make any sense. The objects of a search are always passive in the search. Objecting that the organisms aren’t searching is akin to objecting that easter eggs don’t find themselves. That’s not how any kind of search works. All search is the environment acting on the objects in the search.

Rather than demonstrating the “active information” in Dawkins’ Weasel program, which Dawkins freely confirmed is a poor model for evolution with its targeted search, would DEM like to look at Wright’s paper for a more realistic evolutionary model?

This is a rather strange comment. Smith quoted our discussion of Avida previously. But here he implies that we’ve only ever discussed Dawkin’s Weasel program. We’ve discussed Avida, Ev, Steiner Trees, and Metabiology. True, we haven’t looked at Wright’s paper, but its completely unreasonable to suggest that we’ve only discussed Dawkin’s “poor model.”

Secondly, “fitness landscape” models are not accurate representations of the chaotic, fluid, interactive nature of the real environment . The environment is a kaleidoscope of constant change. Fitness peaks can erode and erupt.

It is true that a static fitness landscape is an insufficient model for biology. That is why our work on conservation of information does not assume a static fitness landscape. Our model is deliberately general enough to handle any kind of feedback mechanism.

While I’m grateful for Smith taking the time to writeup his discussion, I find it very confused. The objections he raises don’t make any sense.

Comments
Can you give an example of mu and mu-bar?
Let's take the set {A,B} Let say that mu = 2/3 A, 1/3 B. The simplest way to understand mu_bar, it to think of it as a uniform distribution over the set {1,2,3}. Then we compose it with the mapping {1,2} -> A, {3} -> B.
But so what? How do you jump from this to concluding anything about the ontological status or probabilities of the two distributions?
We're not claiming anything about ontological statuses. What we are claiming is that whatever process produced a successful search, must itself have a pdf biased towards indirectly producing the targetWinston Ewert
May 2, 2015
May
05
May
2
02
2015
10:17 AM
10
10
17
AM
PST
Joe:
Until you know the effects of the new organism X well into the future, you cannot release it into the environment.
Wow. Keep them straw man arguments coming, though. They are entertaining.
I have been thinking about how to implement ID. You have issues with my concerns. If you're better at this than I, show me how to use ID to introduce an organism into an environment. Give me details. I claim it's harder than you think.Carpathian
May 2, 2015
May
05
May
2
02
2015
10:04 AM
10
10
04
AM
PST
fifthmonarchyman: providing examples and evidence for his claim. Be happy to. Thanks for asking. See Krupp & Taylor, Social evolution in the shadow of asymmetrical relatedness, Proceedings of the Royal Society B: Biological Sciences 2015. For that matter, so is Word Mutagenation.Zachriel
May 2, 2015
May
05
May
2
02
2015
09:38 AM
9
09
38
AM
PST
Carpathian:
In order for ID to work, there is a requirement that the designer be able to see the future and commit almost no errors.
That doesn't follow from anything.
Until you know the effects of the new organism X well into the future, you cannot release it into the environment.
Wow. Keep them straw man arguments coming, though. They are entertaining.
I will model both ID and evolution and see which is a more powerful method for generating successful body plans.
What does that even mean besides proving you have no clue what is being debated? Evolution via intelligent design is by far more powerful than unguided evolution. Try developing antennae without the specifications of what is required programmed in.Joe
May 2, 2015
May
05
May
2
02
2015
09:36 AM
9
09
36
AM
PST
I have pointed to the antecedents for the descriptivce summary in Orgel, Wicken, Dembski and Meyer from 85 on above: https://uncommondescent.com.....ent-562213 These will handily meet the more serious than a blog criterion.
You really think a comment on a blog that quotes other people and calls them idea-roots for FSCO/I qualifies as a serious presentation of the idea of FSCO/I?Winston Ewert
May 2, 2015
May
05
May
2
02
2015
09:24 AM
9
09
24
AM
PST
KF the cardinality of the set of all possible searches (as defined by DEM) is infinite (see #100 above for a small example). But, setting that aside, you are assuming a uniform probability across the set of all possible searches. This is clearly not the case for evolution (and many other real world cases). Searches that involve non-viable steps are quickly terminated. There is a strong relationship between possible searches and the "target" which is a viable organism which has viable offspring.Mark Frank
May 2, 2015
May
05
May
2
02
2015
09:23 AM
9
09
23
AM
PST
kairosfocus: I have given this a lot of thought and ID is tougher than it looks, not from the perspective of designing organism X but rather what role X should play in it's environment. X's effect on other creatures and plant life in an environment could lead to extinction of other species, both prey and predator, as well as a change in the food chain. Until you know the effects of the new organism X well into the future, you cannot release it into the environment.Carpathian
May 2, 2015
May
05
May
2
02
2015
09:22 AM
9
09
22
AM
PST
bornagain77:
i.e. “It just happened for no particular reason whatsoever’ is a science defeater!
