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James Madison

A popular Government, without popular information, or the means of acquiring it, is but a Prologue to a Farce or a Tragedy; or, perhaps both. Knowledge will forever govern ignorance: And a people who mean to be their own Governors, must arm themselves with the power which knowledge gives.-- James Madison (letter to W.T. Barry, 4 August 1822)

Tags: quotes, politics, knowledge on 2008-07-18 -All Annotations (0) -About

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The Bamboo Project - “Information is more valuable than data, and...

Information is more valuable than data, and knowledge more valuable than information and understanding more valuable than knowledge,
— Russel Ackoff

Tags: quotes, data, information, knowledge on 2008-06-17 -All Annotations (0) -About

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A Little Knowledge Is a Dangerous Thing

Tags: knowledge on 2008-01-31 -All Annotations (0) -About

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Displaying intellectuality (Epstein) :: Fire and Knowledge

Tags: ignorance, knowledge on 2007-12-07 -All Annotations (0) -About

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Anne 2.1 » Knowledge Economy (Drucker) vs. Web Economy (Zelenka)

Tags: drucker, gtd, knowledge, productivuty, work on 2007-06-19 -All Annotations (0) -About

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Effective executives do not start with their tasks. They start with their time. And they do not start out with planning. They start by finding out where their time actually goes. Then they attempt to manage their time and to cut back unproductive demands on their time. Finally they consolidate their “discretionary” time into the largest possible continuing units. [From The Daily Drucker]
Web workers do not start with their tasks or with their time. They start with their attention. And they do not start out with planning or by finding out where their time actually goes. They start by finding where their attention wanders, and what gives them energy and increased attention. Then they attempt to let their attention flow freely and to cut back on redundant or tired information sources that demand their attention without providing new ideas or insight. Finally they combine what they have found into something new (software, web design, industry analysis, etc.) and make it available on the web where it can earn attention itself and lead to an ongoing multiplication of attention.
The knowledge worker (the executive in Drucker’s quote) goes after individual productivity; the web worker after group-based, collaborative, wisdom-of-crowds productivity. The knowledge worker cuts out unproductive uses of time; the web worker cuts out redundant information sources. The knowledge worker focuses on time efficiency; the web worker on attention expansion.

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Knowledge Jolt with Jack: Drucker and the (knowledge) worker

Tags: knowledge, productivity, work on 2007-06-19 -All Annotations (0) -About

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Stephen Downes: What do we know about knowledge?

Tags: knowledge on 2007-06-15 -All Annotations (0) -About

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Learning Networks and Connective Knowledge

Tags: knowledge, learning, semantics on 2007-06-15 and saved by42 people -All Annotations (111) -About

