Recently, the New York Times reported on a new approach used for emergency response in Haiti.
A brief excerpt...
Ushahidi suggests a new paradigm in humanitarian work. The old paradigm was one-to-many: foreign journalists and aid workers jet in, report on a calamity and dispense aid with whatever data they have. The new paradigm is many-to-many-to-many: victims supply on-the-ground data; a self-organizing mob of global volunteers translates text messages and helps to orchestrate relief; journalists and aid workers use the data to target the response.
Ushahidi also represents a new frontier of innovation. Silicon Valley has been the reigning paradigm of innovation, with its universities, financiers, mentors, immigrants and robust patents. Ushahidi comes from another world, in which entrepreneurship is born of hardship and innovators focus on doing more with less, rather than on selling you new and improved stuff.
Because Ushahidi originated in crisis, no one tried to patent and monopolize it. Because Kenya is poor, with computers out of reach for many, Ushahidi made its system work on cellphones. Because Ushahidi had no venture-capital backing, it used open-source software and was thus free to let others remix its tool for new projects.
Ushahidi remixes have been used in India to monitor elections; in Africa to report medicine shortages; in the Middle East to collect reports of wartime violence; and in Washington, D.C., where The Washington Post partnered to build a site to map road blockages and the location of available snowplows and blowers.
Think about that. The capital of the sole superpower is deluged with snow, and to whom does its local newspaper turn to help dig out? Kenya.
With every new application, Ushahidi is quietly transforming the notion of bearing witness in tragedy. For a very long time, this was done first by journalists in real time, next by victim/writers like Anne Frank and, finally, by historians. But in this instantaneous age, this kind of testimony confronts a more immediate kind: one of aggregate, average, good-enough truths.
