Making Sense of Human-Machine Symbiosis

April 12, 2009
Cynefin Model

Cynefin Model

A NUMBER of people have remarked to me that Dave Snowden’s title for his forthcoming talk to ISKO UK on 23 April 2009 is less than informative. Well, it depends on how well you know his work since he moved on from IBM’s Institute for Knowledge Management and the Cynefin Centre to focus on his own company, Cognitive Edge Pte Ltd.

I’m no expert in Cognitive Edge’s pioneering approach, but maybe I can shed some light on themes he might address in his talk by describing the context within which I apprehend it, and making a few other links along the way.

The processes of organizing and sharing knowledge are complex because people are involved in both the input and the output. However much we try to codify and structure both, there is always that residue of ‘fuzziness’ – un-order – which Checkland in his Soft Systems Methodology described as giving rise to ‘ill-defined’ or ‘soft’ problems.  Although the computer can help us greatly with codification and structure, it has been virtually useless in the face of soft problems – until perhaps the advent of Web 2.0.

As we are increasingly obliged to acknowledge, organizations are comprised of both formal and informal relationships, and it is often the latter which provide the real channels for knowledge and information flow. But how do we tap into these informal networks, and even if we can, how do we make sense of and derive value from what we find? Major shifts and trends (good and bad) often start as ‘weak signals‘, almost undetectable by conventional means. How can we spot these early enough to be able to discourage bad trends and encourage good ones?

Cognitive Edge addresses these questions within an organization by collecting narrative and organizing and analyzing it for meaningful patterns using its open source methods supported by its proprietary software suite SenseMaker. It should be readily apparent that such early intelligence could prove vital to effective decision-making in many situations where the degree of risk is not clear.

Less readily apparent perhaps, is that knowledge organization has a key role to play in this scenario. As UCL alumnus Patrick Lambe says in his excellent book Organising Knowledge: Taxonomies, Knowledge and Organisational Effectiveness:

“Categorisation is, of course, fundamental to the management of risk. Different kinds of risk must be identified and grouped together based on origin, severity or remedy. Risk intelligence systems need to identify the signals or clues that would indicate particular categories of risk and put in place monitoring mechanisms (strategic early warning systems) so that these signals are picked up whenever a risk is emerging (Gilad, 2001).”

Moreover, it does not take a huge leap of the imagination to suggest that if software such as SenseMaker can discern patterns and trends even when weakly detectable, then it could presumably be employed in bridging the gap between formal vocabularies and newly emergent terms and concepts. Such tools are needed to help us move beyond the spurious divide between the formal taxonomic ‘elite’ and the folksonomic lumpenproletariat which is advancing the cause of neither party.

Interesting thought: If software like SenseMaker had been deployed at Lloyds, would they still have gone through with the HBOS takeover?

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KO and the Enterprise of the Future

April 6, 2009

KM World recently ran a short but spot-on article entitled The Future of the The Future: An opportunity for real change by Art Murray. A couple of short excerpts should suffice to convey the flavour:

In today’s economic climate, it’s clear more than ever—traditional business models no longer work. They are too slow and impede the flow of knowledge—the exact opposite of what is needed to succeed in a turbulent, high-risk economy.”

“At the very least, we need to momentarily halt the process, introduce some serious changes and reboot. Here’s a partial list of specific transformations, any one of which will introduce a new way of doing business that will help propel you forward.”

Murray’s five transformations (on which he elaborates) are:

  • Make the move from hierarchies to networks once and for all
  • Make the cultural shift from silos and knowledge hoarding to openness and knowledge sharing
  • Move from slow, random learning to a systemized approach for fast learning
  • Become fixated on systemic improvements rather than point solutions
  • Move from saying, “That’ll never work here,” to “Let’s find a way to make it work.”

A better checklist of survival initiatives I cannot imagine. Similar sentiments are being expressed elsewhere, from Clay Shirky’s Ontology is Overrated a few years ago, to the challenge posed by Web 2.0 to structured information management disciplines like Records Management  (see e.g. Steve Dale’s recent blog entry EDRM and Web 2.0 – where two worlds collide).

The question is, where does this relentless drift towards the informal, the unstructured and the ‘wisdom of crowds’ leave the highly structured world of KO?




