From: Subject: - The Problem of Information - Date: Tue, 24 Jul 2007 21:33:51 +0300 MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_NextPart_000_0000_01C7CE3A.54474390"; type="text/html" X-MimeOLE: Produced By Microsoft MimeOLE V6.00.2600.0000 This is a multi-part message in MIME format. ------=_NextPart_000_0000_01C7CE3A.54474390 Content-Type: text/html; charset="windows-1256" Content-Transfer-Encoding: quoted-printable Content-Location: http://www.trueorigin.org/dawkinfo.asp - The Problem of Information -

Home | Feedback | Links | Books

The Problem of Information
for the Theory of Evolution

Has Dawkins really = solved=20 it?

Royal=20 Truman
=A9 1999 Dr. Royal = Truman.  All=20 Rights Reserved. 

Abstract

3DIn a recent interview, Richard Dawkins, a fanatical = atheist=20 and a leading spokesman for Darwinian evolution, was asked if = he could=20 produce an example of a mutation or evolutionary process which = led to=20 an increase in information.  Although this has been known = for=20 some time to be a significant issue, during a recorded = interview,=20 Dawkins was unable to offer any such example of a documented = increase=20 in information resulting from a mutation.

After some months, Professor Dawkins has offered an essay=20 responding to this question in context with the interview, and = it will=20 be examined here.  It is pointed out that speculation and = selective use of data is no substitute for evidence.  = Since some=20 statements are based on Thomas Bayes=92 notion of information, = this is=20 evaluated in Part = 2 and=20 shown to be unconvincing.  Some ideas are based on Claude = Shannon=92s work, and Part = 3 shows=20 this to be irrelevant to the controversy.  The true = issue, that=20 of what coded information, such as found in DNA, human = speech=20 and the bee dance, is and how it could have arisen by chance, = is=20 simply ignored.  Part = 4=20 discusses the Werner Gitt theory of = information.

After several years, we continue to request from the = Darwinist=20 theoreticians:  propose a workable model and show = convincing=20 evidence for how coded information can arise by chance!

Part 1:  Biological Systems = Function
Because=20 Information is Present

As scientists penetrate ever deeper into the details of = nature, the=20 feeling is growing that we have some serious rethinking to = do. =20 We cannot use known properties of non-living matter and = naturalistic=20 laws to explain how living organisms arose.

Until recently, limited technology and scientific knowledge = led to=20 a simplistic view of living systems.  Based on the = limited=20 resolution offered by microscopes last century, Ernst Haeckel=20 (1834=961919) concluded that a cell was a =91simple little = lump of=20 albuminous combination of carbon.=92[1]&nbs= p;=20 That simple organic compounds should be able to produce this = clump of=20 =91stuff=92 by accident did not seem too improbable at that = time.

Let=92s contrast this with a modern view as expressed by = biologist=20 and ex-evolutionist Dr. Gary Parker:

=91A cell needs over 75 "helper molecules", all working = together=20 in harmony, to make one protein (R-group series) as=20 instructed by one DNA base series.  A few of these = molecules=20 are RNA (messenger, transfer, and ribosomal RNA); most are = highly=20 specific proteins.

=91When it comes to "translating" DNA=92s instructions = for making=20 proteins, the real "heroes" are the activating = enzymes. =20 Enzymes are proteins with special slots for selecting and = holding=20 other molecules for speedy reaction.  Each activating = enzyme=20 has five slots: two for chemical coupling, one for energy = (ATP), and=20 most importantly, two to establish a non-chemical = three-base=20 "code name" for each different amino acid R-group.  You = may=20 find that awe-inspiring, and so do my cell-biology=20 students!  [Even more awe-inspiring, since the more = recent=20 discovery that some of the activating enzymes have editing = machinery=20 to remove errant products, including an ingenious "double = sieve"=20 system.[2],[3]]

=91And that=92s not the end of the story.  The = living cell=20 requires at least 20 of these activating enzymes I call=20 "translases," one for each of the specific R-group/code name = (amino=20 acid/tRNA) pairs.  Even so, the whole set of translases = (100=20 specific active sites) would be (1) worthless without = ribosomes (50 proteins plus rRNA) to break the base-coded = message of=20 heredity into three-letter code names; (2) = destructive=20 without a continuously renewed supply of ATP energy [as = recently=20 shown, this is produced by ATP synthase, an enzyme = containing a=20 miniature motor, F1-ATPase.[4],[5],[6],[7]]=20 to keep the translases from tearing up the pairs they are = supposed to form; and (3) vanishing if it weren=92t = for having=20 translases and other specific proteins to re-make the = translase=20 proteins that are continuously and rapidly wearing out = because of=20 the destructive effects of time and chance on protein = structure!=20 [8]

=

One can give such descriptions some serious thought, or = repeat the=20 evolutionist=92s mantra, =91But with enough time anything is = possible=92 and=20 change the topic real fast!

Self-organization over Vast = Time=20 Periods?

Is there any reason, a priori, to assume that = inanimate=20 chemicals, unguided, will aggregate in manners which reflect = neither=20 statistical, thermodynamical nor mechanistic principles, and = display=20 behavior which we would otherwise clearly identify as the = product of=20 design?  Random chemical reactions proceed by discrete = mechanisms=20 with rate constants that can be studied in fine detail.  = These=20 follow very exact statistical rules that are at the lowest = level=20 constrained by spatial and thermodynamical laws.

Now, as time passes, molecular bonds may break, allowing = individual=20 molecules to separate and later undergo other chemical=20 reactions.  Eventually, with enough time, one expects a = universal=20 trend towards the thermodynamically most stable = distribution. =20 However, some molecules have energy barriers to breaking, = especially=20 at cold temperatures, and end up as amorphous =91tar=92, the = nemesis of=20 every organic chemist.  These two outcomes are a = priori=20 the expected outcome of random chemical changes, given enough=20 time.

Now, what do we observe today among living forms?  A = steady=20 state of chemical structures plus amorphous junk?  Lets = take a=20 second look at how organic material is found currently, = supposedly=20 after billions of years, in living organisms. Dr. Paul Nelson, = informs=20 us, after the theistic biochemist Dr. Michael Behe:

=91A typical cell contains thousands and thousands of = different=20 types of proteins.  Assembled from amino acids in = chains=20 "anywhere from 50 to 1000 amino acids" long, proteins fold = up into=20 "very precise" three-dimensional structures=97and those = structures=20 determine their precise functions:=92 [9]

=

That doesn=92t sound like nature behaving as = expected.  Let=92s=20 take a closer look at just one of those proteins mentioned = above to=20 see how serious the problem is.  From any biochemical = textbook we=20 find that a precise 3-dimensional structure is necessary for = it to be=20 functional in any useful manner.  In some portions of the = chain a=20 little leeway can be tolerated, in others the = right=20 amino acid must be in place:

=91This means that if, say, a P does not appear at = position 78=20 of a given protein, the protein will not fold regardless of = the=20 proximity of the rest of the sequence to the natural = protein.=92=20 [10]

Might a single protein nevertheless somehow arise = unaided? =20 No!  Of the possible chemical bonds between amino = acids,=20 all must form peptide bonds, although the natural = tendency is=20 for the reverse reaction to occur.[11]&n= bsp;=20 Then the protein must consist of only L or left-handed amino = acid=20 bonds although the inherent symmetry of the chemical reaction = predicts=20 a 50/50 mixture of L and R forms for every amino acid (except = the=20 achiral glycine) on the protein![12]&n= bsp;=20 Then the right sequence of amino acids must be combined.[13]&n= bsp;=20 Robert Sauer, a biochemist at MIT, systematically deleted = small pieces=20 from viral proteins and inserted altered pieces back into the = genes at=20 the sites of the deletions to determine how much variation at = various=20 portions of the sequence can be allowed.  As one might = expect, in=20 some portions more degrees of freedom can be tolerated than in = others.[14]

Sauer=92s conclusion:  the likelihood of finding a = folded=20 protein by a random mutational search is about 1 in 1065.  That is equivalent to = guessing=20 correctly one particular atom out of our whole galaxy.[14]

And that would be one single, isolated, worthless protein, = which=20 would quickly fall apart in the presence of water or = ultraviolet light=20 from the sun!

Something Sounds Wrong = Somewhere!

But we know that fertilized eggs develop into grown humans = and we=20 can synthesize fairly complex vitamins for our=20 consumption.  Even the Bible states that after 6 days of=20 Creation, God =91rested=92, or ceased from His creative work, = and=20 thereafter His activity was upholding His creation (Col. = 1:17). =20 Complexity increase in the development of individual organisms = and=20 useful functionality appear to be a fact, independent of = whether you=20 believe in creation or evolution!  Why do we find the = immense=20 complexity if natural processes predict the opposite, i.e. the = most=20 thermodynamically stable distribution and the =91amorphous = tar=92?

The answer lies in the third fundamental property of living = organisms, and that is information.

Where Does Information Come = From?

