Posts Tagged ‘information scent’

QR Codes and You – A Match from Heaven or Just a Fad?

March 24, 2011

QR Codes are something you are going to enjoy getting used to – from booking seats for a concert to reading a business card, QR codes are a way to shorten the distance between you and something you want, and all for free via your smartphone.

This particular code takes your smartphone browser to my website, but then what were you expecting? – Tickets to the MOMA?

However, keep your eye open and your phone handy and you will see coupons, special deals, and concert tickets on QR codes splattered across bus-shelters, walls, and magazines.

A savvy person might even consider using them at work to link to instructions for the office printer, claim forms, or meetings.

Nielsen pegged the share of smartphones in the US at 31% as of the end of 2010, and has projected the share to climb over 50% this year.
The proportion is higher amongst technology workers and managers, and therefore provides a fertile space in which QR and bar-codes can be used as part of work environment where most staff will have their own readers.

Since many are already using this functionality to scan products, find coupons, and book tickets, it makes sense to put the same technology to work in providing information at work.

This can be done in two major ways

  1. Barcodes and QR codes that link a user to work-instructions, knowledge articles, or contextual information
  2. QR codes that link to an online user profile

The standard QR code can fit neatly on a business card, and can transport directly to a meaningful landing zone like a personal profile page that outlines business activity and contact details.

