http://web.mit.edu/rog/www/papers/fine_tuning.pdf

Where he argues that fine-tuning does not provide evidence for multiple universes.He gives the following analogy:

“Jane knows that she is one of an unspecified number of sleepers each of which has a unique partner who will roll a pair of dice. Each sleeper will be woken if and only if her partner rolls a double six. Upon being woken, Jane infers that there are several sleepers and dice rollers.”

White says that in this story “Jane’s reasoning here is unsound. She may of course have independent grounds for the Multiple Rolls hypothesis, but her being woken adds nothing.”

And argues that in the fine-tuning / observership case the situation is similar:

“As Leslie admits, it is not as though we were disembodied spirits waiting for a big bang to produce some universe which could accommodate

us. We are products of the big bang which produced this universe.”…

“After all, if we postulate enough universes, the chances are that there exist several life-permitting universes, perhaps even universes with precisely the same initial conditions and fundamental constants as our universe, and containing human beings indistinguishable from us. But we do not inhabit these universes, other folks do. If we accept Kripke’s (1980) thesis of the necessity of origins, we should hold that no other big bang could possibly produce us. ”

That we were not “disembodied spirits waiting for a big bang to produce some universe which could accommodate us” however is not necessarily true on theism I might add.

]]>All the probabilities in a Bayesian calculation are plausibilities. In this case the plausibility happens to be equal to a frequency: this is equivalent to using the principle of indifference about the identity of the particular person.

]]>I enjoyed your recent Bayesian lecture. I do wonder about the irony of your example involving the patient with a positive test result–Given the probability of false positives, what is the probability that this particular patient actually has the disease in question?

The irony of this example is that in order to use the Bayesian method effectively, we must have some means of finding the probability of false positives. How do we do this in practice? Well, we just count them; that is, we become “frequentists.” So on the right side of Bayes theorem we have a frequentist estimate yielding a Bayesian result for probability on the left side.

My suspicion is that this operation, although very useful, tends to give many users too much false confidence in Bayesian probabilities. I would favor calling the left side of Bayes theorem the “estimated probability,” to avoid the trap of sweeping our ignorance under some rug. In this case the actual probability would be an abstract idea as in the classical theory of stochastic systems.

]]>Yet here you explicitly agree with that statement.

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