Showing posts with label knowledge management. Show all posts
Showing posts with label knowledge management. Show all posts

Saturday, April 26, 2014

On the true nature of knowledge

@pickover suggests that these two books, in theory, contain the sum total of all human knowledge. "The Joy of Logic", he remarks (via @DavidFCox).

What They Teach You At Harvard Business School
What They Don't Teach You At Harvard Business School

Why is this wrong? Because knowledge doesn't follow the laws of elementary arithmetic. Adding two lots of knowledge together doesn't give you twice as much knowledge. (Does anyone really think that teaching children creationism as well as evolution will double their education?)

Knowledge is like light. When you add two light beams together, you may sometimes get more light. But you may also get puzzling patches of darkness. This is called interference. In high-school physics we learn that this is because light is a wave. If the two waves are out of phase, they cancel each other out.

(Curiously, uncertainty is also like light. When you add two pieces of uncertainty together, you may get less uncertainty. This is called hedging. Works best when the uncertainty is out of phase.)


Obviously these two books are out of phase.


On The Map
Off The Map
 

Related posts

Does Big Data Release Information Energy? (April 2014)

Saturday, March 30, 2013

From Enabling Prejudices to Sedimented Principles

In my post From Sedimented Principles to Enabling Prejudices (March 2013)  I distinguished the category of design heuristics from other kinds of principle. Following Gadamer (via Peter Rowe) I call these Enabling Prejudices.

Rowe also uses the concept of Sedimented Principles, which he attributes to the French philosopher Maurice Merleau-Ponty, one of the key figures of phenomenology. As far as I can make out, Merleau-Ponty never used the exact term "sedimented principles", but he does talk a great deal about "sedimentation".
In phenomenology, the word "sedimentation" generally refers to cultural habitations that settle out of awareness into prereflective practices. Something like the "unconscious". (Professor James Morley, personal communication)
"On the basis of past experience, I have learned that doorknobs are to be turned. This ‘knowledge’ has sedimentated into my habitual body. While learning to play the piano, or to dance, I am intensely focused on what I am doing, and subsequently, this ability to play or to dance sedimentates into an habitual disposition." (Stanford Encyclopedia of Philosophy: Merleau-Ponty)

This relates to some notions of tacit knowledge, which is attributed to Michael Polanyi. There are two models that are used in the knowledge management world that talk about tacit/explicit knowledge, and present two slightly different notions of internalization.

Some critics (notably Wilson) regard the SECI model as flawed, arguing that Nonaka has confused Polanyi's notion of tacit knowledge with the much weaker concept of implicit knowledge. There are some deep notions of "unconscious" here, which may produce conceptual traps for the unwary.

Conceptual quibbles aside, there are several important points here. Firstly, enabling prejudices may start as consciously learned patterns, but can gradually become internalized, and perhaps not just implicit and habitual but tacit and unconscious. (The key difference here is how easily the practitioner can explain and articulate the reasoning behind some design decision.)

Secondly, to extent that these learned patterns are regarded as "best practices", it may be necessary to bring them back into full consciousness (whatever that means) so they can be replaced by "next practices". 




Bryan Lawson, How Designers Think (1980, 4th edition 2005)

Peter Rowe, Design Thinking (MIT Press 1987)

Wilson, T.D. (2002) "The nonsense of 'knowledge management'" Information Research, 8(1), paper no. 144

Stanford Encyclopedia of Philosophy: Gadamer, Knowledge How, Merleau-Ponty

Wikipedia: Boisot's I-Space, Nonaka's SECI model, Tacit Knowledge

Thanks to my friend Professor James Morley for help with Merleau-Ponty and sedimentation.

Related posts: From Black Belt to White Belt (September 2009), Three Notions of Maturity (March 2013), From Sedimented Principles to Enabling Prejudices (March 2013)

Wednesday, January 30, 2013

Real Criticism, The Subject Supposed to Know

"Goodbye, Anecdotes", says @Butterworthy, "The Age Of Big Data Demands Real Criticism" (AWL, January 2013). Thanks to @milouness, who comments "Important concepts here about what is knowable!".  The article tries to link Big Data with Big Questions about the Big Picture, and what @Butterworthy calls The Big Criticism. From this perspective, Bill Franks' advice, To Succeed with Big Data, Start Small (HBR Oct 2012), is downright paradoxical.