That’s my story and I am sticking to it!

~~~

Matthew Loxton is a Knowledge Management expert, holds a Master’s degree in Knowledge Management from the University of Canberra, and provides pro-bono consulting in Knowledge Management and IT Governance to various medical institutions.

Gossip and Rumor – The Natural Instruments of Cultural Learning?

January 26, 2011

Gossip in organizations is almost universally seen as a negative phenomenon and one that in a work situation should be stamped out if at all possible, but what if there were valuable knowledge to be gained from gossip and information that could improve corporate governance and innovation?

For the purposes of this article I am going to conflate gossip and rumor to a large degree, although at a finer level of granularity the two become very different (McAndrew 2008)– Rumor deals more with externalities and objects, whereas gossip involves interpersonal relationships more.
Gossip is a natural human communicative phenomenon that is part of our evolution (McAndrew and Milenkovic 2002) that does several things, amongst which are articulation of what people are worried about, worries that are insufficiently known, instances of cheating, and changes of positional power or influence.

In case you get bored by the discussion later on, I am going to discuss a quick win first – mining the gossip in your organization as an early-warning system.

Early Warning System

Perhaps I should qualify “early” here – I don’t mean like you have a radar that can detect an oncoming wave of bombers long before they reach your shores, I mean in the sense that you get to sample what is already eating away at your foundations and which may give you an idea of what you are dealing with.
For this reason I strongly recommend that gossip be sampled regularly in order to get on the radar screen threats and weaknesses that might otherwise have been missed until they made themselves known more overtly and systemically.

The technique is to gather gossip without people being afraid that the intent is to track the source and to mete out punishment.
If people fear retribution, the gossip doesn’t go away and neither do the causes, it just goes silent – silencing gossip is the equivalent of switching off power to the radar screen.
The idea is not to encourage gossip as much as simply sample and monitor it.

Depending on the level of trust in your organization, there are two main ways to sample gossip:

  • Get them from the people in the organization who are the Connectors, those who lie at the nexus points in your Social Network
  • Provide staff with an anonymous postbox

OK, so I lied a bit, there is another and far more accurate way, but you aren’t going to like it.

Predictions

Gossip is often the stuff that people believe to be true or likely but that they feel uncomfortable to tell management. This might mean they just have a hunch, but it may also mean that they know something but won’t say it for fear of being embarrassed or the retribution that may visit them if they come clean.

This is where Prediction Markets come in, and boy are you going to hate this!

If you ask how a project is going or what the sales forecast is, you are likely to get the sanitized and upbeat evaluation, but if people bid on a market – even with fake money, something different happens, and you are likely to get a far more accurate picture. Asking “how is the project going” gets you a CYA response, but if there was a pseudo-stockmarket in which people bid on a specific question such as “Project X will achieve Y milestone by Z date”, the results are likely to be far more accurate.
Share-value in the market rises or falls according to the insider knowledge and conviction of buyers, and if the identities of bidders are unknown, it represents the most accurate sampling of the organizational knowledge that one can get.

The downside is that questions must be highly specific and need to be somewhat Boolean in nature (Manski 2006), and people must not be able to game the system for personal gain which is perhaps an insurmountable obstacle since you could get the equivalent of “insider trading” in which a person might deliberately sabotage a project to gain benefit from the market.
However, some academics show evidence that “bear raids” and other attempts to game the market tend to be short-lived and self-correcting (Hanson, Oprea et al. 2006)
On the other hand, economists were the same geniuses that said this about the real stock market prior to the Global Financial Crises that appeared from the shadows and ate about $8 trillion.

I told you that you wouldn’t like it! – but let’s talk very quickly about what gossip is really, after all.

Cultural Learning

In a very real sense gossip is a manifestation of “cultural learning” (Baumeister, Zhang et al. 2004), it emerges under several distinct conditions that have to do with (amongst others) detection of social cheating, message incongruity, fragmented information scent, and power vacuums. It also manifests when there are threats and insufficient information available. Rumors often start because of simple information underload.
In the case of social cheating, gossip functions as the channel to communicate cheating and as the foundation for what has been termed “Costly Punishment” (Henrich, McElreath et al. 2006)

Gossip not only communicates efficiently and fast, but also delivers peer pressure to correct non-conformance with norms of behavior – and this is where there is both a problem and an opportunity.
If organizational goals and policies are out of step with the organization’s social norms, then gossip will “correct” behavior to satisfy the social norms rather than the organizational goal, and people will tend to obey the “ground rules” (Davenport and Prusak 1998; Stacey, Griffin et al. 2000) rather than the institutional rules, and this bears repeating – if the social rules are at odds with your institutional rules, the social rules will win almost every time.
Peer pressure is faster and stronger than institutional power, so it is wise to sample the gossip stream to see if there is significant divergence between the two and measure the results of any remedial interventions for signs of success. – bringing the two closer together puts peer dynamics into play to achieve organizational objectives, rather than undermining or corroding them.

At a different level, sampling the gossip-stream also gives a very good picture of what the organizational culture really is like and to what degree the organizational mission as communicated is infectious, sticky, and resilient – A poorly crafted mission statement simply won’t stand up to the test.

“Ba” and the Water-Cooler Dilemma

One of the foundational objectives of Knowledge Management as a practice is to create both built-environment and mental space that fosters and encourages innovation and knowledge diffusion. In his conceptualization of “Ba”, the mental and physical knowledge terrain (Nonaka and Konno 1999), Nonaka proposes the “water-cooler” phenomenon – that more often than not breakthroughs and acquisition of critical knowledge happens in the spaces between formal meetings and workareas rather than in them, that sometimes the water-cooler and other social spaces see more real work than the formal work areas.
While this is certainly a strong argument, what is also clear is that when left to their own devices, people tend to talk about sports, celebrities, and gossip more than they do about work, and that even when they talk about work it tends to be more about their idiot boss, the lazy workmates, or which members of staff are in a romance or likely to leave, than about work itself.

This leads to somewhat of a dilemma – creating “Ba”, areas and time in which staff can mingle, chat, and relax certainly does increase the likelihood of real innovation and productive spread of knowledge, but it also increases at a larger rate the amount of gossip and non-work related talk.

Conclusion

Gossip isn’t going to go away anytime soon and while it can be reduced both by disciplinary action and removing some of the information-gap causes, it can also be monitored as a good error-signal and mined for content to flag things that are miss-matches between organizational objectives and social rules. Gossip is also a reliable indicator of organizational culture, and can be a valuable source of information that can lead to beneficial intervention programs.
Gossip is something that is likely to increase if knowledge management is done well, but the upside is that it becomes a mechanism for good just as much as it does for serving the craving people have to know about the personal foibles of the powerful and who is sleeping with whom in the office.

