In the same way that the Web has changed the communication habits of millions of people, social computing is evolving to help us work with and in complex adaptive systems. The insights from Snowden and Jackson about ‘foresight’ and complexity, and their relationship with social computing, are fascinating not just for futures planning, but also for re-thinking processes in knowledge intensive organisations like knowledge management, communication and collaboration processes. For instance:
Developing a sensor network: The ability to quickly access authoritative guidance from colleagues, and to regular streams of intelligence regarding clients, competitors, market changes, and so on, is crucial to the development of actionable current awareness. But too often, companies rely on a handful of sources to feed them information, constrain sharing to document and email centric models and squeezed people’s interactions into pre-existing software models and workflows. That leaves the better part of a company’s extensive network of resources untapped and a void of higher level meta-data or collective intelligence derived from people’s diverse activities and contributions to a social computing platform.
If employees, clients and collaborators are able to contribute fragments of information, like tags, bookmarks, comments and links, as they come across or create the information in the course of their daily work not only will this be of benefit at the individual level (e.g. there’s no extra or less effort involved), when that information is aggregated, patterns can be determined which help others to spot trends and focus on hotspots in realtime. That makes for a potent early warning system and truly effective current awareness.
Sharing your way to competitive advantage: To operate in complex networked environments, companies are having to rethink old models based on the control of proprietary information. Snowden articulated it in these terms: “The paradigm has shifted. For whole of last century ownership gave economic power. Now, it is the speed at which you exploit things that matters not ownership. A strategy of openness makes more things available to you. What matters then is your agility and ability to exploit things.”
Over the last few years we have seen some companies become more open and share their learning/information with clients and other organisations. For instance, Innocentive.com enables companies, academic institutions and NFPs to come together in an open innovation marketplace to post challenges, share ideas and devise breakthrough solutions. In the UK, several major international law firms established the Banking Legal Technology portal in 2006 due to pressure from investment banking clients wishing to reduce costs and streamline access to all advice/information from the different firms. Likewise, Legal OnRamp provides another forum for lawyers share information and showcase their expertise, and for in-house counsel to access to precedents of major law firms and the pool their resources with other general counsel.Going forward, we will see companies using increasing volumes of fragmented data (e.g. tweets, blogs, comments, html links and pages) to contribute to social extranets, accessible by clients and competitors alike.
In that way, companies will get to see more and do more for less. By opening up the scanning process, not only will they add to the overall pool from which they can draw, they will also be presented with new narratives and possibilities which would not have been apparent or available in a closed setting. It will then be companies’ ability to interpret and apply the information quickly, innovatively and insightfully that will provide competitive advantage.
Developing new meaning through deliberate ambiguity: This picture presents a classic example of ambiguity. There’s an 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 that mean anything? Is one more persuasive than the other? Snowden proposed ‘deliberate ambiguity’ as a vehicle for encouraging emergent meaning and 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 further online discussions and idea sharing, we are deliberately introducing a higher degree of ambiguity to the system. It is precisely this ambiguity that allows us to interpret and give new meaning to the fragments, which provides new perspectives, ideas and interpretations. This is the source of innovation and difference – not best practice and compliance regimes.
There are also ramifications for traditional information categorisation and classification regimes, the purpose of which was to disambiguate and establish order in the system. Efforts to create order in this way can be counter-productive. If you are looking for something that hasn’t been categorised in the way you expect, then you probably won’t find it (quickly or perhaps at all). You are also less likely to make valuable serendipitous discoveries by stumbling across items that sit outside of traditional categories. As Thomas Gruber (2007) explains in his article “Ontology of Folksonomy: A Mash-up of Apples and Oranges”:
“Tags introduce distributed human intelligence into the system. As others have pointed out, Google’s revolution in search quality began when it incorporated a measure of “popular” acclaim — the hyperlink — as evidence that a page ought to be associated with a query. When the early webmasters were manually creating directories of interesting sites relevant to their interests, they were implicitly “voting with their links.” Today, as the adopters of tagging systems enthusiastically label their bookmarks and photos, they are implicitly voting with their tags. This is, indeed, “radical” in the political sense, and clearly a source of power to exploit.”
In that way, user participation in the form of social tagging offers a far more powerful means of discovering information and meaning.
Using technology to provide decision support: Although previous generations dreamed of artificial intelligence and people feeding computers information and receiving answers, we now understand that the roles should be reversed, and we are interested in using computer networks to augment human intelligence and make it easier for us to make decisions of our own. This is the key differentiating factor about social computing – it has human agency in it. Whilst computers can present more data, human agency is needed to determine the meaning of the information fragments. That requires us to deliberate model/look at things from different perspectives then present the data back for human-based interpretation and decision making.
To conclude: “the whole point about technology is to provide decision support for human beings not to make decisions” (Dave Snowden).