I agree!
What separates the science of ID from the pseudo-science of neo-Darwinism is that ID can be rigorously falsified by experiment, and neo-Darwinism cannot.
An experiment is what I intend to do. I will model both ID and evolution and see which is a more powerful method for generating successful body plans. The problem with ID is that I can see the limitations in anyone actually being able to do it, other of course than someone who can accurately see the future. As far as dismissing evolution, I believe that evolving even the simplest self-replicating code would qualify as proof that evolution could be a viable mechanism for biology also.Carpathian
May 2, 2015
May
05
May
2
02
2015
09:14 AM
9
09
14
AM
PST
Carp, in case you do not know, neo-Darwinism is itself based on (bad) Theological premises not mathematical premises. Clean up your own back yard first and then we can talk. What separates the science of ID from the pseudo-science of neo-Darwinism is that ID can be rigorously falsified by experiment, and neo-Darwinism cannot. In fact, ID invites rigorous experimentation to try to falsify its primary claim that unguided material processes cannot produce non-trivial functional information/complexity, and that only Intelligence can (Abel; Behe). Moreover, science cannot be conducted unless teleology is presupposed on some ultimate level. Insisting, as materialists/atheists do, that there is no ultimate reason why anything happens defeats the purpose of doing science in the first place of trying to find the reason why anything happens. i.e. "It just happened for no particular reason whatsoever' is a science defeater!bornagain77
May 2, 2015
May
05
May
2
02
2015
08:58 AM
8
08
58
AM
PST
MF, observe the context of blind, needle in haystack search, and the onward context that any given search will typically be utterly uncorrelated to where targets Ti may be found, the individual searches being of course samples of W and members of the set of subsets of W. IT is patent that it will be hard for a particular direct search to conveniently deposit us on a target Ti or close enough that it is easy to thereafter find it on an incremental narrow scope of search. Thus, we see that the search for such a golden search will put us into a higher order search for search that will come from the power set. Which will hold cardinality 2^W for a set of large cardinality W, starting at 10^150 - 10^301, the reasonable threshold for the same FSCO/I you would dismiss, that turns out to be very directly relevant to blind needle in haystack search. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
08:58 AM
8
08
58
AM
PST
Carpathian:
In order for ID to work, there is a requirement that the designer be able to see the future and commit almost no errors.
Not at all. First, all designers anticipate future possibilities, we look to goals. Second, a world of technology all around us shows that initial designs can be incrementally developed to adequate performance and reliability to be good enough for purpose. Perfection is not required. Just a sophisticated technical base. The PC you are reading this on is good enough as a case in point. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
08:51 AM
8
08
51
AM
PST
WE  
See the top of page 58. We begin with any arbitrary distribution mu on omega. This is projected, as discussed in section 5, to a distribution mu-bar on M(omega). (You could as easily go in the other direction, and start with a distribution mu-bar on M(omega) and produce a distribution M on omega). That is, you can pick any arbitrary distribution that you deem the natural distribution. We are not assuming anything about the distribution, and certainly not that it is uniform. Note that this means that you could decide that the natural distribution of the universe places a high probability on complex life. The result of conservation of information has no quarrel with you if you take that stance.
