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