But why would we expect Big Data to help us answer the Big Questions? Big Data is rather a misnomer: it mostly comprises very large quantities of very small data and very weak signals. Retailers wade through Big Data in order to fine-tune their pricing strategies; pharma researchers wade through Big Data in order to find chemicals with a marginal advantage over some other chemicals; intelligence analysts wade through Big Data to detect terrorist plots. Doubtless these are useful and sometimes profitable exercises, but they are hardly giving us much of a Big Picture. Big Data may give us important clues about what the terrorists are up to, but it doesn't tell us why.

A few years ago, Chris Anderson promoted The End of Theory, and published an article claiming that The Data Deluge Makes the Scientific Method Obsolete (Wired June 2008), although this may have only been an ironic reference to Fukuyama's earlier idea of The End of History. Claiming obsolescence seems like hyperbole, although scientific method has always been modified by technological progress. Even in mathematics, computer power and human brilliance have combined to crack some previously unsolved problems. See for example, Proof and Beauty (The Economist, March 2005).

Although @Butterworthy claims to have identified some critical ("Big Critical") questions, there seems to be only one real question - the dialectical question of quantity becoming quality. Are we on the cusp of aggregating utilitarianism into new tyrannies of scale? Are the numbers are so big, they leave interpretation behind and acquire their own agency? How much information and of what kind would you need to conclude something - for example, something like gender bias in the media?

A recent academic study looked at 2.4 million pages of newspaper and came to the conclusion that there was some gender bias. That's a lot of newspaper. It's like examining every single grain of sand in the forest for traces of ursine faeces. (In other words, looking for microscopic proof that bears defecate in the woods.) From a technophile perspective, Big Data seems to be raising the bar for scientific methodology: following this impressive piece of research, those who don't understand the concept of statistical significance can dismiss any smaller study - for example, one that merely studied thousands of pages - as unscientific anecdote. At a stroke, decades of careful analysis by feminists can be discredited because their sample sizes were too small by modern Big Data standards, and so there is now less scientifically credible evidence of gender bias than there was before.

Seriously, how many pages of newspaper do you have to read to convince yourself of gender bias? Clearly this is an example of Big Data getting in the way of the Big Picture. @Butterworthy clearly understands this danger, and sees the redemptive possibility of Big Crit (whatever that is) revitalizing the notion of critical authority and restoring some balance to the universe. I'm not sure I follow how he thinks that is going to happen. 


 Related post: Big Data and Organizational Intelligence (November 2018)

Friday, January 18, 2013

Beyond Personal Knowledge Management

@hjarche via @Cybersal says "I'll show the same thing many times and people have various interpretations of it. Sharing knowledge artifacts is not transferring knowledge." In other words, we don't actually share knowledge, what we share are documents and other artifacts that are supposed to contain knowledge.

If I send a document to Harold or Sally, they may or may not be able to extract some knowledge from it. There are many possible causes of knowledge impedance or attenuation, such as obscure language and specialized terminology, poor presentation, low motivation, and information overload. Even if either of them is able to glean some knowledge from perusing my document, what they get out may be quite different from the knowledge I thought I was putting in. Their interpretations depend on many things: their situation, their prior knowledge, beliefs and values, their expectations about what I'm trying to say, and their ability to read between the lines. (Even my closest friends and associates, who I imagine share a lot of my assumptions, read my documents in ways I find surprising, which is why I always greatly value their comments.)

Harold promotes something he calls Personal Knowledge Management, which describes knowledge management as an Input-Process-Output system.


