The KM / IM Debate

I don’t really see any worthwhile debate – the buzz of turf-wars may keep the subjects in the headlines, but there is no definitional problem not already adequately sorted by the data > information > knowledge > wisdom stack. (Thanks to David Gurteen’s tweets prompting this post.)

Anyone with strong allegiance to any one part of the stack will widen (blur) their definitions into the adjacent layers, but anyone interested in the whole stack can see worthwhile (pragmatic and valuable) distinctions, each being a layer of patterning built on the previous layer.

  • data – is about significant difference – bits and bytes being distinct from one another, at any level of granularity from fundamental physics upwards to whole books and libraries.
  • information – is about the significance of those data differences, their semantics – what the patterns of data mean.
  • knowledge – is about how that information is applied to add value, valuable patterns of use, applied information.
  • wisdom – is about understanding (knowing, experiencing, appreciating) value and the fact that it depends on how the whole stack works, and the pragmatic need to balance interests and priorities across (two-way) interactions between all levels of the stack. A more “holistic” view, if that’s not a dirty word.

Personally, like anyone else who’s given the matter any thought I guess, the aims are always towards the higher level – wisdom – whatever our (current) level of activity as a practitioner. In my particular case as an engineer I started and worked for 20 years in the applied space – learning and using knowledge of how to apply information to specific ends. It’s all about “decision-support” of course – all worthwhile activities involve decisions, so that truism in itself doesn’t add much to any definitions. One of the things you learn – wisdom you gain – is that those practitioners in the data and information layers can, by inadvertent presumptions about decision-making and use-in-action, create constraints on usage in the knowledge layers. So for the last 12 years or so, I shifted my focus down a couple of layers to understand the presumptions and how (unnecessary) constraints can arise.

I have to say in the process, I’ve developed a huge respect for librarians. Anyone who thinks it’s “just” thorough record keeping – some clerical admin task – misses the need for good strategies and architectures for how data, meta-data, information and relations between these are organized. We benefit from some types of “constraint”. The more virtual our libraries become, the more we need to avoid librarianship becoming a dying art.

Ubiquitous, real-time, interactive connectivity is not necessarily entirely good in and of itself.

Mobile McLuhan

Piece by Peter Benson in Philosophy Now (posted on Facebook by ex-MoQer David Morey) – Marshall McLuhan on the Mobile Phone.

Unsurprising to find McLuhan on the money when it comes to the social effects of our communications age but, for me, a couple of interesting points on value and memetics.

Print is the technology of individualism” (The Gutenberg Galaxy pp.157-8) whereas with [mobile technology and the net], the tendency is once more towards interconnected thinking in a community of minds, and so perhaps less ‘free ideation’.

Less free, notice. It’s the usual Darwinian call for evolutionary balance between fidelity and fecundity. If it is too easy to copy patterns of information in hi-fidelity it is harder for mutations to be introduced in ways that create new value. Too hard is obvious, but too easy is not good. Less is more. Life’s just complicated enough. McLuhan continues:

It is important to recognize the subtlety of McLuhan’s views. He is not saying that modern technology distorts an original human nature, which must be protected from such distortions. Instead, from the moment humans began to create tools, our nature was shaped by the tools we used. The silent reading of texts proliferated after Gutenberg’s invention. This activity is not ‘natural’, in the sense of resulting through evolution from the necessities of survival; but it can be regarded as having value, conferred on it by our judgement as individuals and as a society. [His emphasis]

It is entirely possible that a future society could reverse this judgement; but in the interim we need to give consideration to the potential change in our values due to actual changes in our dominant communications media. [My emphasis]

Did we ever need a little conservatism to moderate mediation in the mix. The art of editing.

The Wrong Boson

Interesting, after all the press buzz last week about possible hints and indications that might suggest the speculative Higgs Boson (all designed to sell Cox’s book in time for Christmas no doubt), that this week the paper published indicates a new “Chi_b(3P)” boson, whatever that is.

What is really interesting, given yesterday’s post about the workings of science, is the paper itself appears as a 17 page PDF, 13-1/2 of which are the acknowledgements and references to the LHC Atlas team 2590 individuals (excluding deceased!) and 212 institutions by name. What is the point?

Bad Scientism, a Messy Business

I read this Ben Goldacre piece a couple of weeks ago. The problem one always has to ask is … is this kind of bad science accidental or in some sense deliberate – a skilled incompetence either by the practitioners or their managers / editors / reviewers, or both in a kind of tacit collusion. In situations of complex human endeavours some hypocrisy is inevitable, to balance motives and goods across multiple levels, and a degree of trust is therefore also inescapable. Science is no different, taken as a whole “business”.

Personally, I’m more against bad scientism, using science badly in situations that are far from scientific – rather than good or bad science per se. With infinite time and resources you could argue all situations can be reduced to science, but the reduction can discard the real world value. Statistics is of course one of those techniques used to bring the vagaries of human behaviour into the scientific space in quantifiable chunks. This adds another level of complexity to the whole exercise leading to more possibilities of evaluating the wrong things, and/or evaluating them wrongly.

Ben’s story above is about the statistical methods, this story today in The Scholarly Kitchen (via David Gurteen and Stephen Downes) is about choosing the wrong inputs for the wrong motives – citations, again. Proves the point that science is a messy business, parts of which are far from scientific.

And of course, the “Measuring the Wrong Things” headline is one a long line including Einstein’s “Not everything that counts can be counted.”