Thanks for going to this effort. It is both enlightening and frustrating.  I guess I am confused by what you mean by “project” or at least its implications. As far as I know a projection is just a type of mapping from one set to another. So you can map a pdf on omega to a subset of M(omega). But so what? How do you jump from this to concluding anything about the ontological status or probabilities of the two distributions? It would help to have a concrete example. Suppose omega comprises just two members A and B. Then as I understand it M(omega) is the set of all possible pdfs on omega and is defined by all the possible values of P( A) i.e. all the real numbers between 0 and 1. Can you give an example of mu and mu-bar?Mark Frank
May 2, 2015
May
05
May
2
02
2015
08:51 AM
8
08
51
AM
PST
MF, pardon directness but you are simply being personally dismissive in a context where you were specifically corrected by direct citation on the contextual meaning of the reference to probability distributions. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
08:46 AM
8
08
46
AM
PST
MF (attn WE): I have pointed to the antecedents for the descriptivce summary in Orgel, Wicken, Dembski and Meyer from 85 on above: https://uncommondescent.com/intelligent-design/aurelio-smiths-analysis-of-active-information/#comment-562213 These will handily meet the more serious than a blog criterion. After all, all it is that I have done and others too, is to create an acronym for a stock descriptive phrase for functionally specific forms of complex specified information. And in the case of Orgel and Wicken, that was the original context. Dembski used a generalisation to speak of specified complexity in general. KF PS: Onlookers, you will be able to judge the [want of] seriousness of onward objectors if they refuse to discuss FSCO/I on grounds that it is not taken up by "senior" ID persons.kairosfocus
May 2, 2015
May
05
May
2
02
2015
08:44 AM
8
08
44
AM
PST
bornagain77:
Carp, I believe God, who is omniscient and who created/creates time itself, is the Designer of the universe and of all life in it. Thus ‘far off targets’ in the future are child’s play for Him in His infinite knowledge since even time itself belongs to Him.
Yes. Information is the key here. In order for ID to work, there is a requirement that the designer be able to see the future and commit almost no errors. This is a problem for the ID movement though in that ID cannot be debated on a scientific basis if this is true. If the claim is that no one but God can possibly engage in ID, we need faith to believe in ID. We have then moved into a religious debate not a scientific one.Carpathian
May 2, 2015
May
05
May
2
02
2015
08:39 AM
8
08
39
AM
PST
WE:
this means that you could decide that the natural distribution of the universe places a high probability on complex life. The result of conservation of information has no quarrel with you if you take that stance.
Pretty serious fine-tuning and front loading! KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
08:37 AM
8
08
37
AM
PST
Mark Frank, All you and yours have done is prove that unguided evolution doesn't have squat. Your entire position is nothing but bald declarations and attacks on anyone who questions them. It is very telling when all you have to do to stop ID is to step up and produce support for the claims of your position and you choose to act differently. Typical but still pathetic.Joe
May 2, 2015
May
05
May
2
02
2015
08:28 AM
8
08
28
AM
PST
KF #91 All youp have shown is that you don't understand DEM's paper - much less the problems with it. But it is not worth pursuing this any more.Mark Frank
May 2, 2015
May
05
May
2
02
2015
08:14 AM
8
08
14
AM
PST
I may not like your model. But what use it is even to you?
I elaborated on the conclusions we draw from our model over at Evolution News and Views. I don't feel the need to repeat myself here.
And I am struggling to see where those assumptions are articulated (although I suspect you are assuming that the pdf of pdfs is uniform between 0 and 1).
See the top of page 58. We begin with any arbitrary distribution mu on omega. This is projected, as discussed in section 5, to a distribution mu-bar on M(omega). (You could as easily go in the other direction, and start with a distribution mu-bar on M(omega) and produce a distribution M on omega). That is, you can pick any arbitrary distribution that you deem the natural distribution. We are not assuming anything about the distribution, and certainly not that it is uniform. Note that this means that you could decide that the natural distribution of the universe places a high probability on complex life. The result of conservation of information has no quarrel with you if you take that stance.
The fact that any so-called search can be reduced to a probability distribution does not mean that any stochastic process that can be reduced to a probability distribution is a “search.”
That's not remotely what I've said. I'm not saying that because both searches and stochastic processes can be reduced to a probability distribution they are the same. That would indeed be incorrect. What I've said is that our purposes we define a search to be a process that can be reduced to a probability distribution. So all processes no matter how insane that can reduced to a probability distribution are searches for the purpose of COI. That is simply a matter of how we've chosen to define our terms.
Is FSCO/I something you’ve heard of? If you have, do you (and as spokesman for DEM) endorse it?
