Dr. David Alan Grier is an Associate Professor of International Science and Policy and International Affairs at The Elliot School of International Affairs, George Washington University. Professor Grier is the author of When Computers Were Human (Princeton, 2005) and Too Soon to Tell (John Wiley, 2009). He was also recently elected as 2012 IEEE President. Professor Grier recently gave a talk, entitled “Crowdsourcing and Social Computation in International Development,” and was kind enough to meet with me to discuss the highlights of his presentation.
As the world tries to keep up to speed with the rapid pace of technological change, we can’t help but wonder how these scientific advances are changing the way science itself is done. Walls seem to be coming down everywhere as the internet facilitates communication and transfer of information; new communication technologies allow for the average citizen to participate in extensive data collection and sharing. The buzz seems to be around crowdsourcing and social media. Citizen-based science, participatory sensing, and volunteered geographic information (VGI) are all examples of crowdsourcing: using large-scale labor markets to get work done. Citizen-based science is any scientific work, such as data collection, that can be done by those without formal scientific or technical training; participatory sensing uses large labor markets of citizens as sensors for the world around them, and can make use of smartphones and other mobile sensing devices. Volunteered geographic information usually involves qualitative observations from average citizens about the physical observations made about a particular place that could go to constructing a contributor-based map or database. This work can be as simple as taking pictures, writing up a short description of what you see, and uploading it onto a website, or much more complex and specialized tasks, such as using software to bend protein structures to contribute to immense databases (Folding@Home).
Understanding the potential of tapping into these infinitely large labor markets is the goal of Professor David Alan Grier of the George Washington University Elliot School of International Affairs. I visited Professor Grier in his office, where we discussed the future of crowdsourcing technologies and their potential place in the ever-changing scientific community. He began by pointing out how crowdsourced information has been used since the 1850s. Grier highlighted a personal favorite sitting on his bookshelf: a Works Progress Administration (WPA) project that asked hundreds of people to go out and calculate mathematic equations by hand, resulting in a multi-volume work containing everything from logarithmic tables to beta functions.
So where does the change come in? Can citizens provide observations or information that is useful to the scientific community? Professor Grier seems to believe so. Yet the focus should not be on whether or not that information is out there. One critical challenge is in developing a process where the information needed for science is broken down into smaller steps that are manageable by individuals who need not understand the inner workings of an entire scientific theory. The greatest potential of these volunteer labor markets lies in breaking down these steps into manageable micro-tasks and using them to gather data. Professor Grier simplified it, “setting up each step requires a knowledge and understanding of the entire process, but that is not to say that the people within those steps cannot see patterns that add to the framework.”
One of the obvious concerns, however, is guaranteeing the quality and usefulness of this information. To this end, Professor Grier points out two approaches. The Christmas Bird Count, for example, is often cited as an extremely successful case of using crowdsourced data, where amateur bird watchers produced extremely high quality information. The Bird Count is possible due to the extensive body of knowledge available to amateur bird watchers, who already have a grasp of fairly technical information compiled by specialists. The second approach is based on what was mentioned earlier, the ability to successfully breakdown scientific data gathering processes into parts that can be managed by those who do not have a complete understanding of the entire framework.
This latter approach is where Professor Grier finds the most potential for new communication technologies. He specifically mentions the experience of the relief effort after the earthquake in Haiti on January 12th, 2010. The advantage in using new communication technologies such as Twitter and SMS messaging is their ability to set up a quick infrastructure for information sharing. Moreover, crowdsourced labor was used in a process to translate, decode, and categorize SMS messages received by digital volunteer groups, such as Mission 4636, which constituted a short number that people could send messages to with their location and needs for relief. The developers tapped into the expat Haitian and Francophone African populations in order to translate over 100,000 messages from the Haitian Creole. Intelligible messages were then sent back to a base in California where they were categorized and sent to the relief organizations. Professor Grier points out that people want to volunteer after a disaster because they get a sense of doing something good for the world. But what can incentivize people to participate in scientific activities when they feel they aren’t qualified to do so?
The main challenge comes in breaking down that barrier between the scientists and the average citizen. Professor Grier emphasizes the difficulty scientists face in deciding “when lowering that barrier is a sign of weakness, and when it indicates strength on the part of the scientific community.” This lies mostly in maintaining the balance between making sure the right incentives are in place to guarantee not only participation, but quality information on the part of participants, and making sure scientists are acceptant of this information and actually find it useful. Here we see great potential for the integration of these crowdsourced projects with education. High school teachers are usually very interested in incorporating these types of information gathering into their curricula: it gives them a sense of prestige as well as something to get their students excited about.
Finally, technological advances have made extremely complex sensors available at the palm of our hands. We have all been told not to underestimate the power of a smartphone, but they represent a truly remarkable way to get science working for scientists, using the contributions of the everyday citizen. Professor Grier attempts to instill his students with the notion that these technologies are opening the way for a new group of scientists, who think about their data collection processes in a much more dynamic way, making room for increased participation and more sources of data.
Luisa Castellanos is a Research Assistant in the Science and Technology Innovation Program at the Woodrow Wilson International Center for Scholars, in Washington, D.C. Luisa is also a junior at Georgetown University pursuing a B.S. in Foreign Service in Science, Technology and International Affairs with a concentration in Energy and Environment. She is a native of Brazil, and is interested in issues of energy security and renewables, as well as using new means of communication to shape science and technology policy.