Let me just flag the appearance of the word "surprise" in Ed's text,
and mention that it is one of the canonical beginnings of "inquiry".
In P**rce's theory of inquiry it is the occasion of "abduction", or
hypothesis generation, followed by a deductive projection, and then
a test of the deduction by "induction", that is, statistical method. (02)
Rinse and Repeat ... (03)
Jon Awbrey (04)
EB = Ed Barkmeyer (05)
EB: But the surprise failures are those that involve a factor that was
not considered at all, and not commonly considered in the trade.
How do you build an "X factor" defense for that? We do the
analysis of these failures in order to learn from them!
And the approach is pure Sherlock Holmes: When you
have eliminated the impossible, whatever is left,
however unlikely, must be the explanation. The
scientific requirement, however, is then to
show that that hypothesis leads to the
result that was observed. The end
is advancement of our knowledge,
not a better "X factor". (06)
Ed Barkmeyer wrote:
> Paola Dimaio wrote:
> >>So bridges stand because we have a certain amount of useful "knowledge" and
> >>they fail because we are not omniscient.
> > They also fail when our models do not accommodate for interaction and
> > change and the immensity of external factors that, in the real world,
> > play such a big role.
> Yes. That is what I meant by not being omniscient. If we overlook a factor
> that plays a big role, then when that factor comes into play, the bridge
> fails. Such was the fate of the bridge in Seattle.
> > Predicting change can only be done with limited expectation, however
> > it is wise to
> > have an 'x' factor in our equations (uncertainty) and design for some
> > preventive failover mechanism, instead of assuming that our models
> > because they are so 'finite' are perfect
> I don't understand how to build an X factor to protect from a beast you have
> never seen. Engineers build in "margin for error" factors, to accommodate
> less than ideal materials, cumulative errors of approximation in estimating
> impacts of factors they understand, and unexpected usage behaviors that are
> only somewhat outside conventional guidelines.
> Most cases of failure involve shoddy material or poor/dangerous design. And
> those cases can be described as simple malpractice -- deliberately failing to
> have the expertise and materials to do the job adequately.
> But the surprise failures are those that involve a factor that was not
> considered at all, and not commonly considered in the trade. How do you build
> an "X factor" defense for that? We do the analysis of these failures in order
> to learn from them! And the approach is pure Sherlock Holmes: When you have
> eliminated the impossible, whatever is left, however unlikely, must be the
> explanation. The scientific requirement, however, is then to show that that
> hypothesis leads to the result that was observed. The end is advancement of
> our knowledge, not a better "X factor".
> In H.G. Wells War of the Worlds, the Martians were not defeated by unexpected
> Earth technologies or climate or radiation, or anything they were able to
> observe and measure from space; they were defeated by viruses. (And of
> course, Michael Crichton's Andromeda Strain is based on the reverse.) It is
> that kind of X factor that brings down the bridge built by experts.
> And bridge building has been known to advance medical knowledge. Roebling and
> his crew learned a lot about "the bends" (absorption of nitrogen in the blood)
> in building the Brooklyn Bridge. That X factor killed him before the bridge
> was finished.
> > The stability factor in a model can only be a temporary , and must be
> > balanced with the 'uncertainty' factors at application stage
> I think we agree here. A model is only as good as our knowledge at the time
> we built it. As we learn more, some parts of that model may change. But we
> can only deal with "uncertainties" that result from factors we know about but
> can't predict well, or factors that we understand but can only calculate with
> some margin for error. We cannot accommodate factors we know nothing about,
> or do not understand. Trying to do that produces X factor models like the
> four humours and phlogiston.
> Edward J. Barkmeyer Email: edbark@xxxxxxxx
> National Institute of Standards & Technology
> Manufacturing Systems Integration Division
> 100 Bureau Drive, Stop 8263 Tel: +1 301-975-3528
> Gaithersburg, MD 20899-8263 FAX: +1 301-975-4694
> "The opinions expressed above do not reflect consensus of NIST,
> and have not been reviewed by any Government authority." (07)
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