I've seen posts about it. I'm not inclined to take it seriously until I see it published some place more serious then a blog.Winston Ewert
May 2, 2015
May
05
May
2
02
2015
08:05 AM
8
08
05
AM
PST
Zac says, Not all evolutionary algorithms search for specific targets. I say, Not all ID critics are incapable of having a genuine discussion of the issues. Zac again demonstrates that he is not one of the honest critics by not providing examples and evidence for his claim. ;-) peace PS That is why he is ignored so oftenfifthmonarchyman
May 2, 2015
May
05
May
2
02
2015
07:59 AM
7
07
59
AM
PST
MF, I have sufficiently shown (i) that searches per whatever means applied will impose some degree of bias from zero up to absolute, in selection, which gives the distribution that Marks, Dembski and Ewert speak of (per citation), (ii) That each search will pick a subset of the set W, so that a blind population of searches will come from the set of subsets. By necessity of what a sample is, what a subset is, and what a cluster of actual samples will be as a result. This addresses your intended correction and shows that it is itself in need of correction. As, that (ii) is so is actually independent of the fact that (i) will be so. Both are true and both carry some relationship but I does not overturn ii. And in the sense that the authors wrote, searches do organically connect to distributions on the set W. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
07:42 AM
7
07
42
AM
PST
#89 KF You are confusing the result of the search with the search. Two completely different pdfs may end up with the same results. DEM defines a search as a pdf. Therefore a search is not the same as the subset of W which results from the search.Mark Frank
May 2, 2015
May
05
May
2
02
2015
06:21 AM
6
06
21
AM
PST
MF, you first need to read the already given context of that little clip, the opening paragraphs of the MDE 2013 paper:
All but the most trivial searches are needle-in-the-haystack problems. Yet many searches successfully locate needles in haystacks. How is this possible? A success-ful search locates a target in a manageable number of steps. According to conserva-tion of information, nontrivial searches can be successful only by drawing on existing external information, outputting no more information than was inputted [1]. In previous work, we made assumptions that limited the generality of conservation of information, such as assuming that the baseline against which search perfor-mance is evaluated must be a uniform probability distribution or that any query of the search space yields full knowledge of whether the candidate queried is inside or outside the target. In this paper, we remove such constraints and show that | conservation of information holds quite generally. We continue to assume that tar-gets are fixed. Search for fuzzy and moveable targets will be the topic of future research by the Evolutionary Informatics Lab. In generalizing conservation of information, we first generalize what we mean by targeted search. The first three sections of this paper therefore develop a general approach to targeted search. The upshot of this approach is that any search may be represented as a probability distribution on the space being searched. Readers who are prepared to accept that searches may be represented in this way can skip to section 4 and regard the first three sections as stage-setting. Nonetheless, we sug-gest that readers study these first three sections, if only to appreciate the full gen-erality of the approach to search we are proposing and also to understand why attempts to circumvent conservation of information via certain types of searches fail. Indeed, as we shall see, such attempts to bypass conservation of information look to searches that fall under the general approach outlined here; moreover, conservation of information, as formalized here, applies to all these cases . . .
Secondly,the substantial matter is that a search samples from the set W with some distribution of probabilities regarding likelihood of any particular member xi being picked up, i.e. a probability distribution function across the set of members xi constituting W. Any given search then kicks out a collection of members, which per definition is a subset of W. Therefore the space of all possible samples -- and thus subsets -- of W is the space from which any given search MUST come. Ranging from {} to W itself (a 100% census). of course the particular samples picked will be chosen based on the specifics of sampling, which imposes a further distribution, pointing onward to a higher yet order search. Therefore it is entirely appropriate to point out that searches will come from a much higher scaled set, 2^W in cardinality. Which renders immediately highly plausible the finding of M, D & E that such a search for a good search imposes a cumulative search burden that is at least as hard as a null search based on some natural sampling of the original W will. Which as I argued just now: https://uncommondescent.com/intelligent-design/id-foundations/on-active-information-search-islands-of-function-and-fscoi/ . . . leads directly back to the blind needle in haystack search challenge imposed by the requisites of FSCO/I. Active info is a bridge coming from designers that makes searches feasible. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
05:44 AM
5
05
44
AM
PST
PPS: Meyer, in his reply to Falk's critique of Signature in the cell: ___________________ http://www.signatureinthecell.com/responses/response-to-darrel-falk.php >> . . . [[W]e now have a wealth of experience showing that what I call specified or functional information (especially if encoded in digital form) does not arise from purely physical or chemical antecedents[[--> i.e. by blind, undirected forces of chance and necessity]. Indeed, the ribozyme engineering and pre-biotic simulation experiments that Professor Falk commends to my attention actually lend additional inductive support to this generalization. On the other hand, we do know of a cause—a type of cause—that has demonstrated the power to produce functionally-specified information. That cause is intelligence or conscious rational deliberation. As the pioneering information theorist Henry Quastler once observed, “the creation of information is habitually associated with conscious