The atheist must propose a solution in which inanimate = matter alone=20 develops information.  Why is this?  Consider a = cherry=20 tree.  Before it dies, it must pass on instructions to = organize=20 organic material and thereby regenerate multiple copies of=20 itself.  A single copy would not be good enough since = external=20 conditions prevent survival from being 100% effective.  = We=20 observe that living beings are able to reproduce more than one = copy of=20 themselves on average per lifetime.  This is behavior = that does=20 not arise through natural processes from inanimate = matter.

How might the necessary increase of information content be = pumped=20 (coded) into DNA?  This question was posed to Professor = Dawkins,=20 a vocal atheistic evolutionist. As shown on the video A = Frog to a=20 Prince,[15]=20 he was unable to answer the question.  The Australian = Skeptics=20 made some typically lame excuses for Dawkins and scurrilous=20 accusations against the producers of the video and = creationists in=20 general,[16]=20 which were thoroughly refuted.[17]&n= bsp;=20 Dawkins himself responded to the =91information = challenge=92.[18],[19]&n= bsp;=20 Careful reading of his essay[18]=20 reveals no arguments or insights that have not been used for = years by=20 those wishing to deny the existence of a Creator.  It = seems=20 worthwhile to spend some effort going over these dead ideas, = not=20 because any particular person has brought them up again, but = simply=20 because evolutionists persist in resurrecting them.

A closer look at what Dawkins and others mean by the word=20 =91information=92 will be examined in more detail in the = following three=20 parts of this essay.

Now, we shall see later that Dawkins offers an impoverished = concept=20 of information which serves neither his nor our purposes, and = does not=20 address the issues of how functional systems needed to support = life=20 processes could arise in an unguided fashion.  My purpose = is not=20 to criticize a person but the ideas.  He has the ability = to tell=20 very entertaining stories to illustrate ideas in a manner = which indeed=20 reflect the underlying thinking of many evolutionists, but = that=92s all=20 they are=97stories.  Since Dawkins=92 article[18] appears to be representative = of the=20 beliefs of many people, we shall take a closer look at the = case he has=20 presented.

There are several statements in Dawkins=92 article which = are not=20 justified from the biological point of view.  After first = discussing information content, Dawkins implies incompetence = on the=20 part of a Creator.  This is a recurring theme in = evolutionist=20 literature:

=91Can we measure the information capacity of that = portion of=20 the genome which is actually used? We can at least estimate=20 it.  In the case of the human genome it is about=20 2%=97considerably less than the proportion of my hard disc = that I have=20 ever used since I bought it.=92 [20]

Here several comments are in order.  First, a = comparison of=20 creationist and atheistic positions shows a constant trend = whereby the=20 latter assume an oversimplified view of nature that becomes = more=20 complex as research continues and our knowledge = advances.  For=20 example, Darwin=92s view of genetics via pangenes has = been shown=20 to be hopelessly simplistic.  Furthermore, from about 180 = atavistic (vestigial) organs[21]=20 claimed for the human body we are down to perhaps none = today.[22],[23]&n= bsp;=20 In the late 1950s, artificial intelligence researchers claimed = human=20 thought could be encompassed by a =91General Problem Solver=92 = based on=20 about 100 rules.  This proved to be hopelessly = na=EFve.

A mind-set that postulates that life arose by chance is = inclined to=20 oversimplify the difficulties involved.  Experience = should teach=20 us that if those claiming 2% efficiency for the human genome = believed=20 in a Creator, they would look more seriously at how it = actually works=20 instead of disparaging what in reality no one really=20 understands.

Dembski discussed this point recently:

=91But design is not a science stopper.  Indeed, = design can=20 foster inquiry where traditional evolutionary approaches = obstruct=20 it.  Consider the term =93junk=94.  Implicit in = this term is=20 the view that because the genome of an organism has been = cobbled=20 together through a long, undirected evolutionary process, = the genome=20 is a patchwork of which only limited portions are essential = to the=20 organism.  Thus on an evolutionary view we expect a lot = of=20 useless DNA.  If, on the other hand, organisms are = designed, we=20 expect DNA, as much as possible, to exhibit function.  = And=20 indeed, the most recent findings suggest that designating = DNA as=20 =93junk=94 merely cloaks our current lack of knowledge about = function.  For instance, in a recent issue of the = Journal=20 of Theoretical Biology, John Bodnar describes how = =93non-coding DNA=20 in eukaryotic genomes encodes a language which programs = organismal=20 growth and development.=94  Design encourages = scientists=20 to look for function where evolution discourages = it.=92=20 [Emphasis added][24]

Secondly, genes are only a part of the DNA molecule, and = how these=20 map to a final outcome is far from understood.

Consider heterochromatin, the highly repetitive DNA which = codes for=20 little or no protein, and which represents about 15% of DNA in = human=20 cells and about 30% in fly cells.[25],[26]&n= bsp;=20 Zuckerkandl observes:

=91Despite all arguments made in the past in favor of=20 considering heterochromatin as junk, many people active in = the field=20 no longer doubt that it plays functional roles ... They may=20 individually be junk, and collectively gold.=92 [27]

That is, the nucleotides should be evaluated as an ensemble = and not=20 exclusively in context of isolated specific genes.

One protein can become part of an enzyme that then allows a = different gene to be able to produce a different kind of = protein.=20 Craig Venter,[28]=20 who founded the Celera company to crack the human genome, = states that=20 of the 70,000 human genes the function of no more than 5000 is = known.  Genes may have multiple functions, such as that = of the=20 SLC6A3-9 whose presence decreases the likelihood the person = will=20 smoke, as reported recently.[29]&n= bsp;=20 Vender points out that the manner in which multiple genes = interact=20 is not understood.  3196 genes are involved in the = brain=20 alone.

Dawkins=92 comments about only 2% of the human genome being = used=20 assumes researchers know far more about human DNA than is the=20 case.

Thirdly, the statement reflects a deliberate attempt to = make the=20 DNA=92s reproductive ingenuity look as bad as possible.  = Other=20 estimates of information capacity to date go as high as = 15%.[24]

Fourth, there is an implied assumption that the best = solution must=20 be 100% information density.  There are other possible=20 trade-offs, such as reliability and rates of production of = various=20 proteins.  Genes jammed together might lead to more = duplication=20 failure and the chemical interactions to produce proteins must = also be=20 optimally timed:  neither too fast nor too slow.  = The=20 spatial location and density of genes must be interpreted with = such=20 considerations.

Here is an example.  How much of a computer=92s = =91mouse=92 is=20 absolutely necessary to function?  Probably less than = Dawkins=92=20 proposed 2%.  It appears to be primarily superfluous = space. =20 The absolute minimum cable length is surely under a = millimetre. =20 The two buttons on mine could easily be crammed into a = fraction of its=20 space.  But it would then not perform its intended=20 function.  My fingers would not be able to press only the = desired=20 button in a comfortable manner.

Atheists are now faced with two problems.  Where does=20 information come from in the first place, and secondly, how = could it=20 increase over time.  Dawkins proposes one of the usual = models=20 whereby change is introduced randomly into the DNA and then = natural=20 selection weeds out unwanted results.

Is there Evidence of = Evolutionary=20 Improvement over Time?

From Dawkins=92 article we read:

=91The dozen or so different globins inside you are = descended=20 from an ancient globin gene which, in a remote ancestor who = lived=20 about half a billion years ago, duplicated, after which both = copies=20 stayed in the genome.

=91There were then two copies of it, in different = parts of the=20 genome of all descendant animals. One copy was destined to = give rise=20 to the alpha cluster (on what would eventually become = Chromosome 11=20 in our genome), the other to the beta cluster (on Chromosome = 16)...

=91We should see the same within-genome split if we = look at any=20 other mammals, at birds, reptiles, amphibians and bony fish, = for our=20 common ancestor with all of them lived less than 500 million = years=20 ago.  Wherever it has been investigated, this = expectation has=20 proved correct.=92 [30]

This is typical of a class of statements one is often = confronted=20 with from the evolutionary story-telling community, so I might = as well=20 invest a little time on it.  Notice the total lack of = evidence=20 (has the ancient globin been demonstrated to have existed?), = lack of=20 plausibility (what would the intermediate molecular structures = look=20 like and what use would they have had?) and implied compulsion = to=20 accept only one of many possible answers (why = shouldn=92t=20 blood-processing organisms all be endowed with such an = ingenious=20 resource by their Creator).

I shall also point out how conveniently data can be picked = and=20 chosen to try to demonstrate a preconception.  The fact = that=20 mould, yeast and the root nodules of beans also contain = hemoglobin is=20 inexplicably (but conveniently) not mentioned!

Clearly what we see here is a story, not evidence.  = There are=20 many ways of evaluating similarities found among living=20 organisms.