  • Input (Seek) - we gather knowledge from our environment, including other people
  • Process (Sense) - we interpret, personalize and use knowledge
  • Output (Share) - we pass on our knowledge to other people


Harold talks about Network Learning, which seems to be about taking advantage of digital connectivity and embedding the Input (Seek) and Output (Share) into a wide social network. What I don't see in Harold's account of Network Learning is any sense of collective sense-making - knowledge emerging from the collaboration rather than being generated by one person. I'm also troubled by the implication that knowledge is produced by thinking rather than doing, since I think the most useful knowledge is what emerges from practice.


So while there is undoubtedly a great deal of value in Harold's approach, I think it underplays some of the social and practical elements of knowledge management and organizational intelligence.



Harold Jarche's website: Personal Knowledge Management, Network Learning

See also Jose Baldaia, Who tells a story transfers tacit knowledge and creates new (May 2012)


Places are still available on my forthcoming workshops Business Awareness (Jan 28), Business Architecture (Jan 29-31), Organizational Intelligence (Feb 1).

Thursday, May 10, 2012

Leadership and Organizational Intelligence

Chief Knowledge Officer

Joseph Goedert, Expert says it's time for Health Care to create ‘Chief Knowledge Officer’ position. Health Data Management, Oct 2011

Chief Learning Officer

CLO Magazine

Josh Bersin, Today's Chief Learning Officer (November 2010)

"A few years ago I wrote an article about how the CLO is really three people:  A Chief Culture Officer (driving engagement, learning, and collaboration), A Chief Performance Officer (driving employee performance, alignment, and skills);  and a Chief Change Officer (vigilantly driving change, seeing the future, and helping the CEO and other leaders transform the workforce as the business and workforce changes).  Today, more than ever, the CLO must be all three."

Chief Sensemaking Officer

Peter Flemming Teunissen Sjoelin, Making Sense: One of the Components of Achieving Holistic Management (Jan 2011); Holistic Management in a Context of Enterprise IT Management and Organizational Leadership (May 2011)

Chief Collaboration Officer

Morten T. Hansen, Scott Tapp, Who Should be Your Chief Collaboration Officer? HBR Oct 2010

Lydia Dishman, Why Your Company Needs A Chief Collaboration Officer. Fast Company, May 2012



Is this several different (but overlapping) positions, or several labels for the same position?  I believe these are all aspects of Organizational Intelligence, and call for coordinated leadership. That doesn't necessarily mean a single position, but certainly not a set of disconnected or rival initiatives.


And who will take such positions? Hansen and Tapp suggest that the responsibilities should be added to one of the existing C-level roles - probably one of the following five.
  • The current CIO. 
  • The current HR head. 
  • The current COO. 
  • The current CFO.
  • The current head of strategy.
I agree that organizational intelligence might reasonably be added to any of these disciplines, but it would undoubtedly represent a radical shift for the traditional disciplines that dominate these functions. Leadership indeed.


Wednesday, May 9, 2012

Can we manage individual knowledge?

Vasily Ryzhonkov asked a couple of interesting questions on a Linked-In discussion.

As I understand it, Vasily's first question was whether "knowledge is a human faculty, and totally belongs to human being a justified true belief and can be managed only by individual". There always seems to be a difficulty in relating individual cognitive capacities with collective cognitive capacities, but my own view is that it does make sense to talk about the collective knowledge of a group or organization, and that this is something that can be managed.

See my post Does Organizational Cognition Make Sense (April 2012).

An important issue for knowledge management in the enterprise is how the organization collectively distinguishes between justified true beliefs and unjustified false ones. (This is one of the many reasons to care about organizational intelligence.)

Vasily's second question was whether it is possible to manage somebody's knowledge. There are all sorts of professions that involve a combination of communication and influence, and these could surely be regarded as attempts to manage the knowledge of a target audience. For the sake of argument, I adopt Fayol's definition of management: to forecast and plan, to organize, to command, to coordinate and to "control" (i.e. monitor and adjust).

Here are four examples that I should regard as attempts to manage the knowledge of individuals, since they all involve some degree of planning, organization, monitoring and adjustment.

Firstly, schools. We pay schoolteachers to manage the knowledge of our children.

