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AI시대 인간번역과 기계(NMT)번역의 공존-경영학 ‘확장(Augmentation)전략’ 중심Coexistence of humans and machines in the era of artificial intelligence

Other Titles
Coexistence of humans and machines in the era of artificial intelligence
Authors
김순미
Issue Date
Aug-2018
Publisher
한국통역번역학회
Keywords
NMT; human-machine coexistence; imployability; post-editing; translation and technology
Citation
통역과 번역, v.20, no.2, pp 1 - 32
Pages
32
Journal Title
통역과 번역
Volume
20
Number
2
Start Page
1
End Page
32
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4374
DOI
10.20305/it201802001032
ISSN
1229-6074
Abstract
Human translators are deeply worried that they might be replaced by machines capable of translating and interpreting through deep learning and big data analysis. This paper takes a complementary mindset rather than either-or mindset to shift translation’s relationships with machines from automation to augmentation. The objective of this study is to set out specific areas of works where humans can coexist with intelligent machines, turning this challenge into an opportunity to expand the scope of translation rather than diminishing it. This paper adopts a model from the business administration field as a framework. It is “five-paths toward employability” (Davenport & Kirby, 2015) based on “augmentation strategy” and “complementarity” (Autor, 2014). Based on the characteristics of translation in this changing world, I could derive employable areas for human translators in the age of AI: human translators can ‘step up’ as managers establishing a platform, overseeing the whole translation process, building corpus database and coordinating collaboration among participants; ‘step aside’ as communicators catering to the linguistic and cultural needs of each party; ‘step in’ as revisers conducting pre-editing or post-editing for translations done by machines; ‘step narrowly’ as translators doing works only humans can do like literary translation; ‘step forward’ as innovators or entrepreneurs creating new areas of business such as combining language service with voice recognition, applying augmented reality technology into translation.
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