Dr. Kofahl, a chemist, observes:

=91A good example of alleged molecular homology is = afforded by=20 the a- and b-hemoglobin molecules of land = vertebrates=20 including man.  These supposedly are homologous with an = ancestral myoglobin molecule similar to human = myoglobin.  Two=20 a- and two b-hemoglobin associate together to form = the=20 marvellous human hemoglobin molecule that carries oxygen and = carbon=20 dioxide in our blood.  But myoglobin acts as single = molecules=20 to transport oxygen in our muscles.  Supposedly, the = ancient=20 original myoglobin molecules slowly evolved along two paths = until=20 the precisely designed a- and = b-hemoglobin molecules resulted that = function=20 only when linked together in groups of four to work in the = blood in=20 a much different way under very different conditions from = myoglobin=20 in the muscle cells.  What we have today in modern = myoglobin=20 and hemoglobin molecules are marvels of perfect designs for = special,=20 highly demanding tasks.  Is there any evidence that=20 intermediate, half-evolved molecules could have served = useful=20 functions during this imaginary evolutionary change process, = or that=20 any creature could survive with them in its blood?  = There is no=20 such information.  Modern vertebrates can tolerate very = little=20 variation in these molecules.  Thus, the supposed=20 evolutionary history of the allegedly homologous globin = molecules is=20 a fantasy, not science.=92 [31]

Hemoglobin has been extensively studied, and is often used = in the=20 creation/evolution discussions. Parker points out that,

=91We find hemoglobin in nearly all vertebrates, but = we also=20 find it in some annelids (the earthworm group), some = echinoderms=20 (the starfish group), some molluscs (the clam group), some=20 arthropods (the insect group), and even in some = bacteria!  In=20 all these cases, we find the same kind of = molecule=97complete and=20 fully functional.=92 [32]

He echoes Dickerson=92s observation[33]=20 that, =91It does not seem possible, that the entire = eight-helix=20 folded pattern appeared repeatedly by time and = chance.=92

Kofahl has also made a similar observation:

=91Hemoglobin molecules occur not only in vertebrate = animals,=20 but also in yeast, the mould, Neurospora, and in the root = nodules of=20 beans.  Hemoglobin occurs in some species of every = major=20 category of life except sponges, coelenterates (jelly fish, = etc.)=20 and protochordates (mostly worm-like marine creatures having = a=20 limited nerve chord, which are supposedly ancestral to = vertebrates=20 which have hemoglobin).  It is obvious that this = distribution=20 of hemoglobin does not fit with the idea that similarities = indicate=20 common descent, for nobody could believe that humans = inherited their=20 hemoglobin molecules from yeast.  And independent = evolution of=20 hemoglobin in so many different species appears highly=20 improbable.=92 [35]

Dr. Hannu Lång, a Molecular Geneticist at the = University of=20 Helsinki, commented about Dawkins=92 statements with respect = to=20 tetrameric hemoglobins:

=91It is not strange that all mammals have tetrameric=20 hemoglobins in their blood; monomeric ones can=92t transport = oxygen=20 from lungs to muscles. Every animal has slightly different=20 hemoglobins, animals live in different environmental = conditions and=20 hemoglobin design has to be accommodated to these = environmental=20 changes accordingly.=92 [34]

The biochemist Dr. Bob Hosken, Senior Lecturer in Food = Technology=20 at the University of Newcastle, Australia, has independently = provided=20 further information on this.  He began his postgraduate = career=20 comparing amino acid sequences of Australia=92s unique = fauna. =20 While he said that trying to work out phylogenetic = relationships was=20 =91very interesting=92, he also said:

=91[T]he most exciting thing ... was the opportunity = it provided=20 for relating the molecular architecture of each species of=20 haemoglobin to the unique physiological requirements of the = animal=20 species studied.

=91In other words, in a study of the relation between = the=20 structure and function of haemoglobin in various marsupial = and=20 monotreme species, I found it more meaningful to interpret=20 haemoglobin structure in relation to the unique = physiological=20 demands of each species.  A marsupial mouse has a = greater rate=20 of metabolism than a large kangaroo, so small marsupials = need a=20 haemoglobin with a structure designed to deliver oxygen to = tissues=20 more efficiently than that required in large animals, and I = found=20 this to be exactly the case.  I also investigated the = relation=20 of haemoglobin structure and oxygen transport in the echidna = and=20 platypus, and again found the oxygen delivery system of the = platypus=20 was well suited to diving, while in the echidna it was = suited to=20 burrowing.=92 [35]

Let=92s look at some other aspects of hemoglobin to see = whether there=20 is evidence of a common ancestry:

=91When it comes to comparing similarities among amino = acids in=20 alpha hemoglobin sequences, crocodiles have much more in = common with=20 chickens (17.5%) than with vipers (5.6%).  Averaging = all the=20 data for three various reptiles, three kinds of crocodiles = and three=20 kinds of birds shows=97completely contrary to the = predictions of=20 evolutionary descent from a common ancestor=97that the = greatest=20 similarity is between the crocodiles and chickens...=92 = [36]

Any similarity, whether at the morphology or cellular = level, could=20 be used to support the evolutionist theory.  Why limit = oneself to=20 hemoglobin?  University of Berkeley law professor Phillip = Johnson, a leading figure in the Intelligent Design community, = points=20 out that there are over 40 different kinds of eyes which, = because of=20 their fundamentally differing structure, must have = =91evolved=92=20 separately[37]=20 since the alternative of a common ancestor would be = unpalatable to=20 evolutionists.  Notice the double standard Dawkins and = others=20 use.  When data appears consistent with one model, it is = used as=20 evidence, and when not, a new story or name like = =91convergence=92 is=20 invented.  One must ask what the driving force is which = produces=20 such miracles repeatedly and independently.

We have a choice of many criteria that could be used to = define=20 similarity between species.

=91By comparing lysozyme and lactalbumin, Dickerson = was hoping=20 to =93pin down with great precision=94 where human beings = branched off=20 the mammal line.  The results were surprising.  In = this=20 test, it turned out that humans are more closely related to = the=20 chicken than to any living mammal tested!=92 [17]

Let=92s continue with Dawkins=92 thesis.  He = claims:

=91Genomes are littered with non-functional = pseudogenes, faulty=20 duplicates of functional genes that do nothing ... And = there=92s lots=20 more DNA that doesn=92t even deserve the name = pseudogene.  It,=20 too, is derived by duplication, but not duplication of = functional=20 genes.  It consists of multiple copies of junk, = =91tandem=20 repeats=92, and other nonsense...=92 [20]

Behe addresses the issue of duplicate genes as follows:

=91The sequence similarities are there for all to see = ... By=20 itself, however, the hypothesis of gene duplication =85 says = nothing=20 about how any particular protein or protein system was first = produced.=92 [38]

He amplifies later:

=91For example, the DNA in each of the = antibody-producing cells=20 of your body is very similar to that of the others, but not=20 identical.  The similarities are due to common descent; = that=20 is, all the cells in your body descended from one fertilized = egg=20 cell.  The differences, however, are not due to = Darwinian=20 natural selection.  Rather, there is a very clever, = built-in=20 program to rearrange antibody genes.  Billions of = different=20 kinds of antibody genes are =93intentionally=94 produced by = your body=20 from a pre-existing stock of just a few hundred gene = pieces.=92=20 [39]

Better designs are always those which are more = fault-tolerant; that=20 is, new eventualities are anticipated.

Living things have by far the most compact information=20 storage/retrieval system known.  This stands to reason if = a=20 microscopic cell stores as much information as several sets of = Encyclopædia Britannica.  To illustrate = further, the=20 amount of information that could be stored in a pinhead=92s = volume of=20 DNA is staggering.  It is the equivalent information = content of a=20 pile of paperback books 500 times as tall as the distance from = Earth=20 to the moon, each with a different, yet specific = content.[40]

However, Dawkins apparently has a low opinion of DNA and = how it=20 works.  This makes it easy to gloss over the issue of how = all the=20 necessary information arose.  Let=92s look a little more = closely at=20 this genetic apparatus.

Many genes tend to be involved in one function and must = work=20 together ab initio.  Dr. Lucy Shapiro of Stanford, = in=20 writing about the flagellum, the filament in bacterial cells = that is=20 driven by a rotary motor and is used for propulsion,[41]=20 writes:

=91To carry out the feat of co-ordinating the ordered = expression=20 of about 50 genes, delivering the protein products for these = genes=20 to the construction site, and moving the correct parts to = the upper=20 floors while adhering to the design specification with a = high degree=20 of accuracy, the cell requires impressive organisational=20 skills.=92 [42]

In an older evolutionary book, various tools, such as=20 electrochemical generators, traps, snares, nets, nooses, = pitfalls,=20 lures, hooks, press-studs, parachutes and so on, which follow = the=20 principles of physics and mechanics, found among living beings = were=20 discussed.  The author, Andr=E9e T=E9try, a leading = French biologist,=20 and anti-Darwinian evolutionist, deliberately sought a = naturalistic=20 explanation for the existence of life.  But she = concluded:

=91But how could these organic inventions, these small = tools,=20 appear? It seems most improbable that a single mutation = could have=20 given rise simultaneously to the various elements which = compose,=20 say, a press-stud or hooking device. Several mutations must=20 therefore be assumed, but this implies the further = assumption of=20 close co-ordination between different and distinct = mutations. Such=20 indispensable co-ordination is a major stumbling block, for = no known=20 mutations occur in this way.=92 [43]

Here we find examples of what Behe calls =91Irreducible=20 Complexity=92:  systems composed of individual parts = which only=20 make sense when all components are present, and for which = developing=20 each part individually is inconceivable.[44]&n= bsp;=20 Behe=92s most convincing examples involve functional systems = composed of=20 individual members which are single molecules.  Examples = include=20 aspects of blood clotting, closed circular DNA, electron = transport,=20 the bacterial flagellum, telomeres, photosynthesis and = transcription=20 regulation.  It is absurd to argue that the individual = parts=20 arose sequentially (or in parallel) and uncoordinated.

