D.P. Dash writes, making a connection with another discussion on this list
about "detectors" in the scientific process:
>Some linguistic structures will fail to detect something.
In fact, don't you think that any detector (whether a linguistic structure
or some other kind) will, by design, fail to detect everything they are
not designed to detect?
That is, in fact, their value -- to only allow through (or detect)
something very specific. But, as D.P. suggests, it is also a problem.
Because it does not permit serendipity, or a "lucky accident," or
creativity/innovation to get through.
That's why the "Crap Detector" (I wish I hadn't chosen to use that name)
is actually a negative kind of detector. That is, it is designed to let
through everything that is not something specific (everything that does
not fail tests of logic or practicality or whatever definition of "crap"
is relevant in the situation.) Because it is detecting what something is
NOT (rather than specifying precisely what something IS or must be), it
does allow for serendipity and innovation -- so long as that serendipitous
or innovative idea is not illogical or impractical (or too expensive or
etc., etc.)
I would like to raise another kind of problem that I see as related to
D.P.'s question. When you speak about mechanisms for learning in
organizations, the tough problem I see these days is that of information
flow. That is, how can we build processes that get vital knowledge (or
even information) to the right places in a timely fashion. There is too
much information. We need both filters and communications links -- links
so we don't miss what's important and filters (or "detectors") so we don't
get overwhelmed by the unimportant. That strikes me as possibly the
number one "systems" priority for people trying to help organizations
learn.
--"John Gunkler" <jgunkler@sprintmail.com>
Learning-org -- Hosted by Rick Karash <rkarash@karash.com> Public Dialog on Learning Organizations -- <http://www.learning-org.com>