When the earthquake hit Haiti in January 2010, professors at the MIT Media Lab organized a class to put together a MIT response. As a result of that class, Greg Elliot and Aaron Zinman came up with Konbit, an interactive communication platform. In a country that is at least 50% illiterate, professional internet network companies fall short because they require literacy, access to internet and a résumé-driven culture. And many of the jobs in Haiti do not require literacy. As a result, Konbit lowers the barrier of entry by allowing users to call and communicate with an automated system in their own language. With the support from telecommunications companies, these phone calls are free.

Konbit improves skill-set collection by using statistical analysis to expose hidden skill associations. By gathering which skills are often associated together, we can help people determine additional skills they may have forgotten to mention. The system integrates crowdsourced translation via phone and web. The search function uses expected fuzzymatching for better results, but also provides an extremely simple interface for bulk recruitment via SMS and provides a dual-channel feedback loop for both employee and employer accountability. This feedback mechanism also avoids reducing humans to context-less ratings that often fail to capture complicated hiring scenarios.

Finally, Konbit aims to provide economic value by creating a location-based census of labor capacity. International companies looking to invest in a country like Haiti want to know what skills exist, where they can be found, and the reliability of those workers. Additionally, this skill indexing system can be applied to the international community as well. Future disasters will again require rapid restructuring of labor and aid. The more we know about the primary and secondary skills of the population, the better those skills can be put to use to quickly recover from loss and destruction.

Designed by
Greg Elliott and Aaron Zinman - United States of America