activity.” And, of course, he was right. Whenever we find information—whether embedded in a radio signal, carved in a stone monument, written in a book or etched on a magnetic disc—and we trace it back to its source, invariably we come to mind, not merely a material process. Thus, the discovery of functionally specified, digitally encoded information along the spine of DNA, provides compelling positive evidence of the activity of a prior designing intelligence. This conclusion is not based upon what we don’t know. It is based upon what we do know from our uniform experience about the cause and effect structure of the world—specifically, what we know about what does, and does not, have the power to produce large amounts of specified information . . . . >> __________________ Meyer here speaks directly to functionally specific complex information in digitally coded form, but with direct application to wider FSCO/I. I trust this isolate, tag and dismiss rhetorical gambit will now be retired. At least, by those interested in addressing substance rather than techniques of caricature and dismissal.kairosfocus
May 2, 2015
May
05
May
2
02
2015
05:30 AM
5
05
30
AM
PST
PS: Dembski, NFL: >> p. 148:“The great myth of contemporary evolutionary biology is that the information needed to explain complex biological structures can be purchased without intelligence. My aim throughout this book is to dispel that myth . . . . Eigen and his colleagues must have something else in mind besides information simpliciter when they describe the origin of information as the central problem of biology. I submit that what they have in mind is specified complexity [[cf. here below], or what equivalently we have been calling in this Chapter Complex Specified information or CSI . . . . Biological specification always refers to function. An organism is a functional system comprising many functional subsystems. . . . In virtue of their function [[a living organism's subsystems] embody patterns that are objectively given and can be identified independently of the systems that embody them. Hence these systems are specified in the sense required by the complexity-specificity criterion . . . the specification can be cashed out in any number of ways [[through observing the requisites of functional organisation within the cell, or in organs and tissues or at the level of the organism as a whole. Dembski cites: Wouters, p. 148: "globally in terms of the viability of whole organisms," Behe, p. 148: "minimal function of biochemical systems," Dawkins, pp. 148 - 9: "Complicated things have some quality, specifiable in advance, that is highly unlikely to have been acquired by ran-| dom chance alone. In the case of living things, the quality that is specified in advance is . . . the ability to propagate genes in reproduction." On p. 149, he roughly cites Orgel's famous remark from 1973, which exactly cited reads:
In brief, living organisms are distinguished by their specified complexity. Crystals are usually taken as the prototypes of simple well-specified structures, because they consist of a very large number of identical molecules packed together in a uniform way. Lumps of granite or random mixtures of polymers are examples of structures that are complex but not specified. The crystals fail to qualify as living because they lack complexity; the mixtures of polymers fail to qualify because they lack specificity . . .
And, p. 149, he highlights Paul Davis in The Fifth Miracle: "Living organisms are mysterious not for their complexity per se, but for their tightly specified complexity."] . . .” p. 144: [[Specified complexity can be more formally defined:] “. . . since a universal probability bound of 1 [[chance] in 10^150 corresponds to a universal complexity bound of 500 bits of information, [[the cluster] (T, E) constitutes CSI because T [[ effectively the target hot zone in the field of possibilities] subsumes E [[ effectively the observed event from that field], T is detachable from E, and and T measures at least 500 bits of information . . . ” >>kairosfocus
May 2, 2015
May
05
May
2
02
2015
05:22 AM
5
05
22
AM
PST
fifthmonarchyman: Premise two) Evolutionary Algorithms are searching for specific targets. Not all evolutionary algorithms search for specific targets.Zachriel
May 2, 2015
May
05
May
2
02
2015
05:22 AM
5
05
22
AM
PST
AS, Isn't it time you paid attention to the idea history instead of trying to tag and dismiss? Let me again cite to you the roots in Orgel, Wicken and co, for the descriptive focus on the FUNCTIONALLY specified subset of CSI. Which on pp 148/9 of NFL, Dembski highlights as the aspect relevant to biological systems: ______________ http://iose-gen.blogspot.com/2010/06/introduction-and-summary.html#fsci_sig >> The observation-based principle that complex, functionally specific information/ organisation is arguably a reliable marker of intelligence and the related point that we can therefore use this concept to scientifically study intelligent causes will play a crucial role in that survey. For, routinely, we observe that such functionally specific complex information and related organisation come-- directly [[drawing a complex circuit diagram by hand] or indirectly [[a computer generated speech (or, perhaps: talking in one's sleep)] -- from intelligence. In a classic 1979 comment, well known origin of life theorist J S Wicken wrote:
‘Organized’ systems are to be carefully distinguished from ‘ordered’ systems. Neither kind of system is ‘random,’ but whereas ordered systems are generated according to simple algorithms [[i.e. “simple” force laws acting on objects starting from arbitrary and common- place initial conditions] and therefore lack complexity, organized systems must be assembled element by element according to an [[originally . . . ] external ‘wiring diagram’ with a high information content . . . Organization, then, is functional complexity and carries information. It is non-random by design or by selection, rather than by the a priori necessity of crystallographic ‘order.’ [[“The Generation of Complexity in Evolution: A Thermodynamic and Information-Theoretical Discussion,” Journal of Theoretical Biology, 77 (April 1979): p. 353, of pp. 349-65. (Emphases and notes added. Nb: “originally” is added to highlight that for self-replicating systems, the blue print can be built-in.)]
