Human vs. Machine: The Future of Translation in an AI-Driven World

DOI

10.2991/978-94-6463-618-5_19How to use a DOI?

Keywords

Machine translation (MT); Artificial Intelligence (AI); natural language processing (NLP)

Abstract

The era of digitalization and advanced technology has revolutionized information exchange, leading to unprecedented efficiency and transformative shifts. Advanced language models are capable of automating routine translation tasks and facilitating communication across languages, making information more accessible globally. In the business world, the rapid development of artificial intelligence (AI) and natural language processing (NLP) have significantly aided humans in the language and translation landscape. This article explores the transformative impact and potential of advanced language models. It examines the strengths and weaknesses of both human and machine translation, emphasizing the unique value human translators bring to complex communication scenarios. The research employs a descriptive approach, synthesizing insights from expert opinions, scholarly publications, and online resources. It also utilizes quantitative analysis to assess the performance and limitations of translation tools. The findings highlight AI’s potential to enhance efficiency and facilitate cross-cultural communication. However, it also underscores the persistent need for human expertise in coping with nuanced meanings, cultural contexts, and ethical considerations. The article exposes the potential of Human-in-the-Loop Translation (HITL), a collaborative approach that combines AI’s efficiency with human expertise to correct and improve models. The conclusion advocates for a collaborative approach, between humans and machines, as copilots, where AI augments human capabilities, and humans augments AI with emotional and cultural intelligence, leading to more accurate, efficient, and culturally sensitive translations.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Antoine Falempin
AU  - Dinda Ranadireksa
PY  - 2024
DA  - 2024/12/29
TI  - Human vs. Machine: The Future of Translation in an AI-Driven World
BT  - Proceedings of the Widyatama International Conference on Engineering 2024 (WICOENG 2024)
PB  - Atlantis Press
SP  - 177
EP  - 183
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-618-5_19
DO  - 10.2991/978-94-6463-618-5_19
ID  - Falempin2024
ER  -