As Tom Sawyer demonstrated, one way to solve a hard problem is to convince a lot of people to devote small amounts of time to work together in the quest for a solution. Maybe Tim Gowers, the Rouse Ball Professor of Mathematics at Cambridge, had Tom Sawyer in mind when he blogged about solving a hard mathematical problem called the density Hales-Jewett problem “by means of a large collaboration in which no single person has to work all that hard …”
Such a problem-solving strategy is commonly called “crowdsourcing.”
I’ve been thinking about crowdsourcing this week after hearing Gil Kalai, an Israeli mathematician, speak about his efforts to use Gowers’s crowdsourcing technique to solve a problem that Kalai has been worrying about for 20 years.
For those not deeply enmeshed in the latest mathematical research, Wikipedia, an almost magical product of international volunteer labor, and the Linux operating system, widely used in scientific computing but developed by a host of volunteer collaborators over a period of years, provide classic examples of successful mass collaborations via the Internet. A more local example is provided by EEBedia, the Wiki site hosted by the Department of Ecology and Evolutionary Biology in CLAS at UConn.
As I try to stay in contact with the large and geographically distributed faculty of the College of Liberal Arts and Sciences, the idea of mass collaboration offers a tempting tool for building a sense of community and creating a platform where information can be easily collected and important decisions can be discussed openly. My experiments in this direction have only been partially successful, but they are promising.
One successful effort at mass collaboration came in response to an inquiry about the college’s international activities. Rather than send the traditional e-mail out through the college hierarchy asking for a report, I set up a Google spreadsheet and asked faculty members to self-report locations where they had research collaborations or other international connections. People responded immediately, and it was very entertaining to watch the spreadsheet fill up over the course of about 48 hours. The result was this map of CLAS’s international connections, the making of which required a very small amount of work by a large number of people:
A second successful effort came out of a desire to identify faculty members with an interest in environmental research. Again, the platform was Google Docs, and the result was the gathering of a lot of information very fast. The resulting spreadsheet shows the breadth of interests in the college.
Less successful, overall, has been my attempt to use collaborative software inside the dean’s office. I’m devoted to it, and other members of the dean’s staff range from enthusiastic to tolerant, but somehow we haven’t managed to abandon the obsolete process of circulating e-mails and replace it with wiki-hosted multi-person conversations. There’s clearly more cultural adjustment that has to take place.
Regardless of the relative success or failure of these local efforts, it’s clear that the ability to mobilize large numbers of people to work together in real-time on problems is a feature of the Internet that has not yet been fully comprehended.
Scholarship – in any field of study – is, after all, a mass collaboration, where many individuals make smaller contributions and share them, leading to progress on the large scale. Crowdsourcing opens the door to a change in scale, with many more people making smaller contributions, but faster. I believe that Wikipedia, Gowers’s project, the Linux operating system, and other successful mass collaborations show that such a change of scale offers, ultimately, the possibility of revolutionary change in the way scholarship is carried out.
Read more posts by Jeremy Teitelbaum, dean of the College of Liberal Arts and Sciences, on his blog.