Secondly, an apprenticeship scheme, which puts an inexperienced person alongside an experienced person, with the explicit intention of transferring knowledge from one to the other.

Thirdly, a censorship and indoctrination scheme, whereby a government interferes with communications to its citizens, in order to shape their knowledge.

And fourthly, a covert public education scheme, which inserts information into entertainment programmes. (It is said that the popular UK radio programme "The Archers" was given stories about farming practices by the British Ministry of Agriculture.)

Let me anticipate three objections to both of these answers.

The first likely objection to both of my answers is whether that counts as managing, or whether we should use another word, like tending or nurturing or coaching or something else. But to the extent that we give management-style targets to teachers, based on the performance of their pupils, the word management seems to be an accurate description.

The second likely objection to both answers is a practical one - to what extent can someone effectively manage their own knowledge, let alone someone else's. Obviously we can debate how successful any of these might be, but surely we can't refuse to call something management simply because it doesn't always work. Football managers are still called managers, even when the team loses.

The third likely objection is an ethical one. Clearly there are ethical problems, especially if managing knowledge slides into manipulation and spin. (Steve Jobs was often praised for his skill at "reality distortion".) But there are many other kinds of management that also have ethical implications. So that doesn't make my answers incorrect, just troubling.


Original discussion on Linked-In: http://lnkd.in/VpvjsK

Thursday, March 24, 2011

The Wisdom of the Tomato

Various people have tweeted the following aphorism.

Knowledge is knowing a tomato is a fruit. Wisdom is knowing not to put it in a fruit salad.

Please permit me to quibble with this aphorism. Classifying tomatoes as fruit is merely information. This classification is supported by data, such as the observation that the tomato contains its own seeds. Knowing not to put it into a fruit salad is a culinary best practice, based on a series of social conventions about the proper constitution of fruit salad and its place within a meal. So this is knowledge, or what is sometimes called received wisdom. However, innovation often involves disobeying social conventions and surprising those who rely excessively upon received wisdom. For example, how did chefs discover that it was okay to put flower petals into salads (next practice)? So courage is knowing that you are not supposed to put tomatoes into fruit salad, but doing it anyway. And real wisdom is not inflicting such gross culinary experiments on the wrong people at the wrong time in the wrong way.



Wikipedia attributes this aphorism to the Irish rugby captain Brian O'Driscoll. Various interpretations can be found in the comments to Brendan Cole's blog What did BOD mean? (Feb 2009)

On the Unbelievable Truth (Series 10 Episode 5), the @RealDMitchell rants about whether a tomato is a fruit or a vegetable. He claims that the US Government taxes tomatoes as vegetables, and regards this as more authoritative than mere science.

See also my post Co-Production of Data and Knowledge (Nov 2012), Alternative to the DIKW Pyramid (Feb 2020)

Updated 29 January 2013. Link added October 2025.

Wednesday, February 2, 2011

The Authorship of Method

Working with organizations is a rich and complex domain, and a large number of methods and frameworks have been developed to help people negotiate this domain. Over the past twenty years or so, I have myself developed or co-developed a number of methods and method fragments.

People may have many different reasons and motivations for developing methods. For my part, I cheerfully acknowledge that my own work has partly been motivated by the desire to earn an honest crust, to find a way of using my talents to feed my family and pay the bills. But I have also been motivated by the belief that this work is worth doing, that by promoting my own ideas and those of other people, I am contributing to making organizations healthier and more viable.

One of the indicators of successful methods is that they are widely adopted and used, and method authors typically aspire to this kind of success. But this kind of success causes new difficulties for its authors, as a broad community of users start to extend and reinterpret these methods for a much wider range of situations than the original authors may have anticipated.

At this point, the authors may wish to impose some authorial control over the evolution of the method: they try to assert a canonical version, to enfranchise carefully selected followers as the only ones approved to make improvements, and to repudiate any other developments as heretical.