Can multi-part systems, which are themselves only a = component of a=20 living organism, arise by chance?  Professor Siegfried = Scherer, a=20 creationist microbiologist, published a paper in the = Journal of=20 Theoretical Biology on the energy-producing mechanism of = bacterial=20 photosynthesis.[45]&n= bsp;=20 He estimated the number of basic functional states involve no = fewer=20 than five new proteins to move from =91fermentative bacteria, = perhaps=20 similar to Clostridium=92 to fully photosynthetic = bacteria. =20 His calculations show that =91the range of probabilities = estimated is=20 between 10-40 and 10-104.=92 [46]&n= bsp;=20 (Note:  the total number of particles in the universe is=20 estimated at around 1080).  And=20 this is a trivial change compared to producing organs such as = a brain=20 or heart.

To Scherer=92s astronomical number, one must factor in the=20 consideration of what all can go wrong when photons interact = with=20 =91chromophores=92, the portions of molecules able to absorb = light in=20 photosynthesis.  If not properly designed, =91free = radicals=92 can be=20 generated which would wreak havoc on the cell.

Might Information Content=20 Increase
through Materialistic Processes?

Does Dawkins offer us any suggestions as to how information = content=20 might increase over time in living organisms?  We = read:

=91Mutation is not an increase in true information = content,=20 rather the reverse, for mutation, in the Shannon analogy,=20 contributes to increasing the prior uncertainty.  But = now we=20 come to natural selection, which reduces the =91prior = uncertainty=92 and=20 therefore, in Shannon=92s sense, contributes information to = the gene=20 pool.  In every generation, natural selection removes = the less=20 successful genes from the gene pool, so the remaining gene = pool is a=20 narrower subset.=92

=91Of course the total range of variation is topped up = again in=20 every generation by new mutations...=92

=91According to this analogy, natural selection is = by=20 definition a process whereby information is fed into = the gene=20 pool of the next generation.

If natural selection feeds information into gene = pools, what=20 is the information about?  It is about how to=20 survive.=92 [47]

Apparently, mutations provide change, and selection makes = sure the=20 good changes are favored, and this is defined by Dawkins as an = increase in information.  Since the amount of total = change=20 available after duplication of genes is greater, and Dawkins = states=20 that mutations decrease the true information content it is not = clear=20 why a larger number of initially identical genes, each = now=20 undergoing random mutations, is going to help his argument = out. =20 He now begins with a larger =91prior uncertainty=92.  The = following=20 parts of this essay will examine this question in more = detail.

It seems all these additional genes are going to add to the = confusion produced by DNA duplicating errors.  The total = number=20 of chances for failure increases, meaning more proteins with = the wrong=20 structures will be produced.

It addition, it would appear that specialization by = selection=20 should tend to decrease the genetic information.  Darwin = found=20 wingless beetles stranded on the island of Madeira.  = Perhaps the=20 beetles that could fly were all blown out to the ocean by the = wind, so=20 drowned before they could propagate their genes. But should = conditions=20 change, those beetles can no longer regain a valuable = function,=20 flying. Selection inevitably removes information from = the gene=20 pool.[48]

We should also consider regulatory genes that switch = other=20 genes =91on=92 or =91off=92.  That is, they control = whether or not the=20 information in a gene will be decoded, so the trait will be = expressed=20 in the creature.  This would enable very rapid and = =91jumpy=92=20 changes, which are still changes involving already created=20 information, not generation of new information, = even if=20 latent (hidden) information was turned on.  For example, = horses=20 probably have genetic information coding for extra toes, but = it is=20 switched off in most modern horses.  Sometimes a horse is = born=20 today where the genes are switched on, and certainly many = fossil=20 horses also had the genes switched on.  This phenomenon = explains=20 the fossil record of the horse, showing that it is variation = within a=20 kind, not evolution.  It also explains why there are no=20 transitional forms showing gradually smaller toe size.[49]

Virtually all mutations are harmful or at best neutral to = the=20 organism and prevent the messages encoded on DNA from being = passed on=20 as intended.  A greater number of redundant genes = compounds the=20 problem.  Consider what the long-term effect of mutations = is=20 according to Parker:

=91The more time that goes by, the greater the = genetic burden=20 or genetic corruption.  Natural selection can=92t = save us=20 from this genetic decay, since most mutations are recessive = and can=20 sneak through a population hidden in carriers, only rarely = showing=20 up as the double recessive which can be =93attacked=94 by = natural=20 selection.  As time goes by, accumulating genetic decay = threatens the very survival of plant, animal, and the human=20 populations=92. [50]

The late Professor Pi=E8rre-Paul Grass=E9, widely regarded = as one of=20 the most distinguished of French zoologists, although not a=20 creationist, denied emphatically that mutations and selection = can=20 create new complex organs, assigning to DNA duplication errors = the=20 role of mere fluctuation.[51]

Dr. Demick, a practising pathologist, likens the activity = of=20 mutations to =91A Blind Gunman=92.[52]&n= bsp;=20 He points out:

=91First, that the human mutation problem is bad and = getting=20 worse. Second, that it is unbalanced by any detectable = positive=20 mutations.  To summarize, recent research has revealed=20 literally tens of thousands of different mutations affecting = the=20 human genome, with a likelihood of many more yet to be=20 characterized.  These have been associated with = thousands of=20 diseases affecting every organ and tissue type in the = body.  In=20 all this research, not one mutation that increased the = efficiency=20 of a genetically coded human protein has been = found.  Each=20 generation has a slightly more disordered genetic = constitution than=20 the preceding one.=92 [52]

Dr. Jonathan Wells, a cell biologist currently at the = University of=20 Berkeley, states specifically with reference to Dawkins=92 = article:

=91But there is no evidence that DNA mutations can = provide the=20 sorts of variations needed for evolution ... The sorts of = variations=20 which can contribute to Darwinian evolution, however, = involve things=20 like bone structure or body plan.  There is no = evidence=20 for beneficial mutations at the level of macroevolution, but = there=20 is also no evidence at the level of what is commonly = regarded as=20 microevolution.=92 [53]

He continues:

=91The claim that mutations explain differences among = genes,=20 which in turn explain differences among organisms, is the=20 Neo-Darwinian equivalent of alchemy.  Compare:

  1. We know that mutations happen, and that they alter DNA=20 sequences; organisms differ in their DNA sequences, so the = differences between organisms must be due (ultimately) to=20 mutations.

  2. We know that we can change the characteristics of = metals by=20 chemical means; lead and gold have different = characteristics;=20 therefore it must be possible to change lead into gold by = chemical=20 means.

In both cases, the mechanisms invoked to explain the = phenomena=20 are incapable of doing so. Darwinists (like alchemists) have = misconceived the nature of reality, and thus hitched their = wagon to=20 an imaginary horse.=92 [53]

Israeli MIT-trained biophysicist Dr. Lee Spetner inspired = the=20 original question as to where the information arose in living = beings=20 through his book Not By Chance.[54]&n= bsp;=20 He made the following observations about Dawkins=92 essay:

  1. Let me coin the word =91biocosm=92 to denote the union = of all=20 living organisms at any particular time.  Then we can = say that=20 the information in the biocosm of today is vastly greater = than that=20 in the putative primitive organism.

  2. If Neo-Darwinian theory (NDT) is to account for the = evolution=20 of all life, as it claims to, it must account for this vast = increase=20 of biocosmic information [which would be needed to transform = bacteria into humans].

  3. Since NDT is based on a long series of small steps = then, on=20 the average, each step must have added some information. =

  4. According to NDT, a step consists of the appearance of = random=20 genetic variation acted upon by natural selection.  = (The=20 randomness is important to NDT to avoid having to invoke = some=20 mechanism for the organism=92s =91need=92 to induce = mutations that are=20 adaptive to it.)

  5. Because the steps in evolution are very small, and = because=20 there is supposed to have been a vast amount of evolutionary = change,=20 there must have been a very large number of such = steps. =20 Likewise, a very large number of steps should have added = information=20 to the biocosm.

