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Translation technology is now widely used almost in all areas where multilingual needs are identified, at least in commercial settings. From a market perspective, it offers a wealth of tools that contribute to speeding up multilingual processes, reducing costs and improving quality. Interestingly enough, the multilingual needs of the third sector and more specifically those of NGOs in the aid chain, seem to have fallen into oblivion as far as translation technology is concerned. We see that there are no easily accessible/shareable large scale resources or tools in this area (translation memory databases, termbases or corpora, to name but a few) and stakeholders, working mostly on a volunteer basis, are ultimately forced to create their own ad hoc materials. With a few exceptions, no reference corpora, public sharing-data initiatives or collaborative experiences can easily be found in the context of not-for-profit. In this scenario, it is my contention that the implementation of language tools and resources specifically designed for the needs of the third sector may see its impact on three key areas: economic, social and technical. The ultimate purpose of the present contribution is to create momentum towards the association of translation technology and the humanitarian aid chain. Sin financiación No data (2019) UEM

When a sudden-onset emergency occurs, the language needs of those affected and those involved in the relief efforts cannot be foreseen. Provided that access to online communication is still available, it is not unlikely that many involved in the crisis will resort to language technologies such as machine translation and initiatives such as crowdsourcing to assist in the urgent need for multilingual communication. This may be done in an attempt to understand the key messages from official bodies, or relief organisations, when there is a lack of professional translators to assist in the multilingual communication process. This approach - machine translation and crowdsourcing - was successfully used in a previous crisis, i.e. the 2010 earthquake in Haiti. However, the use of technologies cannot be taken for granted. Even if they are supposedly used for good, a number of ethical issues should be given consideration before using these technologies, when using them, and in the aftermath of a crisis. In this chapter, we describe those issues by having a closer look at potential crisis translation workflows which rely on machine translation and crowdsourcing.