more fromit.coe.uga.edu

as traditional instructional software became entrenched, it became
difficult not to notice the movement in the other direction. First
was the exodus from commercial software in favour of open source
systems such as Moodle, Sakai
and LAMS. Others
eschewed educational software altogether as a wave of educators began
to look at the use of blogging
and the wiki
in their classes. A new, distributed, model of learning was emerging,
which came to be characterized as e-learning
2.0.
What happens when
online learning software ceases to be a type of content-consumption
tool, where learning is "delivered," and becomes more like
a content-authoring tool, where learning is created?”
The idea
behind the personal learning environment is that the management of
learning migrates from the institution to the learner.
The 2.0
Architecture
ts fundamental architecture, which may be called ‘learning
networks
We
don't present these learning objects, ordered, in a sequence, we
present randomly, unordered. We don't present them in classrooms and
schools, we present them to the environment, to where students find
themselves, in their homes and in their workplaces. We don't present
them at all, we contribute them to the conversation, and we become
part of the conversation. They are not just text and tests; they are
ourselves, our blog posts, our publications and speeches, our
thoughts in real-time conversation.
This is a tentative set of
principles, based on observation and pattern recognition
1.
Effective networks are decentralized.
2.
Effective networks are distributed. Network entities reside in
different physical locations. This reduces the risk of network
failure.
3.
Effective networks disintermediated. That is, they eliminate
‘mediation’, the barrier between source and receiver.
Examples of disintermediation include the bypassing of editors,
replacing peer review prior to publication with recommender
systems subsequent to publication
4. In
effective networks, content and services are disaggregated.
Units of content should be as small as possible and content should
not be ‘bundled’. Instead, the organization and structure
of content and services is created by the receiver.
This was the idea behind learning objects; the
learning object was sometimes defined as the ‘smallest
possible unit of instruction’.
5. In an
effective network, content and services are dis-integrated.
That is to say, entities in a network are not ‘components’
of one another.
6. An
effective network is democratic. Entities in a network are
autonomous; they have the freedom to negotiate connections with other
entities, and they have the freedom to send and receive information.
7. An
effective network is dynamic. A network is a fluid, changing
entity, because without change, growth and adaptation are not
possible.
8. An
effective network is desegregated. For example, in network
learning, learning is not thought of as a Separate Domain. Hence,
there is no need for learning-specific tools and processes.
Given the destructive nature of cascade phenomena,
it would make more sense to leave entities in the network unconnected
(much like Newton escaped
the plague by isolating himself). Terminating all the connections
would prevent cascade phenomena. However, it would also prevent any
possibility of human knowledge, any possibility of a knowing society.
Perception itself consists of selective
filtering and interpretation (pattern detection!). The mind
supplies sensations that are not there. Even a cautiously aware and
reflective perceiver can be misled.
Quantitative
knowledge, the cathedral of the twentieth century,
What
we count is as important as how we count, and on this, quantitative
reasoning is silent
We can measure grades, but are grades the
measure of learning?
We can measure economic growth, but is an
increase in the circulation of money a measure of progress?
We can
easily mislead ourselves with statistics, as Huff
shows, and in more esoteric realms, such as probability, our
intuitions can be exactly wrong.
It is important to
recognize that a structure of connections is, at its heart,
artificial,
an interpretation of any reality there may be, and
moreover, that our observations of emergent phenomena themselves as
fragile and questionable as observations and measurements - these
days, maybe more so, because we do not have a sound science of
network semantics.
is constructed in such a way
that no single impulse is able to overwhelm the network. A perception
must be filtered
through layers of intermediate (and (anthropomorphically) sceptical)
neurons before forming a part of a concept.
the human mind
The
mechanism for attaining the reliability of connective knowledge is
fundamentally the same as that of attaining reliability in other
areas; the promotion of diversity
This leads
to the statement of the semantic condition:
First,
diversity. Did the process involve the widest possible
spectrum of points of view? Did people who interpret the matter one
way, and from one set of background assumptions, interact with people
who approach the matter from a different perspective?
Second,
and related, autonomy. Were the individual knowers
contributing to the interaction of their own accord, according to
their own knowledge, values and decisions, or were they acting at the
behest of some external agency seeking to magnify a certain point of
view through quantity rather than reason and reflection?
Third,
interactivity, or connectedness. Is the knowledge being
produced the product of an interaction between the members, or is it
a (mere) aggregation of the members' perspectives? A different
type of knowledge is produced one way as opposed to the other.
Fourth,
and again related, openness. Is there a mechanism that allows
a given perspective to be entered into the system, to be heard and
interacted with by others?
Downes
Educational Theory
A good
student learns by practice, practice and reflection.
A good
teacher teaches by demonstration and modeling.
The essence of
being a good teacher is to be the sort of person you want your
students to become.
The most important learning outcome is a
good and happy life.
A learning activity is, in
essence, a conversation
This conversation forms a rich tapestry of resources, dynamic
and interconnected, created not only by experts but by all members of
the community, including learners.
the course content (if any) ought to be subservient to
the discussion, that the community is the primary unit of learning,
and that the instruction and the learning resources are secondary,
arising out of, and only because of, the community.
What needs
to be understood is that learning environments are
multi-disciplinary. That is, environments are not constructed in
order to teach geometry or to teach philosophy. A learning
environment is an emulation of some 'real world' application or
discipline: managing a city, building a house, flying an airplane,
setting a budget, solving a crime, for example. In the process of
undertaking any of these activities, learning from a large number of
disciplines is required.
“Educators play the same sort of role in society as
journalists. They are aggregators, assimilators, analysts and
advisors. They are middle links in an ecosystem, or as John
Hiler puts it, parasites on information produced by others. And
they are being impacted by alternative forms of learning in much the
same way, for much the same reasons.”
Postscript:
The Non-Causal Theory of Knowledge
Calls for "evidence that show this claim is true"
and "studies to substantiate this claim" are, like most
Positivist
and Positivist-inspired theories, reductive
in nature; that is why, for example, we expect to find something like
a reductive entity, 'the message', 'the information', 'the learning',
and the like.
They are also aggregationist; the presumption, for
example, is that knowledge is cumulative, that it can be assembled
through a series of transactions, or in more advanced theories,
'constructed' following a series of cues and prompts.
Saying that
there are ‘thoughts’ and ‘beliefs’ that
somehow reduce to physical instantiations of, well, something
(a word, a brain state…) is a mistake. These concepts are
relics of an age when we thought the mental came in neat little
atomistic packages, just like the physical. They are an unfounded
application of concepts like 'objects' and 'causation' to phenomena
that defy such explanation; they are, in other words, relics of 'folk
psychology'.
emergent phenomena are
not causal phenomena. That is (say) the picture of Richard Nixon does
not 'cause' you to think of the disgraced former president. They
require a perceiver, someone to recognize the pattern being
displayed in the medium.
perception (and
language, etc), unlike strict causation, is context-sensitive.
traditional research methodology, and
for that matter, traditional methods of testing and evaluation, as
employed widely in the field of e-learning, will not be
successful (are high school grades a predictor of college success?
Are LSAT scores? Are college grades a predictor of life success?).
Environments with numerous mutually
dependent variables are known collectively as chaotic
systems. Virtually all networks are chaotic systems. Classic
examples of chaotic systems are the weather system and the ecology.
In both cases, it is not possible to determine the long-term impact
of a single variable. In both cases, trivial differences in initial
conditions can result in significant long-term differences (the
butterfly
effect).
This
does not mean that a 'science' of learning is impossible. Rather, it
means that the science will be more like meteorology than like
(classical) physics. It will be a science based on modeling and
simulation, pattern recognition and interpretation, projection and
uncertainty.
Learning
theorists will no longer be able to study learning from the detached
pose of the empirical scientist. The days of the controlled study
involving 24 students ought to end. Theorists will have to, like
students, immerse themselves in their field, to encounter and engage
in a myriad of connections, to immerse themselves, as McLuhan would
say, as though in a warm bath. But it’s a new world in here,
and the water’s fine.

