As revolution spread across North Africa and the Middle East in 2011, participants and observers of the events were keen to engage via social media. However, saturation by Arab-language content demanded a new translation strategy for those outside the region to follow the information flows—and for those inside to reach beyond their domestic audience. Crowdsourcing was seen as the most efficient strategy in terms of cost and time to meet the demand, and translation applications that harnessed volunteers across the internet were integrated with nearly every type of ICT project. For example, as Steve Stottlemyre has already mentioned on this blog, translation played a part in tools like the Libya Crisis Map, and was essential for harnessing tweets from the region’s ‘voices on the ground.’ If you have ever worried about media bias then you should really worry about the impact of translation. Before the revolutions, the translation software for Egyptian Arabic was almost non-existent. Few translation applications were able to handle the different Arabic dialects or supply coding labor and capital to build something that could contend with internet blackouts. Google’s Speak to Tweet became the dominant application used in the Egyptian uprisings, delivering one homogenised source of information that fed the other sources. In 2011, this collaboration helped circumvent the problem of Internet connectivity in Egypt by allowing cellphone users to call their tweet into a voicemail to be transcribed and translated. A crowd of volunteers working for Twitter enhanced translation of Egyptian Arabic after the Tweets were first transcribed by a Mechanical Turk application trained from an initial 10 hours of speech. The unintended consequence of these crowdsourcing applications was that when the material crossed the language barrier into English, it often became inaccessible to the original contributors. Individuals on the ground essentially ceded authorship to crowds of untrained volunteer translators who stripped the information of context, and then plotted it in categories and on maps without feedback from…