I’ve been attending the Ubiquitous Crowdsourcing
workshop today @ Ubicomp
. We were a small group of 10 people only, but the quality of the talks has been really high, and the discussion that followed very intriguing. A nice blend of applications and theory was presented. What it emerged was a pretty much consistent picture of what the challenges in crowdsourcing are: for example, incentives, quality assurance, business models. However, what also emerged from the presentations was that solutions widely vary. During discussion, social scientist Thomas Erickson from IBM suggested a classification framework to characterise different crowdsourcing applications, which may help scientists understand what solutions fit best their specific problem. The framework is simple yet very useful, and distinguishes 2 orthogonal dimensions only, time and place
: same time same place (e.g., audio-centric apps), different place same time (e.g., an enterprise language translation tool presented by the keynote speaker, Uyi Stewart, also from IBM), same place different time (e.g., Cyclopath
, presented by Thomas himself), and different place different time (a la wikipedia).
The picture is not as simple as that though. Michael N. Huhns, from the University of South Carolina presented a case study where architects
built a new university campus WITHOUT roads, let people walk for a year around it, THEN built paved roads following the paths that people used the most. It never occurred to me that the simple act of “walking” could be seen as crowdsourcing, I always thought crowdsourcing required some intention, never mind how simple the task is. But here we go: un-intentional vs task-driven crowdsourcing!
Last thought: crowds vs communities. Lots of work goes on to create incentives to retain and sustain a crowd. At what point will the crowd (meaning a set of individuals working somehow competitively towards a task) becomes a community (where competition disappears and is transformed into cooperation)? And what are the consequences?