It is understandable that naturalistic thinkers are uneasy with the concept of miracles. So should we all be watchful not to believe too quickly because its easy to get caught up in private reasons and ignore reason itself. Thus has more than one intelligent person been taken by both scams and honest mistakes. By the the same token it is equally a danger that one will remain too long in the skeptical place and become overly committed to doubting everything. From that position the circular reasoning of the naturalist seems so reasonable. There’s never been any proof of miracles before so we can’t accept that there is any now. But that’s only because we keep making the same assumption and thus have always dismissed the evidence that was valid.
At this
point most atheists will interject the ECREE issue (or ECREP—extraordinary
claims require extraordinary evidence, or “proof”). That would justify the
notion of remaining skeptical about miracle evidence even when its good. There
are many refutations of this phrase, which was popularized by Karl Sagan. One
of the major problems with this idea is that atheists rarely get around to
defining “extraordinary” either in terms of the claim (why would belief in God
be extraordinary? 90% of humanity believe in some form of God) [1] The
slogan ECREE is usually said to be based upon the Bayes completeness
theorem. Sagan popularized the slogan ECREE
but the mathematical formula that it is often linked to (but not identical to)
was invented by the man whose name it bears, working in the seventeen forties but then he abandoned it,
perhaps because mathematicians didn’t like it. It was picked up by the great
scientist and atheist Laplace and improved upon.[2] This
method affords new atheism the claim of a “scientific/mathematical” procedure
that disproves God by demonstrating that God is totally improbable. It is also
used to supposedly disprove supernatural effects as well as they are rendered
totally improbable.[3]
It is often
assumed that the theorem was developed to back up Hume’s argument against miracles.
Bayes was trying to argue against Hume and to find a mathematical way to prove
that there must be a first cause to the universe.[4]
Mathematicians have disapproved of the theorem for most of its existence. It
has been rejected on the grounds that it’s based upon guesswork. It was
regarded as a parlor trick until World War II then it was regarded as a useful
parlor trick. This explains why it was strangely absent from my younger days
and early education as a student of the existence of God. I used to pour
through philosophy anthologies with God articles in them and never came across
it. It was just part of the discussion on the existence of God until about the
year 2000 suddenly it’s all over the net. It’s resurgence is primarily due to
it’s use by skeptics in trying to argue that God is improbable. It was not
taught in math from the end fo the war to the early 90s.[5]
Bayes’
theorem was introduced first as an argument against Hume’s argument on
miracles, that is to say, a proof of the probability of miracles. The theorem
was learned by Richard Price from Bayes papers after the death of the latter,
and was first communicated to the Royal society in 1763.[6]
The major difference in the version Bayes and Price used and modern (especially
skeptical versions) is that Laplace worked out how to
introduce differentiation in prior distributions. The original version gave
50-50 probability to the prior distribution.[7] The
problem with using principles such as Bayes theorem is that they can’t tell us
what we need to know to make the calculations of probability accurate in
dealing with issues where our knowledge is fragmentary and sparse. The theorem
is good for dealing with concrete things like tests for cancer, developing spam
filters, and military applications but not for determining the answer to
questions about reality that are philosophical by nature and that would require an
understanding of realms beyond, realms of which we know nothing. Bayes conquered the
problem of what level of chance or probability to assign the prior estimate by
guessing. This worked because the precept was that future information would
come in that would tell him if his guesses were in the ball park or not. Then
he could correct them and guess again. As new information came in he would
narrow the field to the point where eventually he’s not just in the park but
rounding the right base so to speak.
The problem
is that doesn’t work as well when no new information comes in, which is what
happens when dealing with things beyond human understanding. We don’t have an
incoming flood of empirical evidence clarifying the situation with God because
God is not the subject of empirical observation. Where we set the prior, which
is crucial to the outcome of the whole thing, is always going to be a matter of
ideological assumption. For example we could put the prior at 50-50 (either God
exists or not) and that would yield a high probability of God.[8]
Or the atheist can argue that the odds of God are low because God is not given
in the sense data, which is in itself is an ideological assumption. It assumes
that the only valid form of knowledge is empirical data. It also ignores
several sources of empirical data that can be argued as evidence for God (such
as the universal nature of mystical experience).[9] It
assumes that God can’t be understood as reality based upon other means of
deciding such as personal experience or logic, and it assumes the probability
of God is low based upon unbelief because the it could just as easily be
assumed as high based upon it’s properly basic nature or some form of elegance
(parsimony). In other words this is all a matter of how e chooses to see
things. Perspective matters. There is no fortress of facts giving the day to
atheism, there is only the prior assumptions one chooses to make and the
paradigm under which one chooses to operate; that means the perception one
chooses to filter the data through.
