In the same way that the Web has changed the communication habits ofmillions of people, socialcomputing is evolving to help us work with and in complex adaptivesystems. The insights from Snowden and Jacksonabout ‘foresight’ and complexity, and their relationship with socialcomputing, are fascinating not just for futures planning, but also forre-thinking processes in knowledge intensive organisations likeknowledge management, communication and collaboration processes. Forinstance:
Developing a sensor network: The ability to quickly accessauthoritative guidance from colleagues, and to regular streams ofintelligence regarding clients, competitors, market changes, and so on,is crucial to the development of actionable current awareness. But toooften, companies rely on a handful of sources to feed them information,constrain sharing to document and email centric models and squeezedpeople’s interactions into pre-existing software models and workflows.That leaves the better part of a company’s extensive network ofresources untapped and a void of higher level meta-data or collectiveintelligence derived from people’s diverse activities and contributionsto a social computing platform.
If employees, clients and collaborators are able to contributefragments of information, like tags, bookmarks, comments and links, asthey come across or create the information in the course of their dailywork not only will this be of benefit at the individual level (e.g.there’s no extra or less effort involved), when that information isaggregated, patterns can be determined which help others to spot trendsand focus on hot spots in real-time. That makes for a potent earlywarning system and truly effective current awareness.
Sharing your way to competitive advantage: To operate incomplex networked environments, companies are having to rethink oldmodels based on the control of proprietary information. Snowdenarticulated it in these terms: “The paradigm has shifted. For whole oflast century ownership gave economic power. Now, it is the speed atwhich you exploit things that matters not ownership. A strategy ofopenness makes more things available to you. What matters then is youragility and ability to exploit things.”
Over the last few years we have seen some companies become more openand share their learning/information with clients and otherorganisations. For instance, Innocentive.com enables companies,academic institutions and NFPs to come together in an open innovationmarketplace to post challenges, share ideas and devise breakthroughsolutions. In the UK, several major international law firms establishedthe Banking Legal Technology portal in 2006 due to pressure frominvestment banking clients wishing to reduce costs and streamlineaccess to all advice/information from the different firms. Likewise,Legal OnRamp provides another forum for lawyers share information andshowcase their expertise, and for in-house counsel to access toprecedents of major law firms and the pool their resources with othergeneral counsel.Going forward, we will see companies using increasingvolumes of fragmented data (e.g. tweets, blogs, comments, html linksand pages) to contribute to social extranets, accessible by clients andcompetitors alike.
In that way, companies will get to see more and do more for less. Byopening up the scanning process, not only will they add to the overallpool from which they can draw, they will also be presented with newnarratives and possibilities which would not have been apparent oravailable in a closed setting. It will then be companies’ ability tointerpret and apply the information quickly, innovatively andinsightfully that will provide competitive advantage.
Developing new meaning through deliberate ambiguity: This picture presents a classic example of ambiguity.
There’san old and a young woman in there. Perhaps you see one or both of them.How long did it take you to focus on the different images? Does thatmean anything? Is one more persuasive than the other? Snowden proposed’deliberate ambiguity’ as a vehicle for encouraging emergent meaningand contributing to to the effectiveness and richness of a work.Increasing moves toward the use of fragmented materials in our work,like clipping items from feed readers, adding to them notes and tags,linking the clippings to blog posts and engaging people in furtheronline discussions and idea sharing, we are deliberately introducing ahigher degree of ambiguity to the system. It is precisely thisambiguity that allows us to interpret and give new meaning to thefragments, which provides new perspectives, ideas and interpretations.This is the source of innovation and difference – not best practice andcompliance regimes.
There are also ramifications for traditional informationcategorisation and classification regimes, the purpose of which was todisambiguate and establish order in the system. Efforts to create orderin this way can be counter-productive. If you are looking for somethingthat hasn’t been categorised in the way you expect, then you probablywon’t find it (quickly or perhaps at all). You are also less likely tomake valuable serendipitous discoveries by stumbling across items thatsit outside of traditional categories. As Thomas Gruber (2007) explainsin his article “Ontology of Folksonomy: A Mash-up of Apples andOranges”:
“Tags introduce distributed human intelligence into thesystem. As others have pointed out, Google’s revolution in searchquality began when it incorporated a measure of “popular” acclaim –the hyperlink — as evidence that a page ought to be associated with aquery. When the early webmasters were manually creating directories ofinteresting sites relevant to their interests, they were implicitly”voting with their links.” Today, as the adopters of tagging systemsenthusiastically label their bookmarks and photos, they are implicitlyvoting with their tags. This is, indeed, “radical” in the politicalsense, and clearly a source of power to exploit.”
In that way, user participation in the form of social tagging offersa far more powerful means of discovering information and meaning.
Using technology to provide decision support: Althoughprevious generations dreamed of artificial intelligence and peoplefeeding computers information and receiving answers, we now understandthat the roles should be reversed, and we are interested in usingcomputer networks to augment human intelligence and make it easier forus to make decisions of our own. This is the key differentiating factorabout social computing – it has human agency in it. Whilst computerscan present more data, human agency is needed to determine the meaningof the information fragments. That requires us to deliberatemodel/look at things from different perspectives then present the databack for human-based interpretation and decision making.
To conclude: “the whole point about technology is to providedecision support for human beings not to make decisions” (Dave Snowden).