I came across this phenomenon many years ago when I wrote an article about Soft Systems Method (SSM), interpreting a certain practice as consistent with SSM. Following my article, Checkland clarified his definition of SSM so that my example would no longer count as valid SSM. (Lakatos would call this "monster-barring").

Obviously there are commercial motives for doing imposing this kind of control - the authors wish to maintain a monopoly or franchise over consulting and training revenues, and to protect the brand from dilution or fragmentation. But for some of these authors, there also seems to be a lot of ego involved in this process.

However, there are also many reasons for relinquishing this kind of control. A key milestone for a notable method is that it gets its own article in Wikipedia, but Wikipedia policy requires some degree of independent coverage and commentary, rather than being based purely on the writings of the method author and his immediate associates. (Although there are many articles in Wikipedia that fail to satisfy this policy.)

Where methods are created by two or more co-authors, we often find that their followers form into rival camps. For example, the key early documents on Information Engineering were written jointly by Clive Finkelstein and James Martin, but many subsequent documents credited either Finkelstein or Martin as the sole author of the method. SSM has also undergone this kind of split - I recently heard someone talking about their experience with SSM and affirming that this was the Wilson version rather than the Checkland version.

One method author who is particularly vigilant in enforcing his brand is Dave Snowden, popularly known as the author of the Cynefin method. In his document on The Origins of Cynefin (pdf), Snowden traces some of the changes that the Cynefin method has undergone since he first invented it, and acknowledges the contributions of several collaborators, including Max Boisot and Cynthia Kurtz. Kurtz and Snowden wrote a paper in the IBM Systems Journal (2003), which must be the paper most commonly cited by other authors as the source of Cynefin. But Snowden doesn't like it when anyone names Kurtz as one of the co-originators.

By objecting to what he regards as an incorrect description of Kurtz's contribution, Snowden is not only claiming to be the prime author of Cynefin, he is also claiming to be the prime authority on the history of Cynefin. But given the complex identity of Cynefin as an evolving cluster of ideas and techniques, it is surely legitimate for a historian of ideas to offer an alternative interpretation of this history. (Just as if we were writing a history of the Beatles, we should of course treat Paul McCartney's account of the creative forces as an important source, but we should not assume that McCartney's account is the last word on the subject.)

Authorship itself is not Simple, as Barthes and Derrida and Foucault have shown. If a method is to be any good, it will pull together ideas and fragments from previous methods, so there will be many voices speaking through a given text. The most successful method authors (James Martin, John Seddon, John Zachman) have always reused and relabelled and reframed old ideas, even when they haven't always appreciated their provenance. (See my post Does Metaphysics Matter? about Zachman's curious misunderstanding of reification.) Tracing the true authorship of a method is Complex, and the relationship between cause and effect can only be perceived in retrospect, if then.


Afterword: At the same time as I was writing this, and perhaps prompted by the same events, Cynthia Kurtz was writing her personal account of the history of Cynefin: Whose Truths Are These? Her account confirms just how complex (and perhaps ultimately unanswerable) are these tricky questions of method authorship.

Tuesday, March 9, 2010

Knowledge Claims

@JDeragon blogs about the emergence of a "know" profile. He identifies four types of knowledge - intellectual, social, creative and spiritual - and advocates the construction of individual profiles that express our individual "knowledge inventory" across these four types of knowledge.

The metaphor of "knowledge inventory" is based on his assertion that people are containers of knowledge. But what if people are NOT "containers" of knowledge, asks @EskoKilpi, who argues that one of the main challenges for knowledge management is bridging the gap between knowing and acting.

I fully concur with Esko's objection to the "container" metaphor, and I agree that the relationship between knowing and acting is important - in fact it's a critical connection in my model of organizational intelligence. However, I think we have to be careful not to imply that the gap between knowing and acting can ever be completely closed. There is always a need to act under conditions of uncertainty.

Even if we were willing to regard knowledge-as-content, Jay Deragon acknowledges that this knowledge would need to be measured and vetted over time. So the best that we could possibly expect from a set of knowledge profiles is a collection of knowledge claims, together with some information that would allow us to evaluate a given claim. Does this person really know everything about project management? Does this medical researcher really know that this procedure is safe and effective?