Stephen
Unwin tries to produce a simple analysis that would prove the ultimate truth of
God using Bayes. The calculations he gives for the priors are as such:
Recognition of goodness (D = 10)
Existence of moral evil (D = 0.5)
Existence of natural evil (D = 0.1)
Intra-natural miracles (e.g., a friend
recovers from an illness after you have prayed for him) (D = 2)
Extra-natural miracles (e.g., someone who
is dead is brought back to life) (D = 1)
Religious experiences (D = 2)[10]
This is admittedly subjective, and all one need do is
examine it to see this. Why give recognition of moral evil 0.5? If you read
C.S. Lewis its obvious if you read B.F. Skinner there’s no such thing. That’s
not scientific fact but opinon. When NASA does analysis of gas pockets on moons
of Jupiter they don’t start out by saying “now let’s discuss the value system
that would allow us to posit the existence of gas.” They are dealing with
observable things that must be proved regardless of one’s value system. These
questions (setting the prior for God) are matters for theology. The existence
of moral evil for example this is not a done deal. This is not a proof or disproof
of God. It’s a job for a theologian, not a scientist, to decide why God allows
moral evil, or in fact if moral evil exists. These issues are all too touchy to
just blithely plug in the conclusions in assessing the prior probability of
God. That makes the process of obtaining a probability of God fairly
presumptive.
this article was criticized by Jeff Lowder: see
response part 1
part 2
this article was criticized by Jeff Lowder: see
response part 1
part 2
[1] find, adherence.com
[2] Sharon Berstch McGrayne, The
Theory that would not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down
Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy.
New Haven: Yale
University Press, 2011, 3.
[3] As seen with chapter (?
Disprove) by Stenger and Unwin.
[4] McGrayne op cit
[5] ibid, 61-81
[6] Geoffrey Poitras, Richard
Price, Miracles and the Origin of Bayesian Decision Theory pdf http://www.sfu.ca/~poitras/Price_EJHET_$$$.pdf
11/11/10.
Faculty of Business
AdministrationSimon Fraser UniversityBurnaby, BCCANADA V5A 1S6. Geoffrey
Poitras is a Professor of Finance in the Faculty of Business Administration at Simon Fraser University. Lisited 12/22/12.
[7] ibid
[8] Joe Carter, “The Probability of God” First Thoughts. Blog of publication of First
Things. (August 18, 2010)
URL: http://www.firstthings.com/blogs/firstthoughts/2010/08/18/the-probability-of-god/ visited (1/10/13). Carter points out that when Unwin (an atheist
discussed in previous chapter) puts in 50% prior he gets 67% probability for
God. When Cater himself does so he get’s 99%.Cater’s caveat: “Let me clarify
that this argument is not intended to be used as a proof of God’s
existence. The sole intention is to put in quantifiable terms the probabilities
that we should form a belief about such a Being’s existence. In other
words, this is not an ontological proof but a means of justifying a particular
epistemic stance toward the idea of the existence or non-existence of a deity.The
argument is that starting from an epistemically neutral point (50 percent/50
percent), we can factor in specific evidence for the existence or non-existence
of a deity. After evaluating each line of evidence, we can determine if it is
more or less likely that it would entail the existence of God.”
”
[9] Metacrock, "The Scale and The universal Nature of Mystical Experience,"
The religious a priroi blog URL:
http://religiousapriori.blogspot.com/2012/10/the-m-sacle-and-universal-nature-of.html
see also the major argument I sue for documentation in that article, In P, McNamar (Ed.), Where God and science meet, Vol. 3, pp. 119-138. Westport, CT: Praeger. linked in Google preview.
[10] Stephen D. Unwin, The
probability of God a Simple Calculation That Proves the Ultimate Truth. New
York New York: Three Rivers
Press, Random House. 2003, appendix 238
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