The idea-roots of the term "functionally specific complex information" [FSCI] are plain: "Organization, then, is functional[[ly specific] complexity and carries information." Similarly, as early as 1973, Leslie Orgel, reflecting on Origin of Life, noted:
. . . In brief, living organisms [--> a functional context] are distinguished by their specified complexity. Crystals are usually taken as the prototypes of simple well-specified structures, because they consist of a very large number of identical molecules packed together in a uniform way. Lumps of granite or random mixtures of polymers are examples of structures that are complex but not specified. The crystals fail to qualify as living because they lack complexity; the mixtures of polymers fail to qualify because they lack specificity . . . . [HT, Mung, fr. p. 190 & 196:] These vague idea can be made more precise by introducing the idea of information. Roughly speaking, the information content of a structure is the minimum number of instructions needed to specify the structure. [--> this is of course equivalent to the string of yes/no questions required to specify the relevant "wiring diagram" for the set of functional states, T, in the much larger space of possible clumped or scattered configurations, W, as Dembski would go on to define in NFL in 2002, also cf here, here and here (with here on self-moved agents as designing causes).] One can see intuitively that many instructions are needed to specify a complex structure. [--> so if the q's to be answered are Y/N, the chain length is an information measure that indicates complexity in bits . . . ] On the other hand a simple repeating structure can be specified in rather few instructions. [--> do once and repeat over and over in a loop . . . ] Complex but random structures, by definition, need hardly be specified at all . . . . Paley was right to emphasize the need for special explanations of the existence of objects with high information content, for they cannot be formed in nonevolutionary, inorganic processes. [The Origins of Life (John Wiley, 1973), p. 189, p. 190, p. 196. Of course, that immediately highlights OOL, where the required self-replicating entity is part of what has to be explained (cf. Paley here), a notorious conundrum for advocates of evolutionary materialism; one, that has led to mutual ruin documented by Shapiro and Orgel between metabolism first and genes first schools of thought, cf here. Behe would go on to point out that irreducibly complex structures are not credibly formed by incremental evolutionary processes and Menuge et al would bring up serious issues for the suggested exaptation alternative, cf. his challenges C1 - 5 in the just linked. Finally, Dembski highlights that CSI comes in deeply isolated islands T in much larger configuration spaces W, for biological systems functional islands. That puts up serious questions for origin of dozens of body plans reasonably requiring some 10 - 100+ mn bases of fresh genetic information to account for cell types, tissues, organs and multiple coherently integrated systems. Wicken's remarks a few years later as already were cited now take on fuller force in light of the further points from Orgel at pp. 190 and 196 . . . ]
Thus, the concept of complex specified information -- especially in the form functionally specific complex organisation and associated information [FSCO/I] -- is NOT a creation of design thinkers like William Dembski. Instead, it comes from the natural progress and conceptual challenges faced by origin of life researchers, by the end of the 1970's. Indeed, by 1982, the famous, Nobel-equivalent prize winning Astrophysicist (and life-long agnostic) Sir Fred Hoyle, went on quite plain public record in an Omni Lecture:
Once we see that life is cosmic it is sensible to suppose that intelligence is cosmic. Now problems of order, such as the sequences of amino acids in the chains which constitute the enzymes and other proteins, are precisely the problems that become easy once a directed intelligence enters the picture, as was recognised long ago by James Clerk Maxwell in his invention of what is known in physics as the Maxwell demon. The difference between an intelligent ordering, whether of words, fruit boxes, amino acids, or the Rubik cube, and merely random shufflings can be fantastically large, even as large as a number that would fill the whole volume of Shakespeare’s plays with its zeros. So if one proceeds directly and straightforwardly in this matter, without being deflected by a fear of incurring the wrath of scientific opinion, one arrives at the conclusion that biomaterials with their amazing measure or order must be the outcome of intelligent design. No other possibility I have been able to think of in pondering this issue over quite a long time seems to me to have anything like as high a possibility of being true.” [[Evolution from Space (The Omni Lecture[ --> Jan 12th 1982]), Enslow Publishers, 1982, pg. 28.]
