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Not sure what knowledge community you refer to as grovelling in bullshit - its not one I recognise or choose to engage with. There are some information professionals who mistakenly use the term KM to refer to what you mention. However, we all know this is a very limited scope and certainly only the tip of the iceberg.
The Knowledge Community I engage in shares deep insights in a trusted environment that engage in conversations about future possibilities for humanity. One that cocreates options that computers are incapable of dreaming about (yet). Perhaps when sufficient Knowledge professionals influence these other fields to think divergently and include socialised half- thoughts to form new possibilities, we can combine ideas across all fields.
Yes computers are good at recognising patterns in data and visualising these to highlight gaps. But it takes humans to determine what the best options are to fill the gaps, of to understand which gaps are most valuable to address.
Mathematics are cool and great for informing quantitative aspects of our world. However, humans and society are subjective and qualitative - thankfully. To me the highest form of Knowledge professionalism is to fuel the flow of knowledge between people. We do this to optimise the value we cocreate when we interact to adapt and apply our collective knowledge (which by the way exists only in peoples' heads - NOT in a computer).
Lets hope that professionals from other fields are open to principles of KM as I am certain that they will accelerate their performance by being so.
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On 14 Jun 2021, at 12:24, Dennis Thomas <dlthomas@...> wrote:
I like this article you referenced. The “mold” example exemplifies the consciousness issue. It’s a great example of the issue that data scientists are grappling with. The physical world can be defined with great precision using mathematics, and objectively, the progressive steps defined in the article can be defined, but what about the consciousness, or intelligence that allows the mold to adapt to an respond to the conditions described?
To me, the behavioral dimension is beyond mathematics and AI. If I were to extrapolate from this example in regard to the human-machine relationship, I would have to say that once people have had enough of the subversive control “the machine” has over them, it will be rejected.
We know this to be true because if people do no not use a technology for whatever reason, it becomes obsolete.
For this reason, KM should establish and demand, technological standards that promote honest behavioral human-machine interactions. This includes the delivery and behaviors that support human behaviors, rather than machine behaviors.
This means (related to my world) cognitive technologies that work the way people naturally think.
Dennis L Thomas
On June 13, 2021 at 9:34:36 PM, Stephen Bounds (km@...) wrote:
100% agree that we're going to have to grapple with a changing
definition of "knowledge" as AI and augmented intelligence
continues to mature.
For what it's worth, I like the Bitbol
and Luisi model for cognition. The lack of a reproduction
and self-maintenance drive does prevent us from talking about AIs
as "living" although I think we can and should start talking about
their "knowledge". From my perspective they are just a different
form of agent in a system.
Executive, Information Management
M: 0401 829 096
On 14/06/2021 10:42 am, Dennis Thomas
Stephen, Arthur & others.
Michigan was the #1 State for investments in the U.S. in
2020. This state has more mechnical engineers in the U.S. and
perhaps the world. It is all about the 4th Industrial
Revolution. This is about AI, Internet of things, and Cognitive
AI may deliver consumption-based information, which is low
level knowledge, but cognitive technologies delivers high
level how, why, and what if knowledge that includes
dependencies, contingencies, cross-silo, cross-functional-
cross-refernce, and causal knowledge. The stuff that real
knowledge is based on. We are people. We are not components
of the machine.
Mathematics is a precise and superb language for defining
the physical world, but sucks when it comes to representing
actual behavioral knowledge outside of the realm of its own
data and self-serving data patterns identified from within its
own skewed stores. Where is Knowledge Management when KM
doesn’t even know where it stands in relation to the big
question - human consciousness? Data scientists,
neurologists, and cognitive scientists want to know? So do
Is it about Controlled Vocabularies and their relevant
conceptual representations, cognitive schemes that provide the
frameworks for unlimited ontological expressions or something
else more relevant to human consciousness? When will the
knowledge management community stop groveling in the mundane
world of how to bullshit?
It’s time to pierce the vail of what human consciousness is
and establish a real 4th Industrial Revolution knowledge
science that makes unequivalent sense. That’s what the data
scientists are trying to do. Why not us?
Ghee, that steak, wine, cigar, and Ole Smokey Tennessee
Liquor sure was great tonight!
Dennis L Thomas, CEO, IQStrategix
On June 13, 2021 at
7:23:50 PM, Stephen Bounds (km@...)
I agree that the next evolution of this list has to
be along the lines you describe.