  6. Mutations provide the raw material from which natural=20 selection chooses.  If a single step of mutation = followed by=20 natural selection adds information, then the mutation that = gets=20 selected must provide an increase in genetic = information.

  7. Considering the great sweep of evolution for which NDT = claims=20 to account, and considering the huge number of steps that = are=20 supposed to have led to that evolution, there must have been = a huge=20 number of random mutations that added at least a little = information=20 to the biocosm.

  8. Therefore, with all the mutations that have been = studied on=20 the molecular level, we should find some that add=20 information.

  9. The fact is that none have been found, and that = is why=20 Dawkins cannot give an example. [55]

Dawkins, and others who postulate that inanimate material = can=20 produce life unaided with a necessary constant increase in=20 information, are going to have to face up to the fact that a = lot of=20 very smart people are taking an increasingly dim view of what = is being=20 presented as =91fact=92 in many textbooks.[56]

It seems fair to point out that evolutionists have yet to = provide=20 even a single concrete example of a mutation leading to an = increase of=20 information as requested.

[Return to=20 Top]

Part 2:  The Concept of Information:
A = Bayesian=20 Approach

Evolutionists have been asked, and often ask themselves, = how they=20 can justify the assumption of a steady increase in average = information=20 content over eons of time as required by their theories.  = Now,=20 most people have some feeling for what the word information = means, but=20 it is not so easy to define.  In addition, there are = several=20 notions, depending on context, which can confuse the = discussion.=20 Relevant for our discussion are concepts of information, which = I shall=20 refer to as:

  1. the Bayesian

  2. the Shannon

  3. the Gitt

We will deal with the first one in this part of this = essay.

What does Dawkins mean by =91information=92? We will see in = this=20 section that (I) is alluded to, and in Part = 3 that he=20 uses definition (II) on occasion. Unfortunately, the truly = relevant=20 one, (III), is not dealt with at all (see Part = 4)!

Dawkins writes (numbering added; emphasis in original):

  1. =91Let=92s estimate, [Shannon suggested], the = receiver=92s ignorance=20 or uncertainty before receiving the message, and then = compare=20 it with the receiver=92s remaining ignorance after = receiving=20 the message.  The quantity of ignorance-reduction is = the=20 information content. ...=92 [57]

  2. =91But now we come to natural selection, which reduces = the=20 "prior uncertainty" and therefore, in Shannon=92s sense, = contributes=20 information to the gene pool...

  3. =91Information is what enables the narrowing down from = prior=20 uncertainty (the initial range of possibilities) to later = certainty=20 (the "successful" choice among the prior = probabilities). =20 According to this analogy, natural selection is by=20 definition a process whereby information is fed into = the gene=20 pool of the next generation.=92 [58]

We recognize from the statements above that Bayes=92 = theorem (see = below)=20 [after Thomas Bayes (1702=961761)], used also in modern = Decision Theory,=20 [59],[60]=20 is being invoked.  Claude Shannon incorporated Bayes=92 = ideas=20 somewhat in his own work.  The word =91information=92 is = indeed=20 sometimes used in such a sense.

Unfortunately, Dawkins declines to develop his argument to = where=20 anyone can quantify and evaluate the plausibility of his = explanation=20 as to how the complexity of organisms could increase over = time. =20 To consider the suitability of his use of prior and posterior=20 probabilities, lets take a short detour, look at the = mathematics=20 involved, and decide whether the case for unguided progress = has been=20 advanced.

In Dawkins=92 statements above, (b) should correctly say, = =91reduces=20 the =93posterior uncertainty=94 compared to the =93prior = uncertainty=94=92;=20 =91information=92 refers to the term P(E|F) / P(E) in equation = (1) below=20 (this is the usage of =91information=92 in this mathematical=20 context).

Bayes=92 theorem says:

P(F|E) =3D P(F) (P(E|F)/P(E))   &nbs= p;            = ;(1)

The symbol | means =91given that=92.

F is a Fact or belief.  Usually it = refers to a=20 hypothesis under consideration.

P(F) is the prior probability, that = is, the=20 probability that F is true or will occur before being provided = with=20 additional statements.

E is some Event or Evidence that is = generally, but=20 might not be, causally related to F.

P(E) is the probability that E will occur.

P(F|E) is the posterior probability, = that is,=20 the probability of event F occurring (or our confidence that F = is=20 indeed true) after being told event E occurred.

P(E|F) is the probability that event E will occur = should F=20 be true.

The probability that event E will occur, P(E), may be a = function of=20 several other factors, Fn.  Simplified by = assuming the=20 factors F1, F2...Fn are=20 mutually exclusive and exhaustive,

P(E) =3D P(E|F1)P(F1) +=20 (E|F2)P(F2) + ... (E|Fn)P(Fn)       &= nbsp;(2)

Mathematically, the probabilities can be expressed with = various=20 distribution functions instead of simple fractions between 0 = and 1. We=20 need not get into this level of detail.

Now, how can E and F be defined, to advance Dawkins=92 = argument? What=20 values are to be assigned?  We are left with nothing a = peer group=20 could evaluate.  Let=92s see if we can help him out a = little. =20 We would like things whose values could at least be = =91guesstimated=92 to=20 some extent.

Let=92s define:

F =3D the probability that a useful protein will arise by = chance

E =3D the event that the organism survives and passes on at = least as=20 many offspring as its parents.  This is a compound event = whose=20 overall probability is composed of several terms as shown in = equation=20 (2).

How do we handle P(E|F)/P(E)?  As shown in statements = a=96c, this=20 is what Dawkins labels =91information=92 (what reduces the = posterior=20 uncertainty compared to the prior uncertainty).  Among = the huge=20 number of parameters which affect which organisms pass on = their genes,=20 a Neo-Darwinist must argue that natural selection makes the = phenomena=20 not quite totally random, and this leads to a value of P(E|F)/P(E)=20 slightly > 1.

Using Sauer=92s work,[14] = the=20 probability of a protein arising by chance is around P(F) =3D=20 1.0x10=9665.  Should = P(E|F)/P(E)=20 be estimated to be greater than 1, say 1.1 (under normal = circumstances=20 an average advantage of 10% due exclusively to the single new = protein=20 in the presence of the other extraneous =91noise=92 survival = factors=20 suggests a massive selective advantage.  A typical = value=20 suggested is around 1.001, corresponding to a selection = coefficient of=20 0.1%[61]),= =20 then from Bayes=92 equation (1), we then obtain P(F|E)=3D = 1.1x10=9665.  That is, the new = estimate for the=20 chances of one protein arising by chance is theoretically = raised by a=20 minuscule amount, but it is still infinitesimal.

That appears to be the gist of Dawkins=92 use of the = concept of=20 information so far.  We cannot guess as to what the new = protein=20 does, do not know why it was produced nor whether it is now a = step=20 towards something new such as an enzyme.

This answer is highly unsatisfying, since the original = question=20 deals with how the know-how to produce complex structures, = such as=20 eyes, bone joints, a heart, became encoded on DNA.  These = involve=20 a vast amount of co-ordination in perfect timing.

Let=92s complete the analysis, remaining with this notion = of=20 =91information=92, and show why many scientists (I suspect the = atheistic=20 evolutionist Professor Gould of Harvard has independently = stumbled on=20 the same problem) realize random mutations cannot explain the=20 development of ever more complex organism.  The key is = that on=20 average, P(E|F)/P(E) may actually be < 1!  = This=20 would be a knockout conclusion for Neo-Darwinists.

Let=92s reconsider P(E|F)/P(E).  How much more likely = is it on=20 average that an organism with one additional protein, = generated ab=20 initio, with or without more duplicated genes, will = survive than a=20 sister exclusively because of that one protein?  In the = best=20 case, this single protein would become functional concurrent = with a=20 drastic change in the environment for which the protein could = be of=20 some immediate use.  This would offer some = measurable=20 advantage.  But it becomes =91just-so=92 story-telling to = invent such=20 environmental catastrophes so often.

Now, it is questionable whether any mutation can be shown = to lead=20 to some kind of improvement without causing deleterious = functioning of=20 some processes already encoded on the DNA (this is very = different from=20 the question whether one mutation could allow some members to=20 temporarily survive some drastic environmental = change). =20 Presumably a very bad mutation leads to death, weeding out = such=20 mutated genes from that species=92 gene pool forever. =20 Nevertheless, that member with a single new protein, whose = offspring=20 will eventually dominate the species population, will = inevitably=20 passively carry a large number of slightly defective but not = yet=20 deadly genes.

In other words, when I determine that a new protein is = present in=20 one or several organisms, I then know that many generations = have=20 passed since the protein-building process started, and that a = huge=20 number of bad, but individually not yet deadly, mutations have = been=20 accumulating.  This time bomb may indeed mean that P(E|F)/P(E)=20 on average may actually be < 1 =97 the chances of survival = for a=20 large number of members with one improvement but a huge number = of=20 disadvantages could militate against enhanced survival = chances!

