[FoRK] Black Belt Bayesian vs. Authority, Fight!

il-young son <il.young.son at gmail.com> on Thu Aug 9 11:21:22 PDT 2007

or you can get a free scan here:
http://omega.albany.edu:8008/JaynesBook.html

e.t. jaynes is indeed one of the most lucid proponent of bayesian
logic.  one can always make the case that even frequentists use priors
(uniform, improper).

On 8/9/07, Matt Jensen <mattj at newsblip.com> wrote:
> Speaking of Bayesian statistics, run, don't walk, over to Amazon
> Canada.  For some reason Jayne's monumental "Probability Theory : The
> Logic of Science" is priced at $4 (versus $49 in U.S., $80 list).
> Maybe that's why it's currently at #3 on the overall bestseller list!
> I just bought my copy...
>
>    http://www.amazon.ca/gp/bestsellers/books
>
> Matt Jensen
> http://mattjensen.com
> Seattle
>
>
> Quoting Jeff Bone <jbone at place.org>:
>
> >
> > BBB is quickly becoming one of my favorite blogs.  This post from
> > earlier today is a perfect example, and a standalone gem.  Anything
> > that begins with the lines "Tim is a famous geologist. Tom is a famous
> > clown." --- is a keeper.  :-)  (Despite the bit of naming confusion
> > that appears midway...)
> >
> > Cf.
> >
> >   http://www.acceleratingfuture.com/steven/?p=33
> >
> > --
> >
> > (This post will be a more in-depth explanation of something I was
> > trying to get across in much of the Rapture of the Nerds essay.)
> >
> > Tim is a famous geologist. Tom is a famous clown. Tim gives us a theory
> > about rocks. We judge it to be 90% probable. In a parallel universe,
> > Tom gives us the same theory about rocks. We judge it to be 10%
> > probable.
> >
> > Jim gives us a theory about fish and presents a full technical case
> > that is good — the facts all fit. In a parallel universe, Jom gives
> > us a theory about fish and presents a full technical case that is
> > bad — it needs coincidences or leaps of logic. We judge Jim's theory
> >  to be 90% probable. We judge Jom's theory to be 10% probable.
> >
> > These two situations might seem the same. In the first case, we used
> >  only indirect evidence — the theorist's credentials — to assess
> > probabilities. In the second case, we used only direct evidence —
> > the known facts of the matter — to assess probabilities. Both are
> > useful kinds of evidence. But there is an important difference.
> >
> > Suppose we ask Tim and Tom to make a full technical case. Tim the
> > geologist gives us a full technical case that is, as expected, quite
> >  good. Tom the clown, in his own parallel universe, gives us the
> > same  full technical case — one much better than we expected from a
> > clown.  Since a full technical case relies in no way on authority,
> > we put  the same probabilities on Tim's claim and Tom's claim.
> > Anything else  would be unreasonable.
> >
> > Suppose we ask Jim and Jom about all of their credentials. It turns
> > out their credentials are exactly the same. Maybe they're both
> > equally famous clowns, who both took a course in marine biology once
> >  — surprising in Jim's case, given that his arguments are so good.
> > Or  maybe they're both famous marine biologists of exactly equal
> > fame  and competence — surprising in Jom's case, given that his
> > arguments  are so bad. None of this matters for our probabilities.
> > Again, we  already have a full technical case, and a full technical
> > case relies  in no way on authority. Jim's theory is still 90%
> > probable, Jom's  theory still 10% probable.
> >
> > So once we knew Tim and Tom's full technical arguments, their
> > credentials no longer mattered. But once we knew Jim and Jom's full
> > credentials, their technical arguments still mattered. Technical
> > arguments and credentials are useful types of information
> > individually, but when both types are available, one trumps the other.
> >
> > If I'm not mistaken (but I need to read up on this!), what I've been
> >  doing here is just repeating the definition of "screening off" from
> >  the theory of causal diagrams. If we have three variables (A, B,
> > C),  and A and C are independent conditional on the value of B, then
> > B  screens off A from C, and A and C do not cause each other. In the
> >  authority example of this post, you could see the causality running
> >  as follows. If a theory is true, that causes the technical case for
> >  it to be good. If people have good credentials, that causes them to
> >  adopt theories for which the technical cases are good. But
> > causality  does not run directly from truth to adoption by people
> > with good  credentials, or from adoption by people with good
> > credentials to  truth.
> >
> > Maybe this all sounds like a complicated way to make a simple point,
> >  but it matters, because people's intuitions sometimes get it all
> > wrong. If an  idea is adopted by silly people, or is not adopted by
> > competent people, that is seen as a "bad point" that is weighed
> > against the "good point" of solid technical argumentation. But this
> > weighing makes no sense — to a rational thinker, the "bad point"
> > counts until the "good point" arrives, and is then annihilated. In
> > real life, everything interesting is a mix of things you'll always
> > have to take on authority and things you can check for yourself, but
> >  you can still apply this insight.
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