~~~

Matthew Loxton is a Knowledge Management expert, holds a Master’s degree in Knowledge Management from the University of Canberra, and provides pro-bono consulting in Knowledge Management and IT Governance to various medical institutions.

Bibliography

Baumeister, R. F., L. Zhang, et al. (2004). “Gossip as cultural learning.” Review of General Psychology
8: 111-121.

Davenport, T., H. and L. Prusak (1998). Working knowledge: how organizations manage what they know. Boston MA, Harvard Business School Press.

Hanson, R., R. Oprea, et al. (2006). “Information aggregation and manipulation in an experimental market.” Journal of Economic Behavior & Organization
60(4): 449-459.

Henrich, J., R. McElreath, et al. (2006). “Costly punishment across human societies.” Science
312(5781): 1767.

Manski, C. F. (2006). “Interpreting the predictions of prediction markets.” Economics Letters
91(3): 425-429.

McAndrew, F. (2008). “Can Gossip Be Good?” Scientific American Mind
19(5): 26-33.

McAndrew, F. T. and M. A. Milenkovic (2002). “Of Tabloids and Family Secrets: The Evolutionary Psychology of Gossip1.” Journal of Applied Social Psychology
32(5): 1064-1082.

Nonaka, I. and N. Konno (1999). The concept of Ba : building a foundation for knowledge creation. Boston MA, Butterworth-Heinemann.

Stacey, R. D., D. Griffin, et al. (2000). Limits of systems thinking Complexity and management; fad or radical challenge to systems thinking. London, Routledge.

 

Controlled Vocabulary

August 4, 2010

Introduction

Language is a powerful thing, it’s not only a prime medium of expression, but it in turn shapes concepts and thinking – terminology frames concepts and makes some ideas more expressible and others less so – it emphasizes or diminishes in turn. Some ideas flow naturally from the syntax and terminology of the language in use and others are not even expressible.

In real terms an argument or proposal resonates better if it is expressed in the dominant terminology, and seems weaker and off-key if it doesn’t, and due to concision effects and psychological set, it allows or limits innovation.

Inconsistent use of jargon and terminology results in higher cost of translation and localization, less effective training and education materials, and raises the cost of product support.

The Foundational Nature of Language

From an Organizational Psychology point of view, Language in the form of endemic jargon, special terms and terminology, and accepted forms of speech and protocol are part of the social structure of an organization.

For example, Chao (1994) proposes six dimensions of Organizational Socialization:

  1. History

  2. Language

  3. Politics

  4. People

  5. Organizational Goals and Values

  6. Performance Proficiency

Language deserves a special mention though because it is through language itself that the other dimensions are expressed and how strongly they are communicated. Historical narratives are elevated or decreased in prominence according to the terminology used to relate them, and so too are the organizational politics detailed and distributed according to the rules and parameters of internal language.

Organizational goals are couched in terms of organizational metaphors, and proficiency itself is measured according to articles of the organizational terminology.

Language thus forms part of what topics are allowable by means of both the “correct” protocols, but also at a more fundamental level by means of the terminology itself.

In this sense, Single-Loop Learning and Type I homeostatic systems in an organization (Argyris1987) are strongly influenced and delimited by the vocabulary that is allowable.

User Experience

A major part of user satisfaction is the feeling of confidence they feel in the product (whether that be using a transit system or a software suite), and in many cases also the degree to which use requires mental computation. Unwelcome processing or decision-making requirements result in low satisfaction.

A major part of this in turn is the continuity of the information architecture – the way terms confirm expectations and make sense, and are used where and when expected. While most suppliers of products take care about simple things such as a hyperlink anchor text being immediately visible on the landing page, many do not consider how multiple designers and engineers may use different text for the same meaning in different parts of the product, its documentation, its sales collateral, its training, and in communication related to the product.

Encountering terminology in unfamiliar context undermines and attenuates information scent, and reduces the user’s confidence and overall satisfaction.

OD & L10N/I18N

Cost-effective Internationalization (I18N) and Localization (L10N) depend on the source language usage being tightly controlled and not having a significant degree of equivocation and ambiguity. The more a single term is used for multiple meanings or multiple terms used for the same meaning, the higher the complexity of translation, the higher the bulk of terms to be translated, and the lower the coherence of the final translated text.