This is an inevitable consequence of the law of increase in = entropy=20 to which all matter is subject in the long run.[62]&n= bsp;=20 This genetic load will get worse with an increasing number of=20 generations.  By invoking duplicate =91junk=92 genes, = Dawkins is=20 merely increasing the potential for more flaws.  When = told that=20 an organism has a new protein, I know that many generations = must have=20 passed since the point where no evidence for that protein = existed, and=20 so the current member has inherited a lot of momentarily = hidden=20 flaws.  Its temporary survival is a blessing in disguise = for the=20 species as a whole.  I therefore suspect that P(E|F)/P(E)=20 would indeed be < 1.

Nevertheless, survival is not the real issue, but rather an = increase in information.  The penalty for generating a = new=20 protein is a degrading of many other functions that have been = damaged=20 by all the concurrent mutations not related to producing that=20 protein.

Now, to obtain anything interesting, such as a new organ, I = need=20 quite more than a single new protein.  The probability of = getting=20 two of the right ones which will eventually lead to a new = structure,=20 all at once or sequentially, can only occur, if at all, should = vastly=20 more generations have passed, accompanied also by a vastly = greater=20 amount of genetic load.  In fact, time becomes the = greatest=20 enemy of evolution.

Conclusion:  the source of information, even when = defined=20 as per Dawkins, remains an intractable problem for = evolutionary=20 theory.

[Return to=20 Top]

Part 3:  The Concept of Information:
A = Shannon=20 Approach

Shannon=92s theory of information, while useful in the = context of=20 telecommunications, does not seem to help anyone much in the=20 evolution/creation debate.  The purpose in spending the = effort at=20 all here is to clarify why a richer concept, discussed in Part = 4,=20 becomes necessary.

Building on ideas Shannon developed in 1948, Dawkins = expresses=20 (here in summarized form) the key ingredients of his view of=20 information.

=91Redundancy was a second technical term introduced = by Shannon,=20 as the inverse of information. ...Redundancy is any part of = a=20 message that is not informative, either because the = recipient=20 already knows it (is not surprised by it) or because it = duplicates=20 other parts of the message. ...

=91Note that Shannon=92s definition of the quantity of = information=20 is independent of whether it is true. The measure he came up = with=20 was ingenious and intuitively satisfying.  Let=92s = estimate, he=20 suggested, the receiver=92s ignorance or uncertainty=20 before receiving the message, and then compare = it with=20 the receiver=92s remaining ignorance after = receiving the=20 message.  The quantity of ignorance-reduction is the=20 information content.  Shannon=92s unit of information = is the=20 bit, short for =91binary digit=92.  One = bit is=20 defined as the amount of information needed to halve the = receiver=92s=20 prior uncertainty, however great that prior uncertainty was = ...=92=20 [63]

=91In practice, you first have to find a way of = measuring the=20 prior uncertainty=97that which is reduced by the information = when it=20 comes.  For particular kinds of simple message, this is = easily=20 done in terms of probabilities. ...

=91In a message that is totally free of redundancy, = after=20 there=92s been an error there is no means of reconstructing = what was=20 intended.  Computer codes often incorporate = deliberately=20 redundant =91parity bits=92 to aid in error detection.  = DNA, too,=20 has various error-correcting procedures which depend upon=20 redundancy. ...

=91DNA carries information in a very computer-like = way, and we=20 can measure the genome=92s capacity in bits too, if we = wish.  DNA=20 doesn=92t use a binary code, but a quaternary one.  = Whereas the=20 unit of information in the computer is a 1 or a 0, the unit = in DNA=20 can be T, A, C or G. ...

=91Whenever prior uncertainty of recipient can be = expressed as a=20 number of equiprobable alternatives N, the information = content of a=20 message which narrows those alternatives down to one is = log2N (the power to which 2 must be = raised in=20 order to yield the number of alternatives N). ...

=91When the prior uncertainty is some mixture of = alternatives=20 that are not equiprobable, Shannon=92s formula becomes a = slightly more=20 elaborate weighted average, but it is essentially = similar.=92=20 [64]

=91The true information content is what=92s left when = the=20 redundancy has been compressed out of the message=92 = [20]

Testing the Relevance of this = Definition of Information

Experiment #1.  Tell me about the information = content=20 of the following message:

1011100100100011

Experiment #2.  In the following pairs which has = the most=20 information:

11010010101 or 1001101

E=3Dmc2 or the big brown = dog=20 which

Experiment #3.  Tell me about the information = content=20 of the following message:

Be6

We see we are in trouble.  Every attempt at an answer = seems to=20 start with, =91It depends=92.  Let=92s give some thought = to these three=20 experiments.

In experiment #1, the bits could represent characters in a=20 computer=92s extended ASCII code or a whole sentence in a = secret agent=92s=20 code look-up book.  What did I actually intend by this = bit=20 sequence?  The first 4 bits represent 1 out of 16 books = (24; we=92ll let 0000 represent book = 0, the=20 first one) I have agreed to in advance with my secret agent in = Bolivia; the next 8 bits represent a page number, between 1 = and 256=20 (28; 00000000 represents the = first=20 page); the final 4 bits represent a sentence on that = page.  In=20 case you are interested, book number 15 was Sun Tzu=92s, = =91The Art of=20 War=92 page 146 sentence 3 and the intended message was:  = =91Expendable agents are those of our own spies who are = deliberately=20 given fabricated information.=92

In experiment #2 we cannot select between the pairs without = knowing=20 what the intended meaning was or how this was coded.  The = short=20 code, E=3Dmc2, provides a = huge amount of=20 information and causes a great amount of surprise.  The=20 information content cannot be captured by Dawkins=92 concept = of=20 information.

The three letters in experiment #3 might have several=20 meanings.  Mine was =91Bishop to e6=92 (=3D =91Bishop to = [White=92s] King=20 6=92, in the obsolete descriptive notation).  Its = information value=20 depends on the particular settings of the other chess = pieces. =20 Shannon might have argued that the number of potential moves = available=20 reflects the space of possibilities, and the densest = communication of=20 the move chosen can be represented through bits of 0 and = 1.  This=20 is not very helpful nor does it reflect the usual, and my, = meaning of=20 information in this context.  In this case the total = information=20 can be what I now surmise, after receiving the message, about = the=20 intentions of my chess opponent and this depends on the = context. =20 Some possible conclusions might be:

  1. =91What a dummy.  That move makes no = sense, he=20 doesn=92t have a clue about what I am up to.  He=92s = dead meat.=92

  2. =91Aha, that closes off the last escape route for my = king. =20 Given the layout of the whole chess board, his strategy = seems to be=20 a direct attack on the big guy.=92

  3. =91Oh no, he just opened my queen to attack by his rook = and=20 simultaneously attacked my unprotected knight.  Time to = bump=20 the table over.=92

The definition of information in terms of binary bits = across a=20 communication channel has been analyzed and evaluated as being = of use=20 in only some limited contexts by many information = theorists. =20 This includes Professor Gitt (see Part 4), who then developed = a=20 detailed theory involving sender and receiver pairs, which = indeed=20 allows us to identify how the three experiments outlined above = can be=20 handled. These ideas will be discussed later.

Let=92s consider an example Dawkins offers, based on = Shannon=92s=20 theory:

=91An expectant father watches the Caesarian birth of = his child=20 through a window into the operating theatre.  He = can=92t see any=20 details, so a nurse has agreed to hold up a pink card if it = is a=20 girl, blue for a boy.  How much information is conveyed = when,=20 say, the nurse flourishes the pink card to the delighted=20 father?  The answer is one bit=97the = prior=20 uncertainty is halved.=92 [65]

Is this a persuasive notion?  There are several=20 weaknesses.  The blue card is known in advance not to = refer to=20 the color of the baby=92s face.  A huge amount of = knowledge must be=20 assumed in advance between the parties before the = communication can=20 take place.  Now, suppose the nurse shows up quickly with = a pink=20 card.  The father concludes several things, with various = levels=20 of certainty:

  • The baby is probably healthy, since the nurse would = hardly bother=20 telling him about a dead girl.

  • With far above 50% likelihood the nurse is correct that = it is a=20 girl:  hopefully the card was not intended for another = party=20 with a different meaning; presumably the nurse has not = forgotten the=20 agreed code, nor does she wish to play a mean joke on = him.

  • The baby is very likely 100% girl and does not possess = parts from=20 both sexes, since this possibility has not been anticipated = in=20 developing the code.  A card held up suggests such=20 possibilities are unlikely, since the sender would otherwise = not=20 know how to react.

  • If the nurse does not show up within 48 hours, in high = likelihood=20 things have not gone well.

To understand how much information transfer between sender = and=20 receiver is occurring it would seem that what is encoded in = the=20 message alone is only part of the picture.  There are = cases where=20 the receiver benefits from a multiplier effect when the = transmitted information is augmented with existing knowledge = on the=20 part of the receiver.