When I pointed out that I can claim knowledge about all sorts of things, and asked who is the best judge of how much I really know, @oscarberg replied that "real life is the best judge".

But since we don't have a reliable way of interrogating real life in real-time, we must surely treat all knowledge-claims with caution.

Wednesday, February 10, 2010

From "Organizational Intelligence" to "Ability to Execute"

There is a common organization structure found in many large professional firms, including global consultancies and the big industry analyst firms.



For any important topic, we may suppose that the firm employs some of the most knowledgeable people in the world, who are available to give presentations to major clients as well as keynote speeches at international conferences. These high-profile experts attract lots of business to the firm, but of course they don't have time to get heavily involved in the day-to-day work, which is mostly executed by their less famous (and less expensive) colleagues.

It is interesting to consider how this structure affects the overall capabilities of such a firm for handling different kinds of client problem. Where a client problem fits neatly within a single knowledge domain, then we might expect it to be handled reasonably efficiently and effectively, according to the "best practice" principles defined by the centre of excellence for that domain, and with some benefits from the economies of scale and scope. But for large and complex problems spanning multiple knowledge domains, the lack of coordination between the knowledge silos seriously impairs the ability to execute, and the economies of scale are outweighed by the diseconomies of scale.

Ironically, it is precisely these large complex problems where the large global firms claim superiority over their smaller more agile competitors. But this claim is not compatible with an organizational structure based on "best practice". The challenge here is not just building more effective knowledge management platforms (with fancy Enterprise 2.0 software) but architecting the organization to achieve real organizational intelligence.

Monday, January 18, 2010

When does Communication count as Knowledge Sharing?

Following my post Intelligent Knowledge Management, taking issue with @snowded's "knowledge sharing" agenda, I have read a few more pieces about knowledge sharing, including Patrick Lambe's piece If We Can’t Even Describe Knowledge Sharing, How Can We Support It?. See also Mark Gould, Knowledge sharing: it may not be what you think it is.

Patrick describes a person with a life-critical illness, being told stuff by various healthcare professionals and others in what he describes as "a series of encounters with intersecting knowledge worlds", and has drawn a good diagram of this process. Patrick seems to regard it as a complex example of knowledge sharing. But in what sense does this count as sharing? To me it just looks like communication - translating specialist knowledge into accessible information.

In many contexts, the word "sharing" has become an annoying and patronizing synonym for "disclosure". In nursery school we are encouraged to share the biscuits and the paints; in therapy groups we are encouraged to "share our pain", and in the touchy-feely enterprise we are supposed to "share" our expertise by registering our knowledge on some stupid knowledge management system.


But it's not sharing (defined by Wikipedia as "the joint use of a resource or space"). It's just communication.

Tuesday, December 15, 2009

From Knowledge to Strategic Advantage

@jhagel asks Are Your Sources of Strategic Advantage Eroding? and points out how strategic advantage can be eroded if knowledge stocks are allowed to depreciate. Thus maintaining strategic advantage depends on intelligent processing of rich and diverse knowledge flows.

1 The first requirement is access to good knowledge flows. Hagel describes this as a positional advantage, but I think it is more accurate to describe this as a relational advantage - it is about our strategic relationships with sources of knowledge.

2. The second requirement is an ability to make sense of these knowledge flows. On the one hand, this means filtering and ranking, to avoid getting overwhelmed or spreading resources too thinly; but on the other hand, it is important to remain alert to weak signals that might suggest a change in direction.

3. Generating and leveraging knowledge (especially tacit knowledge) depends on trust-based relationships with knowledge-flow participants, both inside our own organizations and across our ecosystems. We need to engage (enable + encourage + empower) people into a learning process that is focused on "challenging performance issues".

4. Communicating and disseminating new capability-based knowledge through the organization (and out into the ecosystem) becomes the critical metacapability.