Machine Translation is powerless to fix this, and simply multiplies the variances – requiring lengthy and costly human involvement each time.

Inconsistent terminology equates to duplicated effort and difficulties when it comes to translation of product, documentation, and training materials – greatly increasing the complexity, time, and cost of translation. Creating meaningful Translation Memories when the terminology is overlapping and inconsistent is very difficult, and tends to lead to an even worse degree of inconsistency in all the translated languages.

Likewise, training becomes more costly and less effective when terminology is used with any significant degree of variation in meaning.

Knowledge Management

Most Knowledge-bases rely on keyword searches, and the more sophisticated systems also use tagging, which at heart is still a keyword search and in its best form gathers tags from a Folksonomy.

Unfortunately the power of search-engines in this situation results in very high retrieval but low precision. This results in infoglut and lower search effectiveness, and thus a significant impediment to use of Knowledge-bases to augment knowledge-workers such as customer-support staff, and lowers effective re-use of knowledge.

Since a major component of cost-reduction and quality-improvement in customer-support hinges on use of knowledge-bases, terminology control is a significant factor.

Branding and Market Mastery

Part of gaining mastery or dominating a market niche is having a degree of control over the terminology and therefore the expressible concepts – The degree of influence one player has over the terminology translates directly into their freedom of movement within the domain, the cost incurred in terms of effort to thrive, and the extent to which discourse tends to be channeled in their favor.

At the very least, a clear brand and value proposition relies on message consistency across the many external communications an organization makes – be they the deliberate marketing efforts, training materials, or even HR recruiting information. The terminology used by Recruiters should for example be consistent with those of Sales and Training Materials, and so on. Any one department or group that injects noise will reduce the brand coherence and effectiveness.

Gaining Control

Influence over terminology is not something one can beg, buy, or steal – it can only be attained by thought leadership. In other words, good knowledge management practices around intellectual expression.

It is determined by who is disseminating authoritative information, who provides attractive ideas, and who is leading in thought value – and who gets to saturate the frame of reference and the concept terrain.

An early step in gaining more control over the influence of language is to formalize usage and to self-consciously construct a lexicon detailing what terms mean and where they are used, and it sets the stage for searchable knowledge-bases, single-sourced documentation, and consistent branding.

A low-cost approach is to establish an internal terminology wiki along the lines of wikipedia, and to build and refine a corporate lexicon in three phases of limited crowdsourcing:

  1. Open invitation to internal staff

  2. Invitation to business partners (and industry luminaries) to contribute

  3. Invitation to customers to contribute

Step 1 requires some preparation to identify people who are influential in terminology as well as obtaining buy-in from content-owners and domain experts.

Steps 2&3 are a Marketing bonanza that yield many spinoff benefits.

Making the terminology visible in this manner is not just a step in protecting against erosion of meaningful terminology but also forms part of a knowledge-management approach to organizational-learning.

Conclusion

If an organization is inconsistent in its use of terminology and language, if it vacillates on meaning and implication, if terminology is used hesitantly and passively – then the information scent attenuates, and the audience becomes uncertain and less likely to agree with the message or see the source as trustworthy or authoritative. In addition it leads to escalating costs and loss of effectiveness in training & development, and significant barriers to cost-effective translation & localization.

To get in a position where you influence the discourse and the frame of reference in your market niche you must settle on a controlled vocabulary, use it strongly, and use it consistently over every part of your products, documentation, and communications.

The place to start is inside the company – to practice, refine, and then deliver.

Addendum

Two areas I left out but deserve mention are the effects on Content Management and Health &Safety.
Inconsistent terminology can be a significant safety risk, and this is a topic that deserves its own paper.

Please contribute to my self-knowledge and take this 1-minute survey that tells me what my blog tells you about me. – Completely anonymous.


Bibliography

Argyris C & Schön D (1987) Argyris C & Schön D. “What is an organization that it may learn”. (1987) : .

