Wesley Elsberry wrote:
>Richard Wein wrote:
>
>RW>Wesley, since you've raised this subject again, I'd like to
>RW>reiterate my view that CSI, as Dembski defines it, has not
>RW>been shown to exist in nature.
>
>RW>Since we last discussed the subject, I've had it confirmed
>RW>to me that Dembski, in his book "Intelligent Design",
>RW>defines the test for CSI as:
>
>RW> -log2 P(E) > 500
>
>RW>where E is a specified event. (I haven't read the book
>RW>myself, but this is basically the same as the definition
>RW>Dembski gives in an on-line article.)
>
>I just got a copy of this book, and I would agree that much of
>the work can be seen in Dembski's on-line articles, modulo a
>few editing changes. (Expect more on that later.) But that
>is not the test for CSI. At best, that is a description of
>Dembski's universal small probability bound. CSI is tested as
>the conjunction of complexity and specification.
Well, how does he define complexity?
In his on-line article
(http://www.leaderu.com/offices/dembski/docs/bd-idesign2.html ), he clearly
defines information as -log2p, but he doesn't specifically state how much
information is required for it to be considered complex. Isn't that where
the universal complexity bound (500 bits) comes in?
>RW>This means that the test for CSI is the same as the test
>RW>for design as defined in his earlier book "The Design
>RW>Inference", namely:
>
>RW> P(E) < 1/2 X 10^150
>
>Not quite. TDI's formulation of the universal small
>probability bound is better put as
>
> P(E|H) < 1/2 X 10^-150
>
>See pages 203-209 of TDI.
Certainly. I was simplifying.
>The conditional probability is, IMO, significant.
But, as I mentioned to you in an email a while ago, *all* probabilities are
conditional on some hypothesis. For example, if I state that the probability
of rolling a 6 with a 6-sided die is 1/6, that's conditional on the
hypothesis that the die is fair.
The fact that Dembski *fails* to mention the chance hypothesis in his
definition of CSI is a sleight of hand. If he is abandoning the principle
that the probability of the specifed event must be calculated under "all the
relevant chance hypotheses that could be responsible for E" (TDI p. 50),
then he is quietly abandoning the methodology of TDI.
>RW>But no-one to my knowledge has ever succeeded in showing
>RW>that the probability of a specified event in nature is this
>RW>small.
>
>A 100-city TSP solution meets the criterion of the universal
>small probability bound.
I certainly don't accept that the TSP solution meets TDI's criterion for
detecting design. Whether it meets the CSI criterion is unclear, until we
have a clearer definition of CSI.
>If by "nature" Richard is referring
>to biological events exclusive of human action, then we at
>least have Dembski's assurance in "ID" that the bacterial
>flagellum exceeds this value. But I would agree that no
>detailed probability calculation demonstrates this.
That *is* what I'm referring to. My point is, why should we accept Dembski's
assurance? How does he justify it?
If Dembski's definition of CSI is too vague for us to test whether any event
in nature meets the criterion, then we should refuse to accept his assurance
that he's detected it. It's a mistake, in my opinion, to accept this
unsubstantiated assurance before trying to show that we can detect CSI in
TSP solutions.
If I claimed that flagellums are designed because they are xarky, would you
agree that flagellums are xarky, but claim that TSP solutions are xarky too?
Or would you first insist on a clear definition of xarkiness, a
demonstration that flagellums have this property, and a proof that xarkiness
is a sign of design? (Sorry for the irony. No offense intended.)
>RW>I've seen some calculations by IDers which claim to
>RW>calculate the probability, for example, of a given protein
>RW>forming from a number of amino acids. But they assume that
>RW>the amino acids are selected as i.i.d. (identical
>RW>independently distributed) random variables. Of course,
>RW>this assumption is totally unrealistic, because evolution
>RW>by random mutation and natural selection would not produce
>RW>such a probability distribution (the amino acids are *not*
>RW>independent).
>
>This is where I see the conditional probability used in TDI
>come in. We compute the complexity of an event on the basis
>of how improbable the event is if it were due to chance.
>This does not mean that we actually believe it to be due to
>chance, or that we consider the chance hypothesis sufficient
>to the task. But like other forms of statistical inference,
>chance gives us a null hypothesis to perhaps reject.
But you can't just calculate the probability of an event "as if it were due
to chance". You need to assume a chance hypothesis. For example, the
probability of rolling a 6 with a die takes a different value if I assume
the die is fair than if I assume the die is biased in a particular way.
>RW>So the demand we should be making of Dembski is not "show
>RW>that natural selection can't produce CSI", but "show that
>RW>CSI actually exists in nature".
>
>I think that CSI as a property is not that remarkable. But I
>agree that someone who urges others to "do the calculation"
>might break loose with a few examples that show *all* the
>work, just to get everybody started. Preferably, one or more
>completely worked examples for each of the possible
>termination nodes in Dembski's Explanatory Filter would be
>provided. At least one set of examples should be taken from
>biological science.
I totally agree. But giving a clear example would expose Dembski's sleight
of hand, so I don't expect to see one any time soon.
Richard Wein (Tich)
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