RE: Design detection and minimum description length

From: Glenn Morton (
Date: Mon Dec 02 2002 - 00:53:57 EST

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    Iain wrote:

    >Yes, this is what I understand as well to be Glenn's problem with
    >the whole thing. You need to have "side knowledge" in order to
    >detect a design (or a pattern, to use a less loaded word). Your
    >maths teacher told you about prime numbers, and that is the side
    >knowledge you need to detect a pattern in a sufficiently long
    >sequence of coin-tosses that is based on prime numbers (e.g. "The
    >Nth toss is heads if N is the product of exactly two primes,
    >otherwise it is tails"). Of course you need to know about prime
    >numbers to get this pattern. But I don't see that as equivalent
    >to someone telling you that this particular pattern was designed.
    >Your teacher told you about prime numbers, and then you used your
    >own intelligence to detect the pattern based on primes.
    >Dembski also addresses this point in "No Free Lunch" (p63):
    >"The SETI researchers [in the film Contact] who inferred that an
    >extraterrestrial intelligence was communicating with them needed
    >to know about prime numbers before they could ascertain that an
    >incoming sequence of radio signals representing an ascending
    >sequence of prime numbers was in fact just that and therefore due
    >to another intelligence. A design inference is one intelligence
    >inferring the activity of another intelligence by the judicious
    >exploitation of background knowledge".
    >I really can't (sorry, Glenn), see any problem with this, and how
    >one can go from this to saying that the method has failed because
    >the researchers had to be told it was designed.

    Let me try in another manner. If I correlate two sequences and get a
    correlation coefficient of .9, my personal state of knowledge isn't what is
    telling me that the sequences are quite similar. The math is telling me. If
    I run a Fourier transform and find that the highest periodicity of a
    sequence is 50 cycles/second, then it isn't my personal state of knowledge
    which tells me that. It is the math. These two procedures allow conclusions
    to be made without any reference to the personal state of knowledge I have
    prior to running the programs. They are objective.

    But Dembski's method doesn't have a similar mathematical procedure. It is
    personal knowledge alone which decides whether something is designed. And
    when applied to living systems, it means that those who personally KNOW God
    created the world, will see the systems as designed and those who don't know
    God created the world will see them as not designed. The method will lead
    to no change in the consensus of scientific thought whatsoever. On the
    other hand, if Dembski had some objective correlation coefficient of design,
    it would be objective and no one could argue with it. As it is, he isn't
    even in the realm of science.


    for lots of creation/evolution information
    personal stories of struggle

    >-----Original Message-----
    >From: Iain Strachan []
    >Sent: Sunday, December 01, 2002 10:13 PM
    >To:; Glenn Morton; Adrian Teo
    >Subject: RE: Design detection and minimum description length
    >Thanks, Adrian, for that thoughtful summary of the discussion,
    >which gives much to chew on.
    >I'd like, if I may, to respond briefly to one of your points; the
    >other points need more careful thought & things are busy at the
    >moment. I've a short trip up to Edinburgh this week to (finally!)
    >collect my PhD, (seven years plus doing a full-time job; not a
    >recommended procedure for staying sane :-) so will not be able to
    >respond promptly to any further points that may follow on this week.
    >>Iain offers the example of a "perfect deal" in a game of bridge.
    >Anyone who has sees this situation would become highly suspicious,
    >BUT, only if that person has some knowledge of card games and
    >numbers. And that is precisely Glenn's point. For a person who has
    >never seen a pack of cards, and don't know anything about written
    >numbers, the "perfect deal" is unintelligible and random.