Chao G, O’Leary-Kelly A, Wolf S et al. (1994) Chao G, O’Leary-Kelly A, Wolf S et al.. “Organizational socialization : its content and consequences”. Journal of Applied Psychology (1994) 79: pp. 730-749.

~~~

Matthew Loxton is a Knowledge Management professional and holds a Master’s degree in Knowledge Management from the University of Canberra. Mr. Loxton has extensive international experience and is currently available as a Knowledge Management consultant or as a permanent employee at an organization that wishes to put knowledge to work.

Knowledge Management: The Disease Model discussed

May 1, 2010

 

 

Some readers of my blog on the Disease Model of Knowledge Transfer might have justifiably wondered if I had been typing after a few beers. Admittedly it was a joy to write, but the back-story is actually quite solid and very interesting. (to me at least).

The issue is one of how we can take models built for one purpose, and apply them productively for a completely unintended purpose – in fact a large proportion of technological and scientific breakthroughs occur in exactly this way. Taking a way of seeing things from one domain to an unrelated domain means that you might impose a degree of artificiality, but still derive benefit from the change in perspective and the new questions that might be productively raised.
Philosophy of Science (PoS as it is hilariously abbreviated) calls this an “Instrumental Theory” approach, and people like Ernst Mach (he of speed-of-sound fame) proposed that many if not all scientific facts and theories were actually just instruments of explanation and not real in any strict sense. Electrons, he held for example, were just a useful concept to further investigation, and not real little ball-like things.

In this way one can plot the “infection characteristics” of obesity even though nobody is saying it is “really” infectious, and Richard Dawkins could propose that one could look at ideas themselves as infectious replicators.

What Prof.Dawkins was trying to do was instill a better understanding in his students as to how evolution works at the gene level, and he emphasized that while genes are teleologically blind and not intentional in any way, variation and selection could nevertheless shape populations of people carrying the genes. To understand evolution one needs to look at the world from the perspective of genes under selective pressure in which there are not enough resources for all of them to be replicated. Successful replicants tend to slowly increase in proportion to those that aren’t simply because it is the victors whose code gets replicated.

To explain this Dawkins proposed a thought experiment in which ideas themselves are seen as a replicator.

Picture a world filled with ideas that aren’t entirely stable and can mutate or join together, and which can replicate from one host mind to the next – sometimes suffering copying errors on the way. There are more potential ideas than minds to run them, and those that don’t get run by a mind die out.
Like the DeLorian or Cuban Heels.

The idea of “memes” (as he named them) itself went viral, and soon it became evident that it was a highly productive way of looking at ideas. Whether or not memes or even temes* are “real” is not terribly important – but what is, is the ability it gives us to do useful things and ask productive questions. *See Prof. Susan Blackmore’s Meme/Teme TED talk online

It allows us to ask why some ideas transfer more readily between people, why some are more stable, why some last longer. It allows us to look at Intellectual Property, Job Aids, and Knowledgebase articles in a new way, and to try new ways of getting ideas to behave in ways that we would prefer.

For example, it asks why gossip and the “corporate grapevine” are so compelling and so fast, and begs us to consider how we could put this to use or gather information from it. In Nonaka’s “Ba” a coffee area or watercooler is a place where people will gather to exchange information – the question is how to increase the work content of that without tunring it sour and putting people off.

A second area that I find an interesting parallel, is in the work of a psychologist of human behavior by the name of Eric Berne. In his Transactional Analysis approach, he proposed that there were somewhat stable “games” that seem to be enacted by people – especially in interpersonal settings. By “games” he didn’t mean fun and party-novelty kind of behavior – he meant that the on inspection one could make out somewhat persistent “rules”, “players”, and “roles”. Important to note however that the dehumanizing form of Game Theory described by the earlier Nash is not what I have in mind at all – that path leads to a dreadfully dehumanizing approach to people and drives highly destructive behavior.

Putting the two together (part of my own research activities) one comes to a perspective in which games and ideas “fight” for space in people’s minds and to get expressed as behavior. Just like genes, some memes work well together and some are mutually exclusive. We even know why (to an extent) some ideas push others out.
For example, if you are thinking of money and especially personal reward, some very specific parts of your brain fire up and they suppress activity in some other parts – you can’t easily run the two sets of circuits at the same time. This is why economic norms suppress social norms and why somebody who was perfectly happy to donate time and effort to do something for a “good cause” might be put off if you pay them to do it. It is also why rewarding people with money is a risky approach and tends to lead to conflict and gaming of the system of rewards.

If you doubt this, try the suggestion of researcher Dan Ariely, and at your next Christmas meal offer your Mother In Law $50 for her trouble. Let me know how that works out for you.

Putting another layer on this, some ideas, like pathogens or genes, have evolved specialized penetration or adhesion mechanisms that are usually very specific to the host they will use – and this is where we can start asking how to make some information easier to use, or stick better, or be easier to locate.

For example, although digital watches and instruments were very hip, they were actually less usable – it takes more processing power to turn a digital readout into what your brain uses than analogue.

You can literally measure the time difference between how long it takes to say if a specific time is still a long way off or near when viewing either an analogue clock-face or a digital readout. For this reason many time-critical instruments in a cockpit are analogue.

This is also why it is important to decide if information is something we want somebody to remember, or if we will just present it to them at the appropriate time. Getting people to memorize product codes or server paths is not as effective as simply presenting them with the information when the time is ripe.
It is also important in GUI design and in how IT needs to be appropriate.

At a higher level, when everybody knows that the “real rules of working here” mean that you aren’t actually allowed to use the eLearning materials or the open-door policy, then they behave according to the game rules of the “real ground rules” not the ones in the employee handbook.

In a future blog I hope to go into some of the practical implications and uses, but for now, this is my story, and I am sticking to it.