Hagel claims that "This new form of strategic advantage benefits from network effects and increasing returns." Now it may well be true that, under favourable circumstances, the more these knowledge flows and metacapabilities are exercised the more robust they become. However, this is not a classic network effect, and it is by no means certain that the positive feedback loops will outweigh the negative feedback loops. One limiting factor is organizational torque, defined by @liman as "when an organization fosters grass-roots collaboration externally, but has a resistant internal structure/philosophy". In other words, some modes of organizational change twist the organization out of the control of its legacy leadership.

Monday, August 4, 2008

Peer Review in the Dock

Tonight's Science programme on BBC Radio 4 was critical of the peer review process, in which scientific articles are filtered for publication according to the comments of other researchers in the same field. [Peer Review in the Dock, 4 August 2008]

The purpose of peer review is to give us confidence in the quality of published scientific research. Like many other social institutions, it has well-known weaknesses as well as strengths. [BBC News, Science will stick with peer review]

I have often been asked to provide peer reviews on articles for journals and conferences. Sometimes I find I know much more about the subject of the article than the authors, or at least some aspects of the subject. Even when my knowledge is less, I can usually find some areas of weakness or confusion in the article, demanding (in my opinion) either a significant re-write or complete rejection.

Having gone to the trouble to provide these reviews, I used to be shocked when I discovered that papers sometimes slipped through to publication without the identified flaws being adequately corrected. Experienced authors (or their supervisors) know how to game the system, and most journals and conferences simply don't have the resources to prevent these games. Some years ago I wrote a critique of this process and identified a number of negative patterns.

The BBC programme this evening identified several more, including the famous institution bias and the publication bias. The latter is particularly important for research that involves sophisticated statistics (such as medical research), because if only publishable data are included in the analysis, then the publication criteria may themselves distort the findings. The publication bias also affects the opinions of so-called experts, whose assumptions will have been reinforced by the papers they have read.


Related post: Trahison des Clercs - AntiPatterns of Peer Review (July 2004)

Update - Further links

Liam Kofi Bright and Remco Heesen, The Perfect Time to Reform Peer Review (BSPS 2022)

Remco Heesen and Liam Kofi Bright, Is Peer Review a Good Idea? (British Journal for the Philosophy of Science 2021) 

Friday, October 21, 2005

Overstepping bounds

originally posted by John

Richard's blog Double Bluff raises, as he says, some interesting questions about the boundaries of trust. And while the topic of his blog, the technology of warfare, is of concern to us in these times of terror and insurgency, the boundaries of trust are all the while being eroded in many other aspects of our lives. And in pharmaceuticals, just as in war, transgressions of trust come back to bite us. Sometimes quite savagely.

In the west the bodies responsible for clinical testing define a discrete trust space in which tests must be carried out. The nature and aims of the test, the statistical methodology, control mechanism and review processes must all be made clear. The consent of those taking part must be fully 'informed'. There must be no coercion to take part, no 'undue' inducements to do so and no penalties for refusing to take part. Along with test-specific requirements, these, roughly, are the boundaries of the trust space for clinical tests in the west.

Needless to say the don't apply in the third world. Strange as it may seem (in trust terms at any rate if not in commercial terms) authorities in the west readily accept results of tests done in the third world when it comes to licencing drugs. So boundaries become meaningless when the mega rewards of getting a new drug accepted in the west are at stake.

In Kano, in northern Nigeria in 1996, in the middle of an epidemic of bacterial meningitis, Pfizer carried out a test on their new drug, Trovan. They used children with meningitis who were undergoing routine treatment. As a result in 1997 Trovan was approved by the US FDA (Food and Drugs Administration) but, oddly, not for use on children and not for epidemic meningitis. After less than two years' of highly profitable prescription, Pfizer removed Trovan from the market amidst reports that the drug produced 'hundreds of cases' of liver toxicity and 'several' deaths.

Third world tests, first world deaths. Drugs, like bombs, kill us just as readily as they defend us. The boundaries of trust are our only real protection.