    >>Iain's examples of detecting mathematical
    >relationships/correlations seems irrelevant to me. What would
    >perhaps be a better analogy would be the detection of causality.
    >As in the case of attempting to detect design, one may be able to
    >say that an event (no pattern) is so improbable that we have to
    >reject the null and conclude that there is a pattern, just as in
    >detecting a correlation, one concludes that the null hypothesis is
    >so improbable that we reject it and therefore conclude that there
    >is a relationship. But it is an entirely different matter to go
    >from pattern to design, which would be analogous to going from
    >relationship (correlation) to causation.
    >Perhaps I can explain why I think it is relevant. I think the step
    >of going from correlation to causation comes down to how complex
    >the specification is, and this is close to the heart of how I
    >currently understand the Dembski Complexity/Specificity criterion,
    >and the "Explanatory Filter". For design, according to this, we
    >must first have a sufficiently long sequence that its probability
    >is very low. This constitutes what he calls "complexity".
    >However, that is not enough; one must also be able to describe the
    >data in a much shorter length than the string itself. "This is a
    >sequence of primes" for example. This gets one around the retort
    >"OK, you've found an interesting pattern, but how many other
    >interesting patterns could you find. I bet you could make any
    >pattern 'interesting' with a little ingenuity". The reply to this
    >is the counting argument I've used earlier. If the specifier
    >string is M bits long, then there are at most 2^M patterns of
    >similar interest (by 'interesting' I now mean, "can be described
    >in a compact way"). Then if the string itself is N bits long and
    >N >> M, we have a low probability of that pattern (or any like it)
    >But there is a third box to the filter, called "contingency". The
    >argument here is "but what if it has to be that way via a natural
    >cause". This is covered by the case where the specifier string
    >itself is so short that it could be attributed easily to a natural cause.
    >Such a string might be a third degree polynomial that fits nicely
    >through a set of 20 (x,y) points. One has found correlation
    >there, but no one would suspect design to be at work.
    >But suppose the following happened. I sent you a dataset of
    >10,000 (x,y) points, with x monotonically increasing, and y
    >wiggling about all over the place, apparently at random. Then you
    >decided to analyse it by fitting higher and higher degree
    >polynomials, and you use my minimum description length test to
    >decide the best model. (i.e. you calculate the bit-length of the
    >model, proportional to the model order, plus the number of bits
    >you need to transmit the residuals). Suppose you find that
    >actually the best fit comes when you try a degree 1000 polynomial.
    > Suppose the numbers are all digitised at 16 bits, and the
    >residuals you get from the model can all be expressed in 8 bits or
    >less (i.e. the model always gets it right to within around 0.5
    >percent). So the description length will be:
    >16x1001 (for the polynomial coefficients of a degree 1000 polynomial),
    >+ 10000x8
    >This comes to 96016 bits.
    >The original data (the y points) would be 160000 bits long and the
    >difference in length is 63894 bits. So the probability that you
    >could do better than this given the null hypothesis (no
    >correlatio/causation) is 2^63984.
    >Now, how do we get to the idea that this is design rather than
    >correlation? The IDer would argue (I think) that it is because
    >the description string is so long itself. How many physical
    >processes do we know that are governed by degree 1000 polynomials?
    > I think if you received such a dataset from me, you'd suspect
    >that I deliberately arranged it by generating the data from a
    >polynomial of degree 1000. Would the conclusion be different if
    >you didn't get it from me, but it arrived from outer space?
    >Here's another example that I kind of like. We know that the
    >description "all heads" is much simpler than the description of a
    >sequence of coin tosses governed by some relationship involving
    >prime numbers.
    >There is a party trick that the mathematician John H. Conway (of
    >"game of life" fame) performs. I imagine it has won him many a
    >drink in a bar. He describes it as being able to "cheat
    >probability". He takes around 20 American 1-cent coins, and
    >balances them all carefully on their edges on a table. What's the
    >odds you can make them all come down heads? Roughly 1 in a
    >million. He taps the underside of the table at just sufficient
    >force to get them to all topple, and they all come down heads! (I
    >guess this trick requires a large amount of practice to bring
    >off). Now, for such a simple description (all heads), there could
    >well be a simple naturalistic explanation. There is. It is all
    >down to the slight asymmetry in the milling process of the coins
    >that biases the way it will fall if just toppled. But now
    >supposing you performed a different trick. Suppose you stuck
    >labels on the "heads" sides of all the coins, and wrote the
    >numbers 1 to 20 on them. Then you tapped the table and at the
    >end, the only numbers showing were primes.
    >I think anyone who saw this done, if it could be done repeatedly
    >would suspect a cheat; such a feat might be performed by a
    >magician who cheated (i.e. designed it that way), but it couldn't
    >be down to natural causes. The difference is down to the
    >complexity of describing the pattern of heads and tails.
    >Hope this offers some more food for thought.
    >Thanks for your comments.
    >Best wishes,
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