~~~~~~~~~

Matthew Loxton is the director of Knowledge Management & Change Management at Mincom, and blogs on Knowledge Management. Matthew’s LinkedIn profile is on the web, and has an aggregation website at www.matthewloxton.com
Opinions are the author’s and not necessarily shared by Mincom, but they should be.

Reflections on Tagging Part II.

April 23, 2010

My first reaction to tagging was surprise, followed shortly by a dose of joy.

 Although I am a longtime user of the Internet, IRC, IM, and many other communication tools on the Net, I was surprised not only that tagging could be such a powerful tool, but also that to a great extent I had been unaware of this.

For me, tagging solves two problems: firstly that my favourites can be stored externally and thus not dependant on a specific machine – changing machines or losing a hard-drive always seems to go with a loss of links to valued information. There are pictures, articles, and downloads that I no longer have, because I simply cannot remember how I found them. Even worse, I can’t even remember what they were.

Secondly, it solves a classification problem.

I sometimes struggle to decide under what category to save a new link, and this results either in a steadily growing taxonomy that becomes increasingly arcane and impenetrable with time, or to inconsistencies of where I put things.
Does something go under “Research” or “UC” or “KM”, and why did I have this folder called “NS”?

Storing multiple copies of links was a thought, but quite often Intranet links change, and it would become an administrative overhead to root out all the occurrences of a link each time.

Tagging potentially solves this because it is no longer bound to a canonical format on a specific machine, but rather takes on the nature of a relational database index, where a classification can be created dynamically by user-constructed query strings.

Unfortunately, the ability for sites like del.icio.us to handle Boolean search terms is at present very limited, and although sites like Connotea[1] allow a more structured search mechanism, they also do not yet allow a structured query language that is entirely user constructed.

At present I can use del.icio.us search with Boolean terms to logically AND tags and NOT tags, but I cannot deliberately exclude by period, language, origin, or person for example. To escape the overwhelming abundance and proliferation of the “soup”, I may for instance, need to exclude postings from a specific poster who I have identified to be prolific but untrustworthy. While this poster may have matched tags that I wish to include, I may still desire to exclude anything they have tagged, and to do this I need a meta-language that would look very much like a structured query language.

There seems to be some development along these lines with structured query languages such as “Squeal” (Spertus, 2007), WebSQL (Arocena, 2007), and Xcerpt (Furche, 2004).

However although they all have elements of it, none of those are specifically targeted at tag searching.