In terms of your broader point, I think it is
important to acknowledge both that the application
of KM will mostly fall within the remit of
organisational management in the short to medium
term and that if KM is to survive and
thrive, it must define itself through theory,
concepts, and principles that transcend that
See for example Bruce Boyes' article on KM
disciplines, proposing that we are likely to
see evolution of distinct KM methods and best
practices in different domains including:
- Organisational KM
- KM for Development
- Societal KM
- Customer Experience KM
I believe we'll see more – Medical KM and Sports KM
being the most obvious candidates but there are
I think we are getting there as a community, but we
must always seek a richness of understanding rather
than confining ourselves to the KM techniques that
work for a 9-5 desk-based work paradigm (not least
of all for the reason that it is disappearing before
our eyes in a post-COVID world).
Executive, Information Management
M: 0401 829 096
On 14/06/2021 5:34 am,
Tim Powell wrote:
Hi Stephen and all,
Thank you all for these
insightful and thought-provoking comments. I’ll
second and amplify Stephen’s comments.
Making a list (and checking
it twice) can be a first step toward…what,
exactly? What’s the desired endstate? Though I
may have missed this earlier in the thread, I
always want to know, even before the WHAT, what
is the SO WHAT? What is the
PURPOSE-mission-goal of capturing such a list?
Who is it for? How is it to be used? What
authority will it convey (if only by
What begins as a list can
increase in value and usefulness by being then
grouped into categories (i.e., a taxonomy), then
including definitions (i.e., a dictionary) and
synonyms (i.e., a thesaurus.)
To me, a list could be most
helpful if it’s dynamic, inclusive, and
client-centered. Does it focus on solving
client problems, does it change as those
problems change, does it continually expand to
meet new needs? When knowledge becomes static
and/or hide-bound — as happens too often — its
relevance to client benefits plummets.
Given that some of us define
“knowledge” as a part of IT, others as part of
HR, others as part of strategy, and still others
as its own thing entirely — it’s not surprising
that any such list could expand rapidly to
include those closely-related fields.
For example, in my book on
the value of knowledge — a thin wedge of the
knowledge universe, albeit, to me, one of
paramount importance — I describe 267 key
concepts for that niche alone. My point is not
to throw my picks onto the pile — but, rather,
that for each specialized set of client needs,
there could be (and should be) a pretty deep and
Words matter — and our
language to describe knowledge should be just as
Diverse, Equitable, and Inclusive as our
workforce hiring policies.
My formal training is in
management, and the other thing I notice is the
list is growing to include much of the language
of management. That’s fine, to me — given that
I see “knowledge management” as a sub-discipline
of “management,” which also governs the other
enterprise resources of land, labor, and
capital. But it seems to me that if that is the
case, the list could expand almost infinitely –
with its meaningfulness and impact diluted as a
If Knowledge and Management
are overlapping circles in a Venn diagram, is
Knowledge Management their sum (either-or) or
their intersection (both-and)?
Please forgive my
digressions. Saturday (when I drafted this) is
my day of rest, reflection, and renewal -- and
this fascinating group always gets my wheels
Have a great week,
My conclusion is that
the "core" of knowledge management is (or at
least should be) the analysis of
organisations, diagnosis of dynfunction, and
prescription of suitable treatments. Whenever a
KM person picks some KM method to apply, it is
implied that they are intuitively
performing each of these steps. The problem is
that this typical KM approach is unsystematic,
unreliable, and often unreplicable (even if it
try to be a cheerleader for all initiatives
that improve standards in KM language,
analysis and diagnostic methods. I strongly
believe this is the only path to a "true" and
sustainable KM discipline. While Stan's
list would likely benefit from summary pages as
well as links to longer articles, there is no
doubt in my mind that it is a really valuable
Executive, Information Management
M: 0401 829 096
12/06/2021 10:36 am, Robert M. Taylor via
like the list - Stan you are nothing if not
the encyclopedist of KM. I thought a while
about what bothered me and it's this. I have a
conviction that KM is an open kind of thing.
It's not a fixed kind of thing like a
proprietary method. Its boundaries are always
going to be negotiable. So we're pretty much
able to adopt, adapt, and co-operate with just
about any kind of method or tool available.
But what, if anything, is really ours? I
think there's a smaller list of key areas, and
probably quite a small number of key
strategies. Myriad bits and pieces, maybe, but
they don't affect the core. We need all of the
basics of business strategy, planning and
management; project, process, service, product
and change management for starters. We need
information management and IT - especially
content and collaboration IT. We need
organisational, team and community leadership,
organisational learning, innovation,
communities (might be truly 'ours'), operating
model. We're not, of course, trying to cover
the totality of all of that, but we will use
all of it at some time. The list is nice to