The second problem with Dembski’s application is that he
only tests one particular
chance hypothesis and takes its rejection as evidence that all chance hypotheses can be
ruled out. In particular, the chance hypothesis he considers is based on a uniform distri-
bution or, in daily language, that the flagellum is assembled at random. Once more,
Dembski fails to apply his filter as he has described it. Remember that he should rule out
regularity before he goes on to compute probabilities. Granted, there is no known natural
law that would automatically assemble the flagellum but he also needs to rule out other
chance explanations. An evolutionary biologist would certainly argue that, according to
some plausible evolutionary scenario, the formation of the flagellum is an event of a
probability that is far from negligible. Dembski does not address this possibility but starts
directly at the final step of the filter.
There is an important point to be made here. The probability of an event depends on
what chance hypothesis, or
probability distribution, that is operating. For a quick and
common example, consider the Shakespearean phrase TO BE OR NOT TO BE. If 13
letters are chosen at random, what is the probability to get this phrase? The everyday
meaning of ‘‘chance’’ and ‘‘at random’’ is that letters are chosen independently and that all
letters of the alphabet are equally likely to be chosen. However, in probability theory this is
merely one example of a chance hypothesis corresponding to what is know as a uniform
probability distribution. Using this distribution, it is very unlikely to get the phrase but
there are many other plausible probability distributions that confer different probabilities
on the phrase. For example, if letters are chosen according to their frequencies in the
English language, the phrase becomes more probable. If, in addition, a letter is chosen in
accordance with how likely it is to follow another letter, the phrase becomes even more
likely (in this case, letters are not chosen independently of each other). Any time a
probability distribution (and dependence structure) is specified, the probability of the
phrase can be computed, and can be anything between 0 and 1.
Let us return to the flagellum where Dembski considers only the uniform distribution,
thus assuming that all protein configurations are equally likely. This is yet another version
of the old creationist classic: a microscopic tornado in a protein junkyard (although
Dembski’s own allegory is to go on a random shopping spree for cake ingredients). In a
sense, Dembski achieves absolutely nothing as no evolutionary biologist would suggest a
model even remotely resembling Dembski’s shopping cart and would thus gladly agree to
rule out this particular chance hypothesis. But whereas the evolutionary biologist would
have in mind a more realistic chance scenario, Dembski rules out chance altogether. His
argument for doing so is discussed in a section of
No Free Lunch where he states the need
for ‘‘sweeping the field of chance hypotheses.’’ Writes Dembski:
Design inferences therefore eliminate chance in the global sense of closing the door
to all relevant chance explanations. To be sure, this cannot be done with absolute
finality since there is always the possibility that some crucial probability distribution
was missed. Nonetheless, it is not enough for the design skeptic merely to note that
adding a new chance explanation to the mix can upset a design inference. Instead, the
design skeptic needs to explicitly propose a new chance explanation and argue for its
relevance for the case at hand.
No Free Lunch, p. 67–68
Thus, once Dembski has ruled out a chance hypothesis of his choice, the burden of proof is
on the ‘‘design skeptic’’ who must suggest a relevant chance hypothesis and also compute
its probability. This is in stark contrast to Dembski’s argument for pure elimination in a
later section:
What’s more, a proposed solution may be so poor and unacceptable that it can rightly
be eliminated without proposing an alternative (e.g., the moon-is-made-of-cheese
hypothesis). It is not a requirement of logic that eliminating a hypothesis means
superseding it.
No Free Lunch, p. 102
The inconsistency is striking. Design skeptics are required to make sure that a rejected
hypothesis is superseded; design proponents are not. Without doubt, most biologists would
consider Dembski’s shopping cart model ‘‘poor and unacceptable’’ and thus, appealing to
logic, could safely eliminate it and go on to more important activities.