So, we first see that by the turn of the 1980's, scientists concerned with origin of life and related cosmology recognised that the information-rich organisation of life forms was distinct from simple order and required accurate description and appropriate explanation. To meet those challenges, they identified something special about living forms, CSI and/or FSCO/I. As they did so, they noted that the associated "wiring diagram" based functionality is information-rich, and traces to what Hoyle already was willing to call "intelligent design," and Wicken termed "design or selection." By this last, of course, Wicken plainly hoped to include natural selection. But the key challenge soon surfaces: what happens if the space to be searched and selected from is so large that islands of functional organisation are hopelessly isolated relative to blind search resources? For, under such "infinite monkey" circumstances , searches based on random walks from arbitrary initial configurations will be maximally unlikely to find such isolated islands of function . . . >> _____________ Let us see if you will now respond to substance instead of trying to isolate and target personalities. Which, I point out to you is enabling behaviour in the context of the existence of the ever present lunatic fringe. As well as the tactical recommendation of one certain SDA in his notorious rules for radicals. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
05:18 AM
5
05
18
AM
PST
#80 KF Edited (pressed enter too early)
The set of searches on W is a set of the subsets of W.
This is wrong. Using DEM's definition of a search - the set of searches on W is all possible pdfs over W. This is quite different from from the set of subsets. Among other things it is infinite in size while the set of subsets of a finite set is itself finite.Mark Frank
May 2, 2015
May
05
May
2
02
2015
04:28 AM
4
04
28
AM
PST
DiEb says, In your paper “A General Theory of Information Cost Incurred by Successful Search”, you don’t use the terms model or modeling, not even once. I say, I find the contrast between model and search to be interesting. It illustrates the fallacy of equating software like Avida to other actual scientific models. from here: http://en.wikipedia.org/wiki/Scientific_modelling quote: A scientific model seeks to represent empirical objects, phenomena, and physical processes in a logical and objective way. All models are in simulacra, that is, simplified reflections of reality, end quote: With this description we can construct the following syllogism. Axiom) models reflect reality. Premise one) Evolution is not searching for any specific target other than survival. Premise two) Evolutionary Algorithms are searching for specific targets. Conclusion) Evolutionary Algorithms are not "models" of Evolution. peacefifthmonarchyman
May 2, 2015
May
05
May
2
02
2015
04:17 AM
4
04
17
AM
PST
MF, kindly cf the just above to DiEb. A blind search of a space dominated by non-function and with small targets with inadequate time and atomic resources to sample enough of the v. large space W to make detection of an island Ti likely, is a challenge. The set of searches on W is a set of the subsets of W. The cardinality of the onward space for S4S is 2^W, W starting out at 10^150. Blind search for a golden search is so hard that combining it with an improved search will be harder, much harder generally on avg, than direct blind search. All this, in a context where the target is FSCO/I rich configurations. We already know that there is a known, adequate cause. Intelligently directed configuration that injects active intelligently sourced configuring information as a bridge that puts you down on or next to a target Ti. This then allows troubleshooting exploration to achieve adequate function through a much more restricted and feasible search. The cluster of considerations brings us back full circle to the point that FSCO/I in a configuration and part interaction, wiring diagram based entity, is a strong sign that it's best current causal explanation is design. KFkairosfocus
May 2, 2015
May
05
May
2
02
2015
03:10 AM
3
03
10
AM
PST
1 … 4 5 6 7 8 9