Translation technobabble: An exploration of online discourse about machine translation and artificial intelligence using corpus driven discourse analysis and appraisal theory

Abstract

This research explores the online discourse surrounding translation technology , specifically machine translation and artificial intelligence . This is done by comparing and contrasting different stakeholders, their attitudes and the linguistic resources they use to express these attitudes. This is accomplished by analysing discourse produced by the public, by language service providers and by language software development companies using the methodologies of corpus driven discourse analysis and appraisal th eory. The corpus driven discourse analysis shows partial overlap in the themes that the various stakeholders discuss within the discourse, although some themes unique to each stakeholder also emerge. Further investigation with discourse analysis and appraisal theory reveals that these overlapping themes are framed differently by the different stakeholders , through different associations and how these are expressed. In particular, the capabilities of machine translation and artificial intelligence are discussed by all stakeholders and especially by the software companies, who focus o n incorporating these translation technologies as part of an overall business strategy. Language service providers, in contrast , focus on the role of humans as essential to the translation process and quality of the final product. The public focuses on the larger moral debate, taking into account potential consequences of the use of machin e translation and artificial intelligence. Th e data from this thesis shows a general gradation of attitudes towards translation technology from software companies as the most optimistic to the public as the most pessimistic.