Your analysis of efforts by IBM and Cync to provide effective organization is
getting back to the ideas you submitted on 000208 and 000212 that offer a path
for advancing OHS/DKR. You seem to be calling for a composite capability of
technology to take a stab at organization, and using people to refine it into a
resource that meets specific needs at a specific time and in a form that
expedites getting things done correctly and on time.
Notice how often "time" comes up? The tension remains time, what Peter Drucker
calls our most precious resource. Jack Park's lucid account on 010908 of this
challenge is offset on occasion by reminders that investing time for organizing
the record is critical for saving time and money, as we learned on 001207 and
more recently on 010911.
Technology has the potential to lower the bar so not quite so many of us fall
off the wagon that Jack warned prevents investing time for converting straw into
gold by adding intelligence that converts information into knowledge.
Getting our friends in technology lined up to work on tasks for creating
effective organization requires learning something new. Andy Grove points out
from experience working on technology at Intel that folks don't like to do that,
especially if they are making a good living using what they already know. We
all want to apply what we already know to create something to sell to other
folks. But, in this case engineers don't know that they don't know what to do,
so prodigious efforts are, as Clay Christensen describes in his book "Innovators
Dilemma," merely an exercise of flapping arms to fly. Doesn't get very far, as
we have seen the past two years, following Lee Iverson's report on 000324 that
all of the KM projects have failed.
Some folks talk about "out of the box" thinking. That's not quite right. You
have to step through a window from one "box" into another box that guides
conduct to apply computers under a different set of rules. To summarize (your
"elevator speech"), engineers must transition from information to a culture of
knowledge. As you pointed out on 000503 people who are happy with their life
don't want to make the effort under Jack's explanation on 010908. It is too
hard to expand the architecture for computers and software to include the
architecture of human thought, because it initially seems like a Pandora's Box
of complexity, as Jack noted on 000221, and you anticipated in your letter on
It takes a lot of faith to temporarily abandon beliefs of a life time to invest
time in doing things differently for awhile in order to discover how to create
technology for doing things better. Yet only experience reveals the dimensions
of the new box needed for progress. Faith seems like a tenant of religion, which
seems like the antithesis of technology to people who don't have time to think
carefully about religion. We are told that charismatic leaders can enjoin
people to abandon old beliefs and follow a new path. Perhaps someday a leader
will cross our path and lead us through the window to a new way of working, as
Doug Engelbart envisions. So far, we have been following the pied piper of IT,
and so remain mired in the past.
Perhaps, too, necessity will enjoin people to question religiously held beliefs
long enough for a new idea to take root.
Your letter today shows hope for the future.
Eric Armstrong wrote:
> Eugene Eric Kim wrote:
> > IBM's e-business Management Services has announced business software
> > that has some ability to "self-heal":
> > http://www.siliconvalley.com/docs/news/svfront/076589.htm
> > ...
> > The Deep Blue approach strikes me as being similar to Doug Lenat's Cyc
> > approach, which is to give the computer as much information as
> > possible so that it can make "intelligent" decisions. The problems in
> > both systems is that the information must be structured in a
> > highly-constrained manner.
> > The question is, how do we take terabytes of mostly unstructured
> > information, and structure it so that high-powered computers can do
> > intelligent things with them? Having a small group of people spend
> > decades manually structuring that information, like Lenat's team has
> > been doing, is not a very scaleable solution.
> Lenat's exciting assertion (the truth of which remains to be proven)
> is that there is a certain threshhold at which the system is smart
> enough to begin filling in gaps in its knowledge on its own -- to
> recognize what it needs to know, and either ask for it or find it
> from sources at its disposal.
> He stated that Cyc had just now "crossed that threshhold", and held
> out the promise that knowledge acquisition was now at the "take off"
> point in the exponential curve.
> I think the brute-force approach compensates for the kind of
> "conceptual chunking" that creates structure by grouping together
> similar things, and then building on that partial ordering to create
> taller structures.
> It is fascinating to contemplate a cyc-style version of Deep Blue.
> It should start "overlooking things", the same way a person does,
> by slighly inaccurate categorization, after which analysis should
> lead to an improved categorizing strategy that rectifies the oversight.
> Basically, the answer to "how do we structure terabytes of information",
> is with cyc, topic maps, or RDF -- with meta-information that builds
> a network of interrelationships, and applications which can deal with
> that meta-information to:
> a) Find the information you need
> b) Map the new ontological framework into an ontology you are
> familiar with (the essence of teaching)
> I confess to finding item (b) particularly fascinating. If my personal
> knowledge base has an ontology of things I know about, and I want
> to learn about some new thing, then the system can map the new
> ontology into terms I'm familiar with, constructiing analogies to help
> me "get it". It would figure out where to start by looking for central
> concepts in the new ontology that have similar structures in the
> ontologies I know. It would then build outward, adding more concepts.
> In such a system, the teaching process would be crafted to suit
> the individual, building on familiar things as much as possible to
> introduce new ones.
> For example, to teach Java to a C programmer, a lot of the
> constructs are an exact match. But teaching the object oriented
> aspects of the language requires an appeal to analogies taken
> from life (like cars), since the C language doesn't have a whole
> lot of similar constructs.
> But suppose the person had built a routine that functioned like
> an object! By inspection of the person's personal knowledge
> base, the system could recognize the object-orientedness of
> that example, and use it to give the person new terms for
> concepts they had already intuited.
> Or the system might discover very little familiarity with cars, and
> instead build examples based on totally different kinds of examples.
> I think we're a long way from being able to do those things, but
> those are the kinds of things that I suspect will become possible
> in time.
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