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INTELLIGENT DESIGN EVIDENCE
Methods of Design Detection
Methods of Design Detection
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Dr. William Dembski is a leading intelligent design theorist, and has written
several books on the subject, including Intelligent Design: The Bridge Between
Science & Theology, and The Design Inference: Eliminating Chance through Small
Probabilities (Cambridge Studies in Probability, Induction and Decision Theory).
Dr. Dembski holds a Ph.D. in mathematics and philosophy, and an M.Div. from
Princeton Theological Seminary. One of Dembski's contributions to the intelligent
design movement is to set forth one method of detecting design, a method he
describes as the Explanatory Filter.
Dembski describes his three-part Explanatory Filter together with an example of
its use in a paper published at Access Research Network. In the paper, entitled
The Explanatory Filter: A three-part filter for understanding how to separate
and identify cause from intelligent design, Dembski explains:
For more writings of Dembski's go to The Design Inference.
Also, see Dembski's thoughts on Specified Complex Information
several books on the subject, including Intelligent Design: The Bridge Between
Science & Theology, and The Design Inference: Eliminating Chance through Small
Probabilities (Cambridge Studies in Probability, Induction and Decision Theory).
Dr. Dembski holds a Ph.D. in mathematics and philosophy, and an M.Div. from
Princeton Theological Seminary. One of Dembski's contributions to the intelligent
design movement is to set forth one method of detecting design, a method he
describes as the Explanatory Filter.
Dembski describes his three-part Explanatory Filter together with an example of
its use in a paper published at Access Research Network. In the paper, entitled
The Explanatory Filter: A three-part filter for understanding how to separate
and identify cause from intelligent design, Dembski explains:
- The key step in formulating Intelligent Design as a scientific theory is to
delineate a method for detecting design. Such a method exists, and in fact,
we use it implicitly all the time. The method takes the form of a three-stage
Explanatory Filter. Given something we think might be designed, we refer it
to the filter. If it successfully passes all three stages of the filter, then we are
warranted asserting it is designed. Roughly speaking the filter asks three
questions and in the following order: (1) Does a law explain it? (2) Does
chance explain it? (3) Does design explain it?
- At the first stage, the filter determines whether a law can explain the thing in
question. Law thrives on replicability, yielding the same result whenever the
same antecedent conditions are fulfilled. Clearly, if something can be
explained by a law, it better not be attributed to design. Things explainable
by a law are therefore eliminated at the first stage of the Explanatory Filter.
- Suppose, however, that something we think might be designed cannot be
explained by any law. We then proceed to the second stage of the filter. At
this stage the filter determines whether the thing in question might not
reasonably be expected to occur by chance. What we do is posit a
probability distribution, and then find that our observations can reasonably
be expected on the basis of that probability distribution. Accordingly, we are
warranted attributing the thing in question to chance. And clearly, if
something can be explained by reference to chance, it better not be
attributed to design. Things explainable by chance are therefore eliminated
at the second stage of the Explanatory Filter.
- Suppose finally that no law is able to account for the thing in question, and
that any plausible probability distribution that might account for it does not
render it very likely. Indeed, suppose that any plausible probability
distribution that might account for it renders it exceedingly unlikely. In this
case we bypass the first two stages of the Explanatory Filter and arrive at
the third and final stage. It needs to be stressed that this third and final
stage does not automatically yield design-there is still some work to do.
Vast improbability only purchases design if, in addition, the thing we are
trying to explain is specified.
- The third stage of the Explanatory Filter therefore presents us with a binary
choice: attribute the thing we are trying to explain to design if it is specified;
otherwise, attribute it to chance. In the first case, the thing we are trying to
explain not only has small probability, but is also specified. In the other, it
has small probability, but is unspecified. It is this category of specified
things having small probability that reliably signals design. Unspecified
things having small probability, on the other hand, are properly attributed to
chance.
For more writings of Dembski's go to The Design Inference.
Also, see Dembski's thoughts on Specified Complex Information