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Toward a New Knowledge Society » SlideShare

Tags: cops, human-networks, knowledge, learning, metadata on 2007-06-15 -All Annotations (0) -About

more fromwww.slideshare.net

tacit knowledge
Ineffable

You can’t put it into words You can’t generalize it
Depends on Context
Metadata
– Valuations (markets, Blogshares)
What Will
We See?

Beyond recommendations to…
– Classifications (tagging)
Learning is like perception
the acquisition of new patterns
of connectivity
through experience
Knowledge is like recognition
Pattern Recognition…
http://growchangelearn.blogspot.com/2007/02/emergent-learning.html
"Now I get it"
A-ha!
"Out of the blue"
"My mind leaped"
"Did an about-face"
"Shut up and did it"
Sudden breakthrough
Emergent Learning
Add Sticky Note
- Downes is talking about the process of pattern recognition.... Aha! moments and such where we see how things fit together.
  posted by wisely on 2007-06-15
http://www.downes.ca/files/osn.html
It’s a belief you
can’t not have
Like after
you’ve found
Waldo
Knowledge is
recognition
Pattern recognition is based on similarity
between the current phenomenon and
previously recognized phenomena
http://www.sund.de/netze/applets/BPN/bpn2/ochre.html
What we want is for students to
recognize patterns in existing networks
– in communities of experts,
communities of practice
That’s why we model and demonstrate
Add Sticky Note
- As John Gatto would say ( JohnTaylorGatto.com ), networks are not communities!
  
  Networks may be useful for limited purposes, but they are not communities.
  
  They are at best cheap immitations of real communities where people know and care about one another.
  posted by wisely on 2007-06-15

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Edge: WHO SAYS WE KNOW: ON THE NEW POLITICS OF KNOWLEDGE By Larry Sanger

Tags: expertise, knowledge, truth, wikipedia on 2007-04-24 and saved by10 people -All Annotations (0) -About

more fromwww.edge.org

for each of these things "we all know," significant
minorities insist that they're false.

