The proliferation of people-powered search engines and social media services, which effectively tap the wisdom of crowds to bubble up the good ideas and good content we care about most, are enabling a profound shift in how we locate, create, and share information.
However, I’m having serious doubts about our preoccupation with crowds and our assumption that mass market preferences and tastes are an indication of quality content and correct answers. Blindly following the ideas presented in The Wisdom of Crowds, the best-selling book by James Surowiecki, can lead us to the best content, but it can also detour us toward what is merely most popular. Granted, tapping into the combined intelligence and input of a random group of people can create optimum conclusions, but it can also skew systems and software to regurgitate the views and suggestions of a vocal minority.
It’s a controversial issue that Jakob Nielsen, usability guru and principal of the Nielsen Norman Group, aptly calls the dilemma of participation inequality. Put simply, participation in the online world more or less follows a 90–9–1 rule, with 1% of users accounting for most of the contributions, 9% contributing from time to time, and a whopping 90% of users preferring to lurk in the background.
Read between the lines and the internet is more than a platform that enables the free flow of content and ideas between all people around the planet; it is a space that can also magnify the importance of a small group of hyperactive contributors, allowing a few voices to dominate a whole conversation. Nielsen says the problem of participation inequality will be with us for a long time; he recommends the best approach as one that rewards people for the quality, not quantity, of the content they contribute.
No doubt this approach will restore the balance when it comes to finding a more representative sample of content. Yet it raises the issue of measuring quality: Who’s to judge? And what if we want to locate and connect with the content creators? The problem is all the more acute if we consider knowledge workers searching for their peers in sectors like law, healthcare, securities, research, and professional services.
Indeed, the advance of social networking and the spread of Web 2.0 technologies attach new importance to expertise location, a trend that collides head-on with the dilemma of participation inequality. Who are these experts? Some may be found among hyperactive contributors who promote themselves as gurus on their sites and blogs, but hidden among the lurkers are many experts whose seldom but worthwhile contributions are drowned out by the torrent of material from a vocal minority.
Granted, there is no single definable process for seeking out expertise, but there are tools to help filter out the noise. One such solution comes from Recommind, whose enterprise search and categorization platform automatically organizes, manages, and distributes large volumes of information from multiple sources. The core technology powering this platform is MindServer, a patented proprietary self-learning engine that automatically identifies the concepts that describe a document or set of data.
But Recommind doesn’t stop at providing personalized information retrieval; it can identify experts in a fully automated and accurate manner by following the bread trail of insights and ideas they leave behind. Basically, it scours data repositories and directories, content management systems, human resource databases, billing systems, and the wider web to provide a broad and holistic view of a person’s capabilities and talents. Rather than creating another data repository, Recommind creates an index pointing at the documents stored in various systems that are a testament to an individual’s skills and talents.
The result is what Craig Carpenter, Recommind’s VP of marketing and business development, calls “LinkedIn on steroids” because it not only locates experts; it shows why they are experts, exposing the body of work and data points to back it up. “People are not always honest—or sometimes they are too modest—so we can’t rely on what they write in their profiles or offer for references.”
Expertise is made up of two things: what you say you know and what you’ve done. Systems that enable a contextual understanding of each person and what makes them special will do more than reveal sales leads and job opportunities. They will go beyond bringing together experts for collaboration. Maybe someday they will connect great minds to solve the truly great problems of our time.