Suppose military headquarters is looking for a volunteer = for a=20 dangerous mission.  A candidate is found, and the message = is sent=20 that, =91Candidate X can do 24 push-ups=92.  Suppose the = receiver of=20 this information knows that the elite troop consists of = females who=20 can do between 15 and 26 push-ups, and males who can do = between 50 and=20 110.  Then in addition to a rough estimate of the = physical=20 strength of the candidate the receiver now also knows its = sex. =20 Assume that the original recruitment criteria for women = required them=20 all to have IQs above 110 and that it was known that only 3 = women=20 could actually do 24 or more push-ups and these were all = black. =20 Then the amount of true information available to the receiver = may now=20 be greater than that transmitted by the message and = indeed than=20 available to the sender!  This concept is not captured=20 effectively by Shannon=92s formula for maximum information = transmission=20 but is readily grasped by the average speaker.

Here=92s another example from Dawkins:

=91The great biologist J B S Haldane used Shannon=92s = theory to=20 compute the number of bits of information conveyed by a = worker bee=20 to her hive-mates when she =91dances=92 the location of a = food source=20 (about 3 bits to tell about the direction of the food and = another 3=20 bits for the distance of the food).=92 [66]

This is also very unconvincing.  The amount of = information is=20 not defined exclusively by the message, but what can be = assumed as=20 additional knowledge on the part of the sender and = receiver.  The=20 sender bee decides when the receiver is ready to receive the=20 message.  The intensity of =91wagging=92 reflects the = sender bee=92s=20 opinion as to the size of the food source available, and she=20 apparently decides how often the message must be repeated = before the=20 content is understood and memorized.  The sender can = assume that=20 flight adjustments by the receiver (around this bush, over = that tree,=20 away from that wasp nest) will be made.  The return path = does not=20 need to be explained.  Although the whole communication = appears=20 to be instinctive, somewhere along the line additional = knowledge had=20 to be built in.  The sender or receiver must =91decide=92 = whether it=20 is worthwhile sending the colleagues that distance for that = particular=20 quantity of food, and whether the journey to and fro should be = made=20 now or whether darkness will prevent a successful completion = of the=20 mission.

The amount of information that needs to be coded depends on = the=20 known resources assumed to be available to the receiver.  = If the=20 bee decided to instruct a friendly ant to collect the same = pollen a=20 very different kind of message would need to be used with a = very=20 different minimum content, whose length cannot be calculated = simply by=20 Shannon=92s equation.  The message length required to = ensure the=20 intention can be realized is a function of pre-existing = understanding=20 between both parties.  All sender-receiver members need = to be on=20 the same =91wavelength=92 before it is possible to determine = what needs to=20 be transmitted in the coded message.

In general, information theory as discussed in Part = 4, is=20 based on sender-receiver notions which assumes the sender can=20 intelligently or instinctively evaluate the needs of the = receiver and=20 act accordingly.  In speech, the voice loudness and speed = can be=20 estimated and adjusted to facilitate understanding by the = receiver,=20 without excessive waste.  It is not clear how Shannon=92s = digital=20 concept of maximum information content deals with such = analogue=20 subtleties.

Now, we have not yet developed a useful definition of = information,=20 but lets continue with Dawkins=92 ideas.

=91... [W]e can make an approximate estimation of the=20 information contents of the two bodies as follows.  = Imagine=20 writing a book describing the lobster.  Now write = another book=20 describing the millipede down to the same level of = detail. =20 Divide the word-count in one book by the word-count in the = other,=20 and you have an approximate estimate of the relative = information=20 content of lobster and millipede.=92 [20]

This looks more promising.  Information content in a=20 comparative sense can be grasped.

Let=92s see whether the suggestion, in this form, is=20 satisfactory.  I have 2 bottles, one of which contains a = kilogram=20 of benzene (C6H6) and the other a kilogram of = fluid=20 polyethylene ((CH2)n).  I now proceed to write a = book with=20 all the properties of both substances:  I describe = various=20 spectroscopic observations such as the infrared (IR) peaks, = mass=20 spectra (MS), nuclear magnetic resonance (NMR), and so = on. =20 Benzene, given its high symmetry (regular hexagonal), is shown = immediately to be incomparably simpler.  In fact, the = proton NMR=20 for benzene shows a single peak, whereas for polyethylene they = seem=20 uncountable and totally inseparable.  We continue with=20 rheological properties, such as viscosity as a function of=20 temperature.  Then we describe the distillation behavior, = followed by an analysis by gas chromatography (GC) and liquid=20 chromatography (LC).  Once again, our polyethylene sample = is=20 shown to be incomparably more complex.

Now, let=92s consider how both materials could be = generated, and we=20 write a detailed book for each.  In both cases we = start=20 with a very simple molecule, ethane (which can be converted = into=20 ethylene and other more interesting compounds).  We = describe the=20 chemical steps needed, including the exact processing details, = which=20 include reaction temperatures and in the case of benzene, = distillation=20 at a given point in time, to force ethylene to generate either = benzene=20 or polyethylene.  The result? Benzene is actually far = more=20 difficult to synthesize!  The information needed to = generate the=20 simpler material is greater than for the more complex.

Since DNA must encode the information to drive every step = along the=20 pathway from fertilized egg to adult, a description of the = final=20 product alone, i.e., the mature organism, is an = insufficient=20 criterion to compare information content.

A simpler example would be to compare two chemical = molecules=20 derived from a benzene ring.  Each has two substituents = in the 1=20 and 4 position (i.e. opposite each other=97called the = para=20 isomer).  The first compound uses two methyl (CH3) groups (each of which consists = of four=20 atoms) as substituents whereas the second uses two fluorines = (each=20 consists of one atom).  The relative book sizes of = description=20 and synthetic preparation are once again in the opposite=20 direction.

Now, this is not nit-picking.  I am attempting to = suggest a=20 word of caution.  Looking only at the physical genome of = the=20 organism may not capture the total information picture = actually=20 present very well.  The Designer understands the = ecosystem the=20 organism will be involved in.  The average number of = offspring=20 can be optimized to compensate for survival changes, and = nutritional=20 needs can be provided by the genomes present in other = organisms.

A second observation is that DNA also stores information = for=20 contingencies that may or may not arise, and this is not = reflected in=20 the physical description of the final organism.

Surprisingly, Dawkins may have suspected difficulties such = as those=20 mentioned above because he candidly tells us:

=91The great evolutionary biologist George C Williams = has=20 pointed out that animals with complicated life cycles need = to code=20 for the development of all stages in the life cycle, but = they only=20 have one genome with which to do so.  A butterfly=92s = genome has=20 to hold the complete information needed for building a = caterpillar=20 as well as a butterfly.  A sheep liver fluke has six = distinct=20 stages in its life cycle, each specialized for a different = way of=20 life.=92 [20]

We must now wonder just what it is Dawkins is trying to=20 communicate.  The information coded must also include = that which=20 is necessary to guide every step of the individual stages = along and to=20 provide for contingencies such as disease or temperature = changes.

Let=92s look more closely at this problem.  Dr. = Jonathan Wells=20 and Dr. Paul Nelson offer an example in which virtually=20 indistinguishable organisms are produced, but much more = information is=20 required in one case to guide the individual steps to get = there.

=91Most frogs begin life as swimming tadpoles, and = only later=20 metamorphose into four-legged animals.  There are many = species=20 of frogs, however, which bypass the larval stage and develop = directly.  Remarkably, the adults of some of these = direct=20 developers are almost indistinguishable from the adults of = sister=20 species that develop indirectly.  In other words, very = similar=20 frogs can be produced by direct and indirect development, = even=20 though the pathways are obviously radically different.  = The=20 same phenomenon is common among sea urchins and = ascidians.=92=20 [25]

The same principle is found between species:

=91Similar features are often produced by very = different=20 developmental pathways.  No one doubts that the gut is=20 homologous throughout the vertebrates, yet the gut forms = from=20 different embryonic cells in different vertebrates.  = The neural=20 tube, embryonic precursor of the spinal cord, is regarded as = homologous throughout the chordates, yet in some its = formation=20 depends on induction by the underlying notochord while in = others it=20 does not. [67]&n= bsp;=20 Indeed, as developmental biologist Pere Alberch noted in = 1985, it is=20 =93the rule rather than the exception=94 that =93homologous = structures=20 form from distinctly dissimilar initial states.=94 [68],[25]

Origin vs. Transmission of=20 Information

Transmission of information appears sometimes to be = confused with=20 its origin.  Consider two simple systems which = =91carry=92=20 information.

  1. a car battery

  2. a computer algorithm

To create such systems requires a deep understanding of = natural=20 phenomena to meet a goal and for the solution to be = optimized. =20 Once the intellectual work has been carried out, the knowledge = hidden=20 behind each could be stolen and duplicated without a need to=20 understand how or why a system works.  The information = itself is=20 duplicated and retained on a physical medium.  But such=20 information is not intrinsic to the matter itself and cannot = be=20 understood by knowing its properties.