Those
dissenters, however, don't matter much when it comes to most journalism,
reference, and education. Society forges ahead,
reporting and teaching things without usually mentioning the dissenters,
or only in a disparaging light. As a result, certain claims that
some of us don't accept end up being background knowledge, as
I'll call it. If you question such background knowledge,
or even express some doubt about it, you'll look stupid, crazy,
or immoral. Maybe all three.
It
is particularly the aggregation of public opinion that instituted
this new politics of knowledge
To be
able to determine society's background knowledge—to
establish what "we all know"—is an awesome sort of
power. This power can shape legislative agendas, steer the passions
of crowds, educate whole generations, direct reading habits, and tar
as radical or nutty whole groups of people who otherwise might seem
perfectly normal. Exactly how this power is wielded
and who wields it constitutes what we might call "the
politics of knowledge." The politics of knowledge has changed
tremendously over the years. In the Middle Ages, we were told
what we knew by the Church; after the printing press and the Reformation,
by state censors and the licensers of publishers; with the rise of
liberalism in the 19th and 20th centuries, by publishers themselves,
and later by broadcast media—in any case, by a small, elite group
of professionals.
we
are now confronting a new politics of knowledge
if you want to find out what "everybody knows," you
aren't limited to looking at what The New York Times and Encyclopedia
Britannica are taking for granted. You can turn to online
sources that reflect a far broader spectrum of opinion than that of
the aforementioned "small, elite group of professionals." Professionals
are no longer needed for the bare purpose of the mass distribution
of information and the shaping of opinion. The hegemony of the
professional in determining our background knowledge is disappearing—a
deeply profound truth that not everyone has fully absorbed.
with the chorus (or cacophony) of voices out there, there
is so much dissent, about everything, that there is a lot less of
what "we all know." Insofar as the unity of our culture
depends on a large body of background knowledge, handing a megaphone
to everyone has the effect of fracturing our culture.
I, at least, think it is wonderful that the power to declare what
we all know is no longer exclusively in the hands of a professional
elite. A giant, open, global conversation has just begun—one
that will live on for the rest of human history—and its potential
for good is tremendous
one of the fathers of modern liberalism, John Stuart Mill, argued—an
unfettered, vigorous exchange of opinion ought to improve our grasp
of the truth
With the rejection of professionalism
has come a widespread rejection of expertise—of the proper role
in society of people who make it their life's work to know stuff. This,
I maintain, is not a positive development; but it is also not a necessary
one.
according to one leading account
of knowledge called "reliabilism," associated with philosophers
like Alvin Goldman and Marshall Swain, knowledge is true belief that
has been arrived at by a "reliable process" (say, getting
a good look at something in good light) or through a "reliable
indicator of truth" (say, proper use of a calculator)
Reliability is a comparative quality; something doesn't have
to be perfectly reliable in order to be reliable. So,
to say that an encyclopedia is reliable is to say that it contains
an unusually high proportion of truth versus error, compared
to various other publications. But it can still contain some
error, and perhaps a high enough proportion of error that—as
many have said recently—you should never use just one reference
work if you want to be sure of something
when we say that encyclopedias should state the
truth, do we mean the truth itself, or what the best-informed people
take to be the truth—or perhaps even what the general public
takes to be the truth? I'd like to say "the truth
itself," but we can't simply point to the truth in the
way we can point to the North Star. Some philosophers, called
pragmatists, have said there's no such thing as "the truth
itself," and that we should just consider the truth to be whatever
the experts opine in "the ideal limit of inquiry" (in the
phrase of C. S. Peirce). While I am not a pragmatist in this
philosophical sense, I do think that it is misleading to say simply that
encyclopedias aim at the truth. We can't just leave it
at that.
experts
disagree about a lot of things. It is presumptuous, and a great
disservice to readers, for editors to choose one expert to believe
over another.
what do we most want, as responsible, independent-minded researchers,
out of an encyclopedia? Primarily, I think most of us want mainstream
expert opinion stated clearly and accurately; but we don't want
to ignore minority and popular views, either, precisely because we
know that experts are sometimes wrong, even systematically wrong. We
want well-agreed facts to be stated as such, but beyond that, we want
to be able to consider the whole dialectical enchilada, so that we
can make up our own minds for ourselves.
I believe that if someone
meets a certain standard of credentials about some topic, then that
person is probably more reliable on that topic than someone picked
at random. Bear in mind, however, that "credentials" should
be construed very broadly, and can mean much more than simply degrees
and certifications
due to its sheer size, the
public can also contribute enormous breadth and extra eyeballs for
all sorts of the more usually "expert" topics, too. The
general public may add a far greater assortment of topics and perspectives
than one would get if one assigned only experts to write about only
their areas of expertise. Moreover, the sheer quantity of eyeballs
gazing at obvious mistakes means that such mistakes will be fixed more
quickly and reliably than if one engages only experts working only
on their areas of expertise.
Experts,
or specialists, possess unusual amounts of knowledge about particular
topics. Because of their knowledge, they can often
sum up what is known on a topic much more efficiently than a non-specialist
can.
Wikipedia's
defenders have a great many arguments for dabblerism: non-experts
can create great things; the "wisdom of crowds" makes