It cannot be long before a structured search language specifically encompassing tags  and meta-tags becomes available, and this would turn the “tag soup” into an instantly structured information subset – Of course that creates the dilemma of how and where one saves the search term itself for future use or reference.

Curiously, one of the very reasons that the “invisible” or “deep” web is opaque is because many large databases of information create classifications on the fly through user-constructed query strings of the kind I am suggesting. One hopes that tag searches would be open in a way that more is revealed, rather than driving everything into islands of information that are mostly hidden.

What I also found fascinating was that social media are curiously attractive, enjoyable, and emotionally “warm” in a way that traditional databases like EBSCO, EMERALD, and LEXUS/NEXUS are socially “cold”.  This “attractiveness” is seemingly unrelated to the level of actual knowledge acquisition or information quantity retrieved.

For example, the human-computing experiment called “ESP Game”[2] has already labeled over 10,000,000 images on the web by getting humans to work collaboratively without any tangible reward. The payoff for the individuals is somewhat in the act of participation in something socially useful – the identification of images in order to make them searchable, but is mainly in the simple pleasure that people get from playing with other people. The sensation of having an anonymous “partner” who is “in tune”, is strangely attractive, if not somewhat addictive.

The parallel between using other people’s discoveries as part of one’s own online heuristic, and normal human or even primate behaviour is to me, very striking.

All primate species appear to be highly motivated to, and to derive pleasure from, learning from others and leaving clues for others to find. In this way, social bookmarking appears to engage with some very ancient and well developed behaviour patterns, and thus fit snugly into the ergonomic requirements we have for information.

Perhaps it reveals a search for mutuality – people who like what I like, are interested in what interests me and are themselves therefore interesting to me.[i]

Rebecca Blood remarked that tagging led her to some surprising self-discovery, by looking post facto at what she had tagged, she came to realise that there were things that she was evidently interested in that she would not have previously said were her top interests. In some sense then, we are what we tag, or at least what we tag demonstrates actual interests as opposed to stated interests, and this self-revelation may be quite emancipatory, or at least informative.

On the negative side, there may be some serious privacy concerns. In a very real sense, you are what you seek – as was evidenced by the release of AOL search terms which enabled quick discovery of individual persons, even though their identities were anonymised.[3]

I am also not sure if it might actually amplify my biases by giving me an ability to screen out discordant information or see only agreeable information.

After having experimented with tagging, I am doubtful that canonical taxonomical systems will be replaced since these represent in effect a sort of hypothesis test in a truly scientific sense. We can pose what we think may be true, and by cementing this in a canonical classification, we open our claim to natural selection – will nature and reality prove it to be true or false, will it stand or fall. In these falsifiable claims – and a canonical taxonomy is indeed a truth claim in which we are able to put our beliefs to the test.

References

  1. “Squeal” (Spertus 2007) http://www9.org/w9cdrom/222/222.html a structured query language for the web

 

  1. WebSQL (Arocena 2007) http://www.cs.toronto.edu/~websql/www-conf/wsql/PAPER267.html

 

  1. Xcerpt (Furche 2004) http://www.pms.ifi.lmu.de/rewerse-wgi4/software/Xcerpt “declarative, rule-based query and transformation language for the Web”

 



[1] Connotea is located at www.connotea.org and is published free of charge by the journal Nature.

[2] www.espgame.org

[3] The release of AOL search strings allowed a researcher to quickly identify a Mrs.Thelma Arnold, even though she was identified only as “searcher #4417749” http://www.nytimes.com/2006/08/09/technology/09aol.html?ex=1312776000en=f6f61949c6da4d38ei=5090


[i] User of the participative labeling game at http://www.espgame.org report a sense of please in finding a compatible partner that in itself serves as a reward.

~~~~~~~~~

Matthew Loxton is the director of Knowledge Management & Change Management at Mincom, and blogs on Knowledge Management. Matthew’s LinkedIn profile is on the web, and has an aggregation website at www.matthewloxton.com
Opinions are the author’s and not necessarily shared by Mincom, but they should be.


%d bloggers like this: