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Creation Evolution University • View topic - Opinion -- ID should drop information theory arguments

Opinion -- ID should drop information theory arguments

A forum for discussion and criticism of specialized topics relevant (pro and con) to Intelligent Design (ID) -- design detection, design specification, irreducible complexity, origin of life, platonic forms, design matrix, population genetics, cybernetic theories, semiotic theories, Fishers's fundamental theorem, Kimura's neutral evolution, Darwinian evolution, modern synthesis, probability theories, fine tuning, typology, discontinuity systematics, steganography, evolutionary algorithms, published ID material, ID philosophy, front loaded evolution, omega point theory, anthropic principles, multiverses and many-worlds, panspermia, extra terrestrials, teleology in biology, redundant complexity and fault tolerance, algorithmic complexity, complexity measures, no free lunch, blindwatchmakers, bad design, evil design, junk DNA, DNA grammars, von Neumann replicators vs. autocatalysis, Quines, polyconstrained DNA, Mendel's Accountant, DNA skittle, re-association kinetics, molecular clocks, GGU/GID models, enigma of consciousness and Quantum Mechanics, Turing machines, Lenski's bacteria, thermodynamics, Avida, self organization, self disorganization, generalized entropy, Cambrian explosion, genetic entropy, Shannon information, proscriptive information, Programming of Life, law of large numbers, etc.

Opinion -- ID should drop information theory arguments

Postby stcordova » Fri Oct 24, 2014 2:36 am

The plain old explanatory filter seemed good enough. I see no benefit in converting probabilities into bits and then making information theory arguments. It just leads to confusion. The fundamental problem: we can't give undisputed measurements as to how much information is in a system. Simple example, how much information is in a 1 meg JPEG file?

When I gave the example of a robot ordering 2000 fair coins from a random configuration to all heads, none of the ID proponents could agree on how much CSI the all heads configuration had. Winston said 0 bits, and I said 2000.

I've argued the easy analysis is to simply say 2000 fair coins under maximum uncertainty have an expectation of 50% heads. A 100% heads configuration is therefore improbable and indicates design according to the criteria of the explanatory filter. What's the point of using information theory in this case. It just adds confusion and pointless disagreements.

I've considered many designs in biology, and they can also be framed in terms of multi-sigma violations of expectation rather than using information theory. The arguments using law of large numbers and deviations from expectation are simpler, clearer and less assailable.
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Re: Opinion -- ID should drop information theory arguments

Postby awstar » Fri Oct 24, 2014 4:06 am

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Re: Opinion -- ID should drop information theory arguments

Postby WinstonEwert » Wed Nov 19, 2014 11:27 pm

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Re: Opinion -- ID should drop information theory arguments

Postby stcordova » Tue Dec 23, 2014 1:25 pm

Thanks for your reply Winston.

If I saw that string, I would not be able to reject the chance hypothesis unless I had a pre-existing pattern written in advance. So I would consider the string written by chance and risk the possibility I rejected a designed pattern.

In biology, unfortunately, we don't have pre-existing patterns written in advance, but we can still reject the chance hypothesis by self-specified patterns.
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Re: Opinion -- ID should drop information theory arguments

Postby WinstonEwert » Tue Dec 23, 2014 1:57 pm

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Re: Opinion -- ID should drop information theory arguments

Postby stcordova » Thu Dec 25, 2014 1:53 am

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Re: Opinion -- ID should drop information theory arguments

Postby WinstonEwert » Thu Dec 25, 2014 3:19 pm

Sal,

Merry Christmas

I'm rather critical of that non-increasing information line of argument. I suspect its true, but we don't have a developed theory of information that supports the argument. Instead, they are only appealing to some intuitive notion of information and I think that's rather shaky ground to argue from.

I actually agree that Dembski using the terms complexity and information with reference to what he was doing brought in more confusion and baggage then help. With hindsight, I'd say we'd be better off if he had called it specified improbability.