How the Semantic Web Will Change Information Management: Three Predictions

October 25, 2008
Semantic Web Stack

Semantic Web Stack

I have doubts about “the wisdom of the crowd” as promoted by various writers on social networking tools. But I have no such reservations when it comes to the enhanced wisdom of smaller groups of connected individuals. Yes, ‘two heads are better than one’ often, and three, four or more can be even better in the right circumstances.

In my Knowledge Architecture workshop which I run for Aslib, I make sure that delegates hear me talk for five or so minutes about the Semantic Web (SemWeb, or Web 3.0 if you must), and in particular the role which ontologies will play. I do this by showing them a block diagram (above right) of the structure of the SemWeb as devised by the W3C. But now, I realise that it’s just not enough to describe the structure, and that I need to explain how it will fundamentally change how we can access Web-based information.

ISKO UK member Silver Oliver has recently had an article published in Freepint’s FUMSI network with the title I have used for this post. Despite the millions of words which must have been written to explain what the SemWeb is about, Silver’s explanation is the best account I have yet come across of how SemWeb KO techniques will change our approach to information management.

Read it – or regret it! I’ll certainly be including a reference to Silver’s article in future runs of my workshop.



Wikipedia’s approach to categorization

September 22, 2008

I was intrigued by Silver’s posting asking for information on Wikipedia’s approach to categorization. Since I was busy at the time, I hoped that someone else would respond, but no-one has. So in a brief spare moment, I have tried to work out what they’re doing myself.

Let’s say that it’s not obvious! There is plenty of documentation here and here and elsewhere. Perhaps the most significant clue to what they’re doing lies in the latter page. They say:

“Each Wikipedia article can appear in more than one category, and each category can appear in more than one parent category. Multiple categorization schemes co-exist simultaneously. In other words, categories do not form a strict hierarchy or tree structure, but a more general directed acyclic graph (or close to it; see below).”

The ‘see below’ refers to an image showing a representative sample of the category structure and this is where we get somewhat contentious. This image looks to me like a mish-mash of hierarchical and associative relationships (some of which are questionable IMHO) which is far closer to the realm of ‘real world’ perceptions than the neat, clinically precise representations of classic KO. Is this an example perhaps of ‘Freely Faceted Classification’ as described to us by our Italian colleague Claudio Gnoli at our Ranganathan Revisited event in November 2007? Or is it something else?

Taking a specific example, I used the CategoryTree tool to explore a section of the Wikipedia category structure. I specified ‘en.wikipedia.org’ as the Wiki and ‘transportation’ as the category in order to examine how ‘trains’ are represented. I made the facile (but not unwarranted) assumption that ‘trains’ would appear somewhere as a lower-level category of ‘Transportation’. Indeed it does, being reported as Transportation > Rail Transport > Trains.

What you note in passing though is interesting. ‘Transportation’ itself has parent categories ‘Industries’, ‘Technology by type’ and ‘Travel. Fair enough, I suppose, given that we embrace polyhierarchy and acknowledge the need to provide for multiple access routes to specific concepts. However, ‘Rail Transport’ and ‘Public Transport’ occur adjacent to each other at the same level. Hmmm. Some overlap of categories methinks, since I’m not aware of any form of rail transport which isn’t also public (except freight, but that’s out-of-scope for our purposes). But then, if you examine the sub-categories of ‘Public Transport’, you find that the principle of differentiation is quite different and at a higher level.

Screen shots of the CategoryTree hierarchies I examined are provided below so that anyone interested can peruse them before perhaps investigating the question for real online.

Conclusion? The Wikipedia categorization system reflects but does not consistently apply the principles of KO as expounded in the formal literature. It is nevertheless interesting because it might well represent what results when folksonomy meets formal KO and agrees to a compromise.

If anyone has the time and patience to analyze this interesting phenomenon further and comment on it, then I for one would be grateful. And I’m sure Silver Oliver would too, since he and his colleagues at the BBC have invested considerable effort in building a system which utilizes Wikipedia topics as subject identifiers for their own internal use. Obviously, they would like to know if Wikipedia’s categories can be utilized ‘as is’ or whether they need to embark on a categorization exercise of their own.