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dc.contributor.authorMassey, Gary-
dc.contributor.authorEhrensberger-Dow, Maureen-
dc.date.accessioned2018-02-27T15:32:40Z-
dc.date.available2018-02-27T15:32:40Z-
dc.date.issued2017-06-23-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/3278-
dc.description.abstractDevelopments in artificial intelligence (AI) and deep learning (DL) have led to increasing effective machine-translation systems, most recently evident in the measurable improvements achieved by neural machine translation (NMT) over existing statistical machine translation (SMT) systems. Although NMT is still at the R&D stage, initial test results on both in-domain (e.g. Junczys-Dowmunt et al. 2016) and out-of-domain (e.g. Wu et al. 2016) performance have been promising. New AI and DL technologies are set to change the face of translation as well the nature and the distribution of translators’ and other language mediators’ primary tasks. The Translation Automation User Society (TAUS), for instance, is predicting Fully Automatic Useful Translation (FAUT) by about 2030 (Massardo et al. 2016). Yet, although theoretical and practical courses on computer-aided and machine translation are widespread in language mediator education, less attention has been directed towards how recent advances in AI and DL might feasibly and coherently be accommodated in competence profiles, development models and curricula. This presentation addresses the challenge to language mediator education posed by AI in general and NMT in particular. From the perspective of competence-oriented curriculum development, it considers the ways in which students can gain the knowledge and toolkits to learn when and how new technologies should be embraced, and proposes a framework for when and how the added value of human intuition, creativity and ethics might be deployed in a future “re-humanized” approach to language mediator education.de_CH
dc.language.isoende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectArtificial intelligencede_CH
dc.subjectLanguage-mediator educationde_CH
dc.subjectTranslationde_CH
dc.subjectNeural machine translationde_CH
dc.subject.ddc410.285: Computerlinguistikde_CH
dc.subject.ddc418.02: Translationswissenschaftde_CH
dc.titleLearning machines and teaching humansde_CH
dc.typeKonferenz: Sonstigesde_CH
dcterms.typeTextde_CH
zhaw.departementAngewandte Linguistikde_CH
zhaw.organisationalunitInstitut für Übersetzen und Dolmetschen (IUED)de_CH
zhaw.conference.detailsPoints of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
Appears in collections:Publikationen Angewandte Linguistik

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Massey, G., & Ehrensberger-Dow, M. (2017, June 23). Learning machines and teaching humans. Points of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017.
Massey, G. and Ehrensberger-Dow, M. (2017) ‘Learning machines and teaching humans’, in Points of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017.
G. Massey and M. Ehrensberger-Dow, “Learning machines and teaching humans,” in Points of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017, Jun. 2017.
MASSEY, Gary und Maureen EHRENSBERGER-DOW, 2017. Learning machines and teaching humans. In: Points of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017. Conference presentation. 23 Juni 2017
Massey, Gary, and Maureen Ehrensberger-Dow. 2017. “Learning Machines and Teaching Humans.” Conference presentation. In Points of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017.
Massey, Gary, and Maureen Ehrensberger-Dow. “Learning Machines and Teaching Humans.” Points of View in Translation and Interpreting, Kraków, Poland, 22-23 June 2017, 2017.


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