Abstract
This chapter examines the impact of augmented reality in relation to translation. How can translation be augmented by technology? How is the translator empowered through partnerships with non-humans and what do these mean epistemologically? How can theories of translation be reframed to include reflections on the extant synergies between humans and non-humans? The discussion draws on theories and concepts related to human–computer interaction, digital business, and robotics. Given the novelty and contemporary nature of the subject, reference material has been drawn from recent online and industry sources. The argument is that augmentation is not a threat (cf. Davenport and Kirby, Harvard Business Review, 93(6), 58–65, 2015) to translators or translation, but a disruptive, innovative change that might allow for human–technology partnerships that generate new forms of knowledge and perception.
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Notes
- 1.
“L’homme transformé peut intégrer les avantages de l’intelligence artificielle, coupler son cerveau à des cerveaux informatiques qui l’aident à traiter des problèmes complexes. Cet homme est de surcroît transformé par les nouvelles interfaces homme/machine. C’est une transformation par ‘explantation’ plutôt que par ‘implantation.’ Il devient ainsi le ‘neurone’ d’un réseau plus grand que lui, auquel il s’interface.” (de Rosnay 2015, p. 42; original quote).
- 2.
“le traducteur ne se rend pas toujours compte que ce qu’il fait s’inscrit nécessairement dans un contexte écologique” (Vihelmaa 2010, p. 857; original quote).
- 3.
“the term ‘chatbot’ refers to a computer program configured to simulate an intelligent conversation with users via voice, images, video and/or text on an instant message basis. […] chatbots may provide users with text-to-speech and speech recognition functions such that users may interact with a chatbot similarly as in communication with a real person. The chatbot may therefore recognize a user’s speech, convert it into machine-readable form, process user requests, and deliver corresponding responses as spoken language.” (TERMIUM Plus® 2019, online).
- 4.
“Agile” refers to a series of methodologies for developing software, which appeared as a new stream of thought in the late 1990s. In the translation sector, agile refers to a “better, smarter approach” to translation processes (Smartling 2019) where workflows are automated and simplified to accelerate content delivery, individuals are valued over processes and tools, flexibility takes over process (personalized workflows are created), cross-team information sharing is crucial, learning is stimulated and possible feedback is implemented at each step of the translation process.
- 5.
- 6.
- 7.
“You can now dictate to your software […] Users can open the app on their devices, start memoQ on their PC, and connect the two by scanning a QR code. The app relies on the cloud-based speech recognition that is part of iOS, and sends everything users dictate straight to memoQ. Users can control every aspect of memoQ’s translation interface through commands specific to the translation environment, in any of the 30+ languages that have dictation support in their smartphones.” (memoQ 2018).
- 8.
- 9.
E.g., most current advanced translation platforms handle only a small fraction of languages and dialects spoken across the globe. Also, in specialized contexts, such as the medical or legal contexts, AI systems require domain-specific language examples for training.
- 10.
“a combination of human, structural and relational capital” (Risku et al. 2010, p. 85).
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Mihalache, I. (2021). Human and Non-Human Crossover: Translators Partnering with Digital Tools. In: Desjardins, R., Larsonneur, C., Lacour, P. (eds) When Translation Goes Digital. Palgrave Studies in Translating and Interpreting. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-51761-8_2
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