How To Make Crowdsourcing Disaster Relief Work Better

We must identify successes and mistakes to optimize usefulness of data collected during an emergency.

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Dr. Jennifer Chan, a Public Voices fellow at the OpEd Project, is the director of Global Emergency Medicine in the Department of Emergency Medicine at Northwestern University's Feinberg School of Medicine and an associate faculty member of the Harvard Humanitarian Initiative.

In the wake of Sandy's destruction, digital volunteers mobilized again. From their homes and offices, using iPads and laptops, hundreds of volunteers crowd-sourced information and took on microtasks to help FEMA and other agencies process large swaths of information and speed humanitarian response.

For instance, in the first 48 hours after the hurricane, 381 aerial photos collected by the Civil Air Patrol were viewed by hundreds of volunteers, with the goal of quickly giving an overview of the extent of storm and flood damage. This project was called the Humanitarian OpenStreetMap MapMill project. In response to a request from FEMA, project developer Schuyler Erle volunteered to launch and lead the project. By mid-afternoon November 2nd, more than 3,000 volunteers had assessed 5,131 images, viewing them more than 12,000 times. Just a week later, more than 24,000 images had been assessed. Each view from a digital volunteer—a mother, a researcher, a friend, a colleague—helped FEMA determine the degree of damage along the eastern seaboard, assessing the condition of buildings, roads, and houses, with the aim of helping the agency in its post-disaster recovery and planning. That's an amazing effort.

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But did it actually help?

This isn't the first time digital volunteers have supported disaster-affected communities. Nor is it the first time that those volunteers and other disaster responders have been left wondering: Did that help? If so, how?

After the 2010 Haiti earthquake, 650 volunteers began tracing roads from annotated maps and satellite imagery into an online map called OpenStreetMap. This created a post-disaster map of Haiti, especially Port au Prince, revealing what remained of its roads, buildings, hospitals, and shelters. At the same time, more than 80,000 text messages, mostly in Haitian Kreyol, poured over the country's mobile telephone networks, asking for help, via the short emergency code 4636. "Mission 4636" was a predominantly Haitian-run initiative but was set up with the help of a few international individuals, including Rob Munro, a computational linguist. At first, those messages went to a Web platform where online volunteers—Haitians around the world, including in Haiti—translated and organized these messages. Messages were sent onward to relevant first responders, including the U.S. military, for search and rescue and other emergency activities, and back to radio stations and community groups in Haiti. Each translation took a volunteer about five minutes—not much time for each effort, but cumulatively, an enormous amount of work. Munro's evaluation of the Mission 4636 project found that the power of this effort was that it helped Haitians communicate with one another during the disaster—showing that the work needed to make this happen can occur all around the world and often simultaneously. In other words, a distributed workforce of Haitians with powerful local knowledge was able to help international organizations respond to a disaster—and, more important, to help Haitians help themselves.

[See photos of the aftermath of the earthquake in Haiti.]

In still another project called Ushahidi Haiti, Tufts students had collected information from several data sources, including texts, Twitter, and news websites; they then helped categorize and geolocate this information, offering a map for the responders. Afterwards, the Tufts students insisted on learning whether or not the time they put in resulted in helping. Researchers found that the U.S. Southern Command, which was tasked with undertaking support, search, and rescue operations in Haiti, used some of this information. But we still don't have a deep understanding of how many other responding organizations used it, for what purpose, and if it impacted their response effort. And despite wanting to know, we still know little about how many Haitian nationals knew about it, and if they did use it, whether it affected their lives.