Also, for matter organized as for the examples (i) and (ii) = above=20 to perform an intended goal, additional physical components = are=20 necessary, such as computer hardware components or an = engine. =20 These are anticipated and understood by the creator of the = information=20 system.  In these senses I argue that the total picture = of=20 quantity of information content often requires a broader view = than if=20 one merely looks at the carefully arranged matter.

Dr. Kofahl provides an interesting example that leads one = to=20 question whether Shannon=92s notion of information, = transmitted as a=20 message, captures the essential issue:

=91One mystery is how one virus has DNA which codes = for more=20 proteins than it has space to store the necessary coded=20 information.

'The mystery arose when scientists counted the number = of=20 three-letter codons in the DNA of the virus, QX174.  They found that the = proteins=20 produced by the virus required many more code words than the = DNA in=20 the chromosome contains.  How could this be?  = Careful=20 research revealed the amazing answer.  A portion of a = chain of=20 code letters in the gene, say -A-C-T-G-T-C-C-A-G-, could = contain=20 three three-letter genetic words as follows:=20 -A-C-T*G-T-C*C-A-G-.  But if the reading frame is = shifted to=20 the right one or two letters, two other genetic words are = found in=20 the middle of this portion, as follows: -A*C-T-G*T-C-C*A-G- = and=20 -A-C*T-G-T*C-C-A*G-.  And this is just what the virus=20 does.  A string of 390 code letters in its DNA is read = in two=20 different reading frames to get two different proteins from = the same=20 portion of DNA. [69]&n= bsp;=20 Could this have happened by chance?  Try to compose = an=20 English sentence of 390 letters from which you can get = another good=20 sentence by shifting the framing of the words one letter to = the=20 right.  It simply can=92t be done.  The = probability of=20 getting sense is effectively zero.=92 [35]

Dawkins is aware of this, but provides no materialistic = explanation=20 for its origin.[70]&n= bsp;=20 The total information prepared in the above genome by the = sender (God)=20 presupposes co-ordination with the receiver as how to process = the=20 message.  Two schemes, of identical message lengths, = could allow=20 either one or two proteins from the same DNA sequence to be=20 generated.  In each gene there is no redundancy, yet one = provides=20 twice the information as to the protein(s) to be generated = than the=20 other one does.

Dembski has argued in a mathematically rigorous way that = what he=20 calls Complex Specified Information (CSI) cannot = arise=20 by natural causes:

=91Natural causes are in-principle incapable of = explaining the=20 origin of CSI.  To be sure, natural causes can explain = the flow=20 of CSI, being ideally suited for transmitting already = existing=20 CSI.  What natural causes cannot do, however, is = originate=20 CSI.  This strong proscriptive claim, that natural = causes can=20 only transmit CSI but never originate it, I call the Law of=20 Conservation of Information.  It is this law that gives = definite scientific content to the claim that CSI is = intelligently=20 caused.=92 [24]

Why does change ever occur in the sense of = microevolution? =20 Random fluctuations, leading to small fluctuations among = existing=20 genes, is fully compatible with our view that God created = unique and=20 fully functional plant and animal categories which are to = =91reproduce=20 after their kind=92.  Before Darwin=92s time, natural = selection was=20 viewed as a method of culling members of a population which = were no=20 longer as well adjusted to the environment as the norm, and it = is an=20 information removing process.

Conclusion.  The question as to the origin = of=20 information necessary to develop greater complexity and to = guide an=20 organism=92s development has not been answered by Prof. = Dawkins.  A=20 discussion of Shannon=92s notions is not the same as providing = an=20 example as requested.

[Return to=20 Top]

Part 4:  The Concept of Information=97the Gitt = Approach

The key intuition is that some knowledge is =91pressed=92 = on to a=20 physical medium (matter or energy), the intellectual content = of which=20 was prepared by an original sender and after a time = lapse a=20 final receiver will decode the message and use = it.

Occasionally messages are accepted and passed on via = several=20 sender/receiver pairs.  I am calling the final receiver, = or its=20 substitute, the intended target, for whom the message was = generated in=20 the first place.

Here are some principles about coded information, = based=20 generously on Prof. Gitt=92s theory,[71]=20 which should facilitate future discussions as to how nature is = able to=20 perform in manners seemingly inconsistent with known = mechanistic and=20 probabilistic processes.

  1. Information is more than the physical coding used to = represent=20 it.  The sender and receiver must agree in advance on=20 conventions to represent whatever is to be communicated in = the=20 future.

  2. Information exchange requires that the frame of reference = or=20 context be agreed to in advance.

  3. Random processes cannot generate coded information; = rather, they=20 only reflect the underlying mechanistic and probabilistic = properties=20 of the components which created that physical = arrangement.

  4. Information efficiency may be denser than implied by = Shannon=92s=20 log2(n) equation, since a = common=20 basis of understanding exists between sender and receiver, = often=20 allowing implications with various degrees of = certainty to be=20 assumed by both parties, in addition to the raw data of the=20 message.

  5. In addition to the data encoded in the physical message = the=20 intention of the original sender must be considered.  = An=20 encoding system can be devised to ensure transmission = accuracy or to=20 avoid understanding by an unwanted party.

  6. A message allows information to survive over time. = Assuming that=20 the physical medium is not destroyed, there is some = flexibility as=20 to when the receiver can interpret the = information.

  7. The underlying meaning of coded information is external = to the=20 mere nature and properties of the sender.

  8. The physical medium upon which a message is encoded is = subject to=20 physical laws such as a natural trend towards increased = entropy in=20 the long run (and thereby loss of encoded information which = is=20 dependent on a physical medium).

  9. Information content of messages is more easily quantified = in a=20 comparative than absolute sense.

My suggestion (f) that information, encoded in the form of = a=20 physical message, can be used to bridge a time span to = communicate,=20 and that this time can be variable, offers useful = insights.  When=20 certain bacteria penetrate our bodies, an immune reaction is=20 activated.  This suggests that the necessary information = was=20 already present telling the body how to act.  The sender = (immune=20 system) responds to an environmental stimulus, generates the = necessary=20 message, whose conventions and frame of reference had already = been=20 anticipated, and the receiver can take appropriate = action.  The=20 necessary machinery was prepared by information stored in the=20 DNA.  What we see here is a complex chain of = sender/receiver=20 members which are able to respond to an external stimulus.

The activation of a message could occur a short time after = the egg=20 has been fertilized, or might never occur should the need = never=20 arise.  But the infrastructure is in place.

Consider point (g).  Say we are told the exact point = where a=20 billiard ball impacted a second one and are also told the = velocity and=20 direction of the deflected ball.  Do we have enough = =91information=92=20 to calculate the speed and direction of the first ball?  = This is=20 not the sense, sometimes used in mathematics, for what we are=20 discussing.  The feedback provided in this example is = inherent to=20 the properties and state of the first ball and the immediate=20 environment, such as friction of the table.

True information encoded in a message looks quite = different. =20 Human speech can communicate an intention, which has no = relationship=20 to the physical nature of the sender nor to the transmission=20 medium.  DNA can communicate how organs are to be = developed, step=20 by step, or how to regulate a body temperature in the = future. =20 These messages are more than mechanistic outcomes based on the = nature=20 or state of the sender.

Consider point (i).  Suppose a chemistry teacher shows = us a=20 bottle of a pure chemical compound and offers us a choice of=20 knowing:  the melting point; heat capacity; or infrared=20 spectra.  Based on what we may already know about that = sample,=20 the three choices would offer differing amounts of = information.

Note that it is easy now to evaluate experiments 1=963 from = Part = 3. =20 Information is far more than the coded message.  It = requires an=20 understanding of what the sender and receiver already know and = can do=20 with the message.  The relationship E=3Dmc2 has a very deep information = content to=20 someone already possessing the necessary mathematical and = physical=20 knowledge who also knows what the letters in the equation=20 represent.

Types of Sender and=20 Receiver
(a) Intelligent Sender and Intelligent=20 Receiver=20

Clearly intelligent sender/receiver pairs exist, such as=20 people.  The path between the sender and final target = can, of=20 course, involve intermediate sender/receiver pairs.  In = addition,=20 the message can be received and re-coded in various manners,=20 preserving all or most of the original intended = information. =20 Examples include the use of human translators or transmission = across=20 various media (voice 3D"" radio waves 3D"" tape recorder 3D"" paper 3D"" computer diskette).

(b) Intelligent = Sender and=20 Non-Intelligent Receiver=20

Can an intelligent sender communicate with a = non-intelligent=20 receiver?  Sure.  Humans can interact with = computers, for=20 example.  The sender transmits a database query and the = result is=20 sent back.  The exchange can be interactive, such as = working with=20 a computer expert system.  Of course the message encoding = (computer language) and additional infrastructure (hardware = and=20 communications devices) needs to be set up in advance by an=20 intelligent agent.

(c) Non-Intelligent Sender and = Intelligent=20 Receiver=20

Can a non-intelligent sender/receiver pair or sequence of = pairs=20 occur?  Certainly.  Automated production equipment = can rely=20 on a controller, which sends messages to on-line meas