See also: Marcia Angell's review of The Constant Gardener (NYReview, October 6th, 2005)

Wednesday, March 16, 2005

Off-Label as Samizdat


One of a series of posts about Off-Label

In a pharmaceutical context, Off-Label refers to drugs being used in ways that are not approved by the regulators and cannot therefore be printed on the product label or officially promoted by the drug company. More generally, it refers to any unauthorized or emergent use of a product or service. In this blog posting, I shall explore the implications of off-label for knowledge management.

Robert Stern describes some of the difficulties involved in disseminating Off-Label research data. There are clearly some potential conflicts of interest, and doubtless sometimes there is natural suspicion of the motives of the drug companies. However, the result is that data describing the behaviour of certain drugs in certain contexts are not available.

This means that many good uses of drugs may be suppressed by regulators, or self-censored by drug companies in order to get speedy approval. In a separate post, Robert Stern quotes a physician as saying "Often the drug companies will under-dose their labeling to get it through the FDA." So does the physician have some other way of finding out an appropriate dose, or is it all done by trial and error?

If the official channels are blocked, how does the medical community share practical knowledge about Off-Label. Is this all done by unofficial samizdat and word-of-mouth?

There is a newsletter for sceptical patients called What Doctors Don't Tell You. Perhaps there should be, if there isn't already, a newsletter for doctors called What Drug Companies Don't Tell You.

Monday, September 13, 2004

Workflow Learning

Jay Cross of the Workflow Institute raves about the component-based business (the subject of my 2001 book), which he calls a Business Singularity. He identifies some interesting consequences for what he calls Workflow Learning.

Workers are learning in small chunks delivered to individualized screens presented at the time of need. Learning is being transformed into a core business process measured by Key Performance Indicators.
This prospect raises interesting questions for what we might call the Architecture of Knowledge. If workers learn in small chunks, how can these chunks be assembled into a coherent body of knowledge? How does the way the work is decomposed between workers affect the learnings that are accessible to them?




In response to Jay's comment

Doesn't the underlying Business Process Management and Business Rules structure the KM as much as needed? The work itself lends the coherence, but some external taxonomy.

In my view, the structure provided by the Business Process Management and Business Rules is usually either underdetermined or overdetermined. The chunk is polymorphic, and takes on a different meaning according to the context in which it is framed.


Just because the workers digest chunks doesn't mean the chunks aren't part of a larger entity.

Indeed they may be part of a larger entity, but this doesn't happen by magic.



Think about the way a film director puts together a film. The actors may not know how their scene fits into the whole until they see the final cut. (Indeed, some directors deliberately leave their actors in the dark during the shoot.) Or think about the way a composer/arranger puts together strands of music. Composition/orchestration/editing is a skilled process, which the actors/musicians cannot always second-guess.



So if the work is distributed - perhaps across different organizations and locations - there is no guarantee that the coherence of the work is visible to the individual worker. Indeed, the composition of business processes out of services is one of the key challenges of the service economy. The point I was making here is that this composition also applies at the level of knowledge management and learning; and the possible fragmentation of knowledge is a serious issue.



More on this in my SOAPbox blog.



Monday, May 17, 2004

Knowledge Reuse and FAQ

A body of knowledge often contains a (hyper)document called FAQ - "frequently asked questions". But the word "frequently" is often a lie. There are three possibilities.

Never asked questions. Here is some miscellaneous information we want to put out, which we didn't find anywhere else for. We have made up some phoney questions, to make it appear as information pull instead of information push.

Once asked questions. Here are some obscure and awkward questions which we've been asked once, and hope never to be troubled with again, so we'll dump the answers here.

Genuine reuse. We have identified some common threads among the many questions we have been asked, and designed some generalized answers.


FAQ often represents a transitional stage in the production of knowledge, somewhere between adhoc and fully commoditized. FAQ is inevitable, because the fully commoditized knowledge always leaves something to be desired. Thus properly interpreted FAQ documents may expose some misalignment between the production of knowledge and its consumption; although they are often carefully composed in an attempt to cover up any such misalignment.

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