As for using expectations instead of specifications, can you explain using expectations why we infer design for Mt. Rushmore but not Mt. Fuji? I'm not clear how you differentiate between those cases using expectations alone.
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Re: Opinion -- ID should drop information theory arguments

Postby stcordova » Sat Dec 27, 2014 5:58 pm

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Re: Opinion -- ID should drop information theory arguments

Postby WinstonEwert » Mon Dec 29, 2014 1:18 am

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Re: Opinion -- ID should drop information theory arguments

Postby stcordova » Tue Dec 30, 2014 4:49 am

I wasn't aware of your paper, thank you for sharing it. There is nothing I could disagree with, and perhaps what little benefit I can offer is to show how I might alternatively implement the Explanatory Filter for some of the examples you provided wherein you used the ASC method.

For the number heads and tails, especially for large number of fair coins, I'd determine the violation of expectation from the mean. This is done via the binomial distribution, and the resulting probabilities when converted into bits will resemble the shape of your graph. For a system of 500 fair coins here are the associated probabilities for deviation from the mean

P(H=500) = 1/2^500 = 500 bits = 22 to 26 sigma (depending on which sigma approximation is used)
P(H>=499) = 1.53 x 10^-148 = 491 bits
P(H>=400) = 8.43 x 10^-44 = 143 bits = 13.6 sigma
P(H>=300) = 4.47 x 10^-6 = 17 bits = 4.54 sigma
P(H>=250) = 51.8 % ~= 1 bit = 0 sigma
P(T>=250) = 51.8 % ~= 1 bit = 0 sigma
P(T>=300) = 4.47 x 10^-6 = 17 bits = 4.54 sigma
P(T>=400) = 8.43 x 10^-44 = 143 bits = 13.6 sigma
P(T>=499) = 1.53 x 10^-148 = 491 bits
P(T=500) = 1/2^500 = 500 bits = 22 to 26 sigma (depending on which sigma approximation is used)

I got the binomial calculations from:
http://stattrek.com/online-calculator/binomial.aspx

I think this has a comparable shape to one side of the graph in your paper. I would suspect we ought to have comparable bit values???

The binomial distribution in the way I used it above has use in finding some biological designs (with some caveats):
1. homochirality
2. nucleotide bias
3. codon bias

One issue however for both the ASC method and the alternate method I suggest is the problem of repeats in DNA. Are some designs, or just copying accidents? The telomeric sequence is repeated a lot "TTAGGG", I think it is designed. It will signal "non-random" in ASC and in my alternate method. But what do we do with accidental repeats (they do happen)? I have no good answer.

Royal flush raises the question of why we should find it special above all other hands. My answer is that it's not just our subjective valuing of it, but it violates 3 dimensions expectation in the most extreme possible ways:

1. we statistically expect a mix of suits not the same suit
2. we statistically expect more number cards (2,3,4,5,6,7,8,9,10) than face cards (J,Q,K,A)
3. we statistically expect cards not to be adjacent to each other in collating sequence

Hence, just the way we affix symbols to a deck of cards makes the Royal special, and a natural specification. I did not have to do a Phi_ST analysis to point out the Royal is special given the symbols in use. The Royal Flush specification emerges naturally from the system of card symbols (suit, rank, collating sequence) much like "all fair coins heads" emerges naturally as a specification from the system of coin symbols (heads, tails).

There is the interesting topic of external specification. One hand called the "dead man's hand" (the hand Wild Bill Hickock held when he was shot): A-spade A-club 8-spade 8-club stands out because of subjective significance. External specifications of this sort probably don't have significance in biology. But there are other external specifications which we might be able to use.

In biology what I view as external specifications are duplications. We have duplicated cells, DNA, etc. We have convergence of form not attributable to common descent. Some biological systems have thematic resemblance to human designs like motors, gears. We can mathematically correlate the relationship.

Finally, there are external specifications that are algorithmic: binary digits of pi, binary digits of e, the chapernowne sequence, etc. There are only a finite number of such conceptual sequences a human mind can hold, or for that matter all the libraries of the world can hold. With this knowledge, Bill's Phi_ST calculations gives an approximation for the likelihood an idea in our mind can be realized physically by chance. I gave an alternate take on the influence of human psychology in defining specification (of which algorithmically compressed specifications are a subset):

http://www.uncommondescent.com/psycholo ... formation/

There are algorithmic compressible patterns in biology (like repeats). But more sophisticated algorithmic patterns? One I can think of is the Fibonacci sequence in certain flowers. How good of a specification it is remains an open issue.

I don't have a good working procedure for explaining how functioning systems violate expectation.
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