deference to experts unnecessary; studies appear to confirm this in
the case of Wikipedia; there is no prima facie reason to give
experts any special role; it is only fair to judge people by what they
do, and not by their credentials; and making a role for experts will
actually ruin the collaborative process.
But what facts are
Wikipedians attempting to describe?
The
facts they want to amass are facts contained in the books and articles
that, it so happens, they are so keen on citing. Who writes those
books and articles? Experts, mostly.
Wikipedia can be expected to excel in scientific
and technical topics, simply because there is relatively little disagreement
about the facts in these disciplines. (Also because contributors
to wikis tend to be technically-minded,
but this probably matters less than that it's hard to get scientific
facts wrong when you're simply copying them out of a book.)
To give authority
to people simply on the basis of their expertise is—as Wikipedians
often say—simply "credentialism," and no more rational
than rejecting an application from a stellar programmer simply because
he lacks a B.S. in Computer Science. People should be judged
based on their demonstrated abilities, not degrees.
Some
of the finest programmers in the world lack any computer science degrees,
and it would be silly to fail to recognize that fact. But there
is no reason why a content creation system could not recognize as a "credential," or
as proof of expertise, all manner of evidence, not just degrees
Wikipedians have a sort of moral argument for
their dabblerism: they say, sometimes, that it is only fair to judge
people based on what they do, not who they are. Meritocracy
is the only fair way to justify differing levels of editorial authority
in open projects; and a genuine meritocracy would assign authority
not based on "credentials," but only based on what people
have demonstrated they can do for the project. It is
wrong and unfair to hand out authority based on credentials
Define "credential" as "evidence
of expertise." If we reject the use of credentials, we
reject all evidence of expertise; ergo, lacking any means of establishing
who is an expert, we reject expertise itself. Meritocrats are
necessarily expert-lovers.
I find
the moral argument annoying for another reason, however. It
implies that degrees, certificates, licenses, association memberships,
papers, books, presentations, awards, and all other possible evidence
of expertise—the whole gamut of "credentials"—just
don't matter. They don't constitute good evidence
of anything. But if they don't count
as good evidence of expertise, why should the ability to do something
on behalf of a mere Internet project count as good evidence? There
is a bizarre reversal in the insular world of Wikipedia: mere quantity
of work is a credential there, but not for academic tenure and advancement
committees; meanwhile, degrees and peer-reviewed papers are credentials
for tenure and advancement committees, but not for Wikipedia and its
ilk. (Wikipedians will protest that quantity of work doesn't
really matter. But, of course, it very much does.)
Wikipedia pooh-poohs the need
for expert guidance; but how, then, does it propose to establish its
own reliability? It can do so either by reference to something
external to itself or else something internal, such as a poll of its
own contributors. If it chooses something external to itself—such
as the oft-cited Nature report—then it is conceding
the authority of experts.
It is one thing to
argue for "the wisdom of crowds" by reference to an objective
benchmark. It is quite another thing to maintain that crowds
are wise simply because they are crowds. That is a philosophical
view, a variety of relativism, according to which the only truth there
is, the only facts there are, are literally "socially constructed" by
crowds like the contributors to Wikipedia.
Wikipedians attempt to take my dilemma by the horns, supporting the
credibility of Wikipedia's content through a combination of both
external and internal means. They insist that footnotes suffice
to support an article. If a fact has been supported by a footnote,
then, apparently, it is credible. This, we might say, is an external
means of fact-checking; but it is up to rank-and-file Wikipedians,
not any fancy experts, to add and edit the footnotes, and so it's
also an internal means of fact-checking
It seems that we all know that
footnotes makes articles much more credible—but why? Whatever
the reason, Wikipedians wouldn't want to say that it's
because the people cited are credible authorities on their subjects.
The dilemma
Wikipedia finds itself in, then, is that if it wants to establish
its credibility by reference to expert opinion, then it has no reason
not to invite experts to join in some advisory capacity. But
this is completely intolerable for Wikipedians.
epistemic (knowledge) egalitarianism
this is a doctrine about rights or authority,
not about ability
the power to declare society's
background knowledge is awesome, and that many consequential decisions,
including political decisions, are deeply influenced by that background
knowledge
the main philosophical reason for epistemic egalitarianism is, like
the reason for egalitarianism generally, the now-common and overarching
desire for fairness. The desire for fairness creates
hostility toward any authority—and not just when authority uses
its power to gain an unfair advantage, but toward authority as
such. That is, the most radical egalitarians advocate that
our situations be made as equal as possible, including in terms of
authority. But, in our specialist-friendly modern society, expertise
can confer much authority not available to non-experts. Perhaps
the most important and fundamental authority experts have is the authority
to declare what is known. This authority, then, should be placed
in the hands of everyone equally, according to a thoroughgoing egalitarianism
I support
meritocracy: I think experts deserve a prominent voice in declaring
what is known, because knowledge is their life.
Ultimately,
at the bottom of the debate, the deep modern commitment to specialization
is in an epic struggle with an equally deep modern commitment to egalitarianism. It's
Truth versus Equality, and as much as I love Equality, if it comes
